Welcome to our comprehensive guide on how to install Matplotlib in Python! If you're looking for information on "command to install matplotlib in Python," or "how to install Matplotlib in Python IDLE," you've come to the right place. Matplotlib is a powerful data visualization library used by data scientists, analysts, and Python enthusiasts to create stunning plots and charts. In this blog, we'll walk you through the step-by-step installation process, ensuring you can quickly and easily start leveraging Matplotlib's capabilities for your data visualization needs. Whether you're a beginner or an experienced Python user, we've covered you. Let's dive in and get Matplotlib up and running on your system!

## How to Install Matplotlib in Python Using Command Prompt

To install Matplotlib in Python, you can follow these simple steps. Matplotlib is a popular data visualization library that allows you to create a wide range of plots and charts.

### Step 1: Check Your Python Installation

Before installing Matplotlib, ensure you have Python installed on your system. Open your terminal or command prompt and enter the following command to [check your Python version](https://www.almabetter.com/bytes/articles/how-to-check-python-version):

```plaintext
python --version
```

If Python is not installed, download and install it from the official Python website: [https://www.python.org/downloads/](https://www.python.org/downloads/)

### Step 2: Open a Terminal or Command Prompt

Open a terminal or command prompt on your computer. The exact method varies depending on your operating system.

### Step 3: pip install Matplotlib in Python

To install Matplotlib, you can use Python's package manager, pip. Enter the following command:

```plaintext
pip install matplotlib
```

This command will download and install Matplotlib and its dependencies. Wait for the installation process to complete.

### Step 4: Verify the Installation

After the installation, you can verify it by running a simple Python script. Create a Python script (e.g., verify\_matplotlib.py) with the following content:

```plaintext
import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4])
plt.ylabel('Some numbers')
plt.show()
```

Save the script and run it using the following command:

```plaintext
python verify_matplotlib.py
```

If Matplotlib is correctly installed, a window displaying a simple plot should appear.

That's it! You've successfully installed Matplotlib in Python and are now ready to create beautiful data visualizations in your Python projects.

## How to Import Matplotlib

Once Matplotlib is installed, you need to import it into your Python scripts or interactive sessions before you can use its functions. The standard way to import Matplotlib is:

```plaintext
import matplotlib
```

This line makes the entire Matplotlib library available for use in your current environment. While `import matplotlib` working, it's very common when working with plotting to import the `pyplot` submodule with a shorter alias, `plt`:

```plaintext
import matplotlib.pyplot as plt
```

Throughout tutorials and examples, you will frequently see `matplotlib.pyplot` imported as `plt`. This is the recommended convention for using the plotting functions within Matplotlib. For basic usage, just `import matplotlib` is sufficient, but for creating plots, It `import matplotlib.pyplot as plt` is standard practice.

## Verifying the Matplotlib Version

It can be helpful to check which version of Matplotlib you have installed. This is useful for ensuring compatibility with certain code examples or for debugging purposes.

You can easily check the installed version using the `__version__` attribute:

```plaintext
import matplotlib
print(matplotlib.__version__)
```

If you used the `pyplot` import convention, you can still check the main library version like this:

```plaintext
import matplotlib.pyplot as plt # Or just import matplotlib
print(matplotlib.__version__)
```

Run this code in your Python environment, and it will output the version number of your installed Matplotlib library.

## Conclusion

In conclusion, we've provided you with a straightforward guide on how to install Matplotlib in Python 3.6. Following these steps, you've learned how to set up the Matplotlib library in Python, an essential skill for anyone pursuing a [Python tutorial](https://www.almabetter.com/bytes/tutorials/python) or a [Data Science course](https://www.almabetter.com/courses/full-stack-data-science).

With Matplotlib successfully installed, you are now well-equipped to harness the power of this versatile data visualization library for all your plotting needs. Whether you're a beginner taking your first steps in Python or an aspiring Data Scientist, Matplotlib is an invaluable tool to bring your data to life.

Remember that this is just the beginning of your Python journey, with endless possibilities. As you dive deeper into Data Science and programming, Matplotlib will be a valuable asset in your toolkit.

Stay curious, keep exploring, and continue learning. If you are looking for online platforms to learn more about Python or Data Science as a student, we recommend selecting institutes that offer a [pay after placement](https://www.almabetter.com/bytes/articles/top-pay-after-placement-courses-in-india) model to avoid financial risks.

We wish you the best in your Python and Data Science endeavors!

Learn how to install Matplotlib in Python with our step-by-step guide. Get started on developing stunning and informative data visualizations effortlessly. 


How to Install Matplotlib in Python.webp

Data Science

How to Install Matplotlib in Python with Detailed Steps

If you've ever wondered about the vast world of operating systems and thought, "What's the operating system name of my device?" or "How many operating systems are out there?" - you've come to the right place. In this comprehensive guide, we'll not only list the types of operating systems but also delve into the names of operating systems that have shaped the digital landscape. Whether you're a tech enthusiast looking to expand your knowledge or someone seeking the perfect operating system for your device, our operating system list will provide insights into the 5 operating system names you need to know. Let's dive into the fascinating realm of operating system names and discover the diverse world of operating systems!

![list of operating system](https://almablog-media.s3.ap-south-1.amazonaws.com/what_is_operating_system_3b4b575025.jpg)

List of Operating System

## **List of All Operating Systems**

Before delving into the comprehensive list of operating systems, let's begin by understanding what operating systems entail.

Operating systems, often abbreviated as OS, are the unsung heroes of modern computing. They serve as the fundamental software layer that facilitates interaction between hardware and software components of a computer or electronic device. An OS acts as a bridge, managing resources, coordinating tasks, and ensuring a seamless user experience. Now, let's embark on a journey through the history of operating systems, exploring the evolution of these essential components while uncovering the 5 OS names that have left an indelible mark on the world of technology.

**The Evolution of Operating Systems:**

*   1950s - The Beginnings: The concept of operating systems took root in the 1950s when computers were large, room-filling machines. Early systems were incredibly primitive and required manual input to perform even the most basic tasks. These systems had no names as we know them today.
*   1960s - The Rise of Batch Processing:In the 1960s, the era of batch processing began. IBM's OS/360, introduced in 1966, is a notable example. It revolutionized computing by allowing multiple tasks to be processed sequentially, setting the stage for more advanced OS development.
*   1970s - The Birth of Unix: The 1970s saw the emergence of Unix, a revolutionary operating system developed at Bell Labs. Unix introduced the concept of multitasking, allowing multiple processes to run simultaneously. It also marked the birth of the concept of an "OS name." Unix would become the foundation for many modern OS variations.
*   1980s - The Personal Computing Era: With the advent of personal computers, operating systems like MS-DOS (Microsoft Disk Operating System) and Apple's Macintosh System Software (later MacOS) gained prominence. These OS names became synonymous with the rise of the PC.
*   1990s - The Windows Era: Microsoft's Windows series, starting with Windows 3.0 in 1990, became dominant in the OS market. Windows 95, Windows 98, and Windows XP are some of the iconic OS names from this era.
*   2000s - The Proliferation of Linux: [Linux](https://www.almabetter.com/bytes/articles/linux-interview-questions), a Unix-like open-source OS, gained traction in the 2000s, offering a free and flexible alternative to proprietary systems. This marked a significant shift in the OS landscape.
*   2010s - The Mobile Revolution: As smartphones and tablets gained prominence, iOS, and Android emerged as leading operating systems, bringing the concept of OS names to the palm of our hands.

Today, we have an extensive OS name list featuring many operating systems, including [Windows](https://www.almabetter.com/bytes/articles/how-to-install-python-in-windows-os), MacOS, Linux distributions, iOS, Android, and many more. These systems continue to evolve, shaping the way we interact with technology. As we dive deeper into our exploration, we'll uncover the all-encompassing list of operating system names that have played pivotal roles in the history and future of computing.

## **5 Operating System Names List**

### First-ever computer OS list

Below is the computer systems list that was developed first:

*   GM-NAA I/O
*   UNIVAC I Operating System
*   Fortran Monitor System (FMS)
*   IBM 650 Tape System
*   Batch Processing Monitor (BPM)
*   Dartmouth Time Sharing System (DTSS)
*   CTSS (Compatible Time-Sharing System)
*   IBM OS/360

### The First Exclusive Computer Operating Systems

Below is the computer operating system list of the first exclusive computer operating systems

*   Apple Computer.
*   Business Operating System (BOS).
*   Commodore PET.
*   Flex, Flex9, and mini-FLEX.
*   TI99-4.
*   TRS-DOS, ROM OS.
*   First IBM-PC.
*   Sinclair Micro and QX.

### Operating System Name List: Unix Based and POSIX-ready Operating Systems

Below is the list of all operating systems that are Unix Based and POSIX-ready

*   Linux
*   macOS
*   FreeBSD
*   OpenBSD
*   NetBSD
*   AIX (IBM)
*   HP-UX (Hewlett Packard)
*   Solaris (Oracle)
*   IRIX (SGI)
*   QNX
*   MINIX
*   Tru64 UNIX

### Names of Operating Systems From Popular Companies

Below is the OS name list from famous companies

#### **Apple:**

*   macOS
*   iOS
*   watchOS
*   tvOS
*   iPadOS
*   macOS Server

#### **Microsoft:**

*   Windows 1.0
*   Windows 2.0
*   Windows 3.0
*   Windows 3.1
*   Windows 95
*   Windows 98
*   Windows Me (Windows Millennium Edition)
*   Windows 2000
*   Windows XP
*   Windows Vista
*   Windows 7
*   Windows 8
*   Windows 8.1
*   Windows 10
*   Windows 11

#### **Google:**

*   Chromium OS
*   Android
*   gLinux
*   Fuchsia
*   Wear OS

#### **IBM:**

*   OS/360
*   z/OS
*   IBM i
*   AIX
*   OS/2

### List of The Most Popular Operating Systems

Below are names of operating systems that are popular amongst users worldwide.

*   Apple macOS
*   Google's Android OS
*   Microsoft Windows
*   Apple iOS
*   Linux Operating System

## **Conclusion**

In conclusion, operating systems are the silent architects behind our digital experiences, serving as the essential bridge between hardware and software. From the early days of computing with pioneering systems like GM-NAA I/O and UNIVAC I to the modern era with the ubiquitous presence of macOS, iOS, Windows, and Android, we've witnessed a remarkable journey of innovation and evolution.

As we explored the list of operating systems, we've seen how they've shaped how we interact with technology, from the massive mainframes of the past to the sleek smartphones and powerful servers of today. Each operating system, with its unique features and capabilities, has left its mark on the ever-expanding landscape of computing.

Whether you're a tech enthusiast tracing the footsteps of computing history or a user seeking the perfect operating system for your device, this journey through the world of operating systems has provided insights into the names and legacies that continue to define our digital age.

In the grand tapestry of technology, operating systems remain the unsung heroes, quietly orchestrating the symphony of bits and bytes that power our modern lives. Each new iteration and innovation brings us closer to a future where seamless integration and enhanced user experiences continue to be at the forefront.

Explore a comprehensive list of operating systems - from classic to cutting-edge; this thorough blog covers them all. Discover the evolution of OS. Read more!

List of Operating System-min.png

Computer Science

List of Operating System: Top Operating System List for 2024

Microsoft Excel, often referred to simply as Excel, is a powerful spreadsheet application developed by Microsoft. It has become an essential tool in various fields, from business and finance to education and research. Excel offers a wide array of features designed to help users create, manage, analyze, and visualize data effectively. In this blog, we'll explore the features of Microsoft Excel, starting with a brief introduction to the software.

## What is Microsoft Excel?

Microsoft Excel is a part of the Microsoft Office suite, which includes other popular applications like Word, PowerPoint, and Outlook. It is primarily used for creating, editing, and managing spreadsheets. A spreadsheet is a digital grid composed of rows and columns where users can enter, organize, and manipulate data.To truly harness the power of Microsoft Excel, it's essential to explain the features of MS Excel comprehensively, ensuring you can make the most of this versatile tool in your daily tasks.

## Key Features of MS Excel

As we continue our exploration of Microsoft Excel, we will answer the question: 'What are the main features of MS Excel?' to provide you with a deeper understanding of its capabilities. To help you get started on your journey of mastering Excel, we will highlight more than 10 features of MS Excel that are essential for both beginners and experienced users.

### Spreadsheets and Data Organization

At its core, Excel is designed to work with spreadsheets. This is one of the basic features of MS Excel and users can create multiple sheets within a single workbook, making it easy to organize and categorize data. This grid-based structure allows for efficient data entry and management. The features of a spreadsheet in MS Excel, such as its versatile formulas and functions, powerful data visualization tools, and robust sorting and filtering options, empower users to efficiently manage and analyze data within its grid-based structure.

### Formulas and Functions

One of Excel's standout features is its ability to perform calculations and operations on data using formulas and functions. Users can create complex calculations by combining mathematical operators, cell references, and built-in functions. Some commonly used functions include SUM, AVERAGE, IF, and VLOOKUP.

### Data Visualization

Excel offers a variety of [data visualization](https://www.almabetter.com/bytes/articles/data-visualization-for-decision-making) chart types, such as bar graphs, line charts, and pie charts, to help users visualize data trends and patterns. This is one of the main features of MS excel. Creating charts is as simple as selecting data and choosing a chart type, making it an excellent tool for creating informative reports and presentations.

### PivotTables and PivotCharts

PivotTables are powerful tools for summarizing and analyzing large datasets. This is one of the advanced features of MS Excel They allow users to create dynamic summaries, apply filters, and rearrange data to gain insights from different angles. PivotCharts works hand-in-hand with PivotTables to provide visual representations of the summarized data.

### Data Validation and Drop-Down Lists

Excel enables users to create drop-down lists and apply data validation rules to ensure data accuracy and consistency. This feature is particularly useful when multiple individuals are entering data into the same spreadsheet, as it helps prevent errors.

### Conditional Formatting

Conditional formatting allows users to automatically format cells based on specific criteria. This is one of the most important features of MS Excel and this feature helps highlight important data points, trends, or outliers, making it easier to identify key insights in your data.

The formatting features of MS Excel encompass a wide range of options, from conditional formatting for data visualization to custom cell formatting for enhancing the clarity and presentation of your spreadsheets.

### Data Sorting and Filtering

Excel provides robust sorting and filtering capabilities that make it easy to organize and locate specific data within a large dataset. Users can sort data alphabetically or numerically and apply filters to display only the relevant information.

### Data Analysis ToolPak

For advanced statistical analysis, Excel offers the Data Analysis ToolPak, a collection of statistical functions and tools. It includes features like regression analysis, sampling, and hypothesis testing, making it valuable for professionals in fields such as finance, science, and engineering.

### Solver Add-In

The Solver Add-In is a powerful tool for solving optimization problems. Whether you need to maximize profits, minimize costs, or allocate resources efficiently, Solver can help find the optimal solution.

### Collaboration and Sharing

With Microsoft 365 integration, Excel supports real-time collaboration, allowing multiple users to work on a spreadsheet simultaneously. Users can also share files through OneDrive or SharePoint, enhancing collaboration and version control.

### Macros and VBA (Visual Basic for Applications)

Excel's VBA allows users with programming knowledge to create custom macros, which are scripts that automate repetitive tasks or extend Excel's functionality. This feature is especially useful for users seeking to streamline their workflow or develop customized solutions.

### Data Import and Export

Excel facilitates data import from various sources, including databases, web pages, and text files. It also offers multiple export options, allowing users to save their work in formats such as CSV, PDF, and more.

_Learn more with our latest article "_[_Advantages and Disadvantages of MS Excel_](https://www.almabetter.com/bytes/articles/advantages-and-disadvantages-of-ms-excel)_"_

## Conclusion

Microsoft Excel is a versatile and feature-rich spreadsheet application that plays a pivotal role in data management, analysis, and reporting across diverse industries. In this comprehensive guide, we delved into 'What are the features of MS Excel,' ‘What are the 10 features of MS Excel’ and explored the myriad tools and functions that make it an indispensable tool for data management and analysis.

The various features of MS Excel like its robust capabilities, from basic data organization to advanced statistical analysis and automation, make it an invaluable tool for professionals, educators, and students alike. By harnessing the power of Excel's features, users can efficiently handle data-related tasks, make data-driven decisions, and enhance productivity in their respective fields. Whether you're a beginner or an experienced user, mastering Microsoft Excel opens doors to a world of possibilities for data management and analysis.

Explore the comprehensive guide to the features of MS Excel, from data organization to advanced functions. Master Excel for data analysis and productivity.

Features of MS Excel.webp

Top 12 Advanced Features of MS Excel in 2024

Node.js is a powerful JavaScript runtime that allows developers to create server-side applications using JavaScript. When the time comes to uninstall the Node js Ubuntu system, following the proper steps to ensure a clean removal is essential. This comprehensive guide will walk you through the uninstall Node js Ubuntu process while also providing insight into Node.js and its relationship with the Ubuntu operating system.

## Understanding Node.js and Ubuntu

Node.js is renowned for its versatility and efficiency in developing server-side applications. It is particularly well-suited for Ubuntu, a popular Linux distribution known for its stability and developer-friendly environment. Many developers use Node.js on Ubuntu due to its seamless integration, robust package management system, and excellent support for JavaScript development.

Node.js is an open-source, server-side JavaScript runtime environment that allows developers to run JavaScript on the server rather than just in the web browser. It is built on the V8 JavaScript engine, the same engine used by Google Chrome, and it enables JavaScript to be used for creating dynamic and scalable web applications and services.

Node.js provides a non-blocking, event-driven architecture, which makes it particularly well-suited for building real-time applications, web servers, and network applications. Its key features include

**Event-Driven:** Node.js operates on a single-thread event loop, which means it can handle multiple connections simultaneously without requiring multiple threads or processes.

**Asynchronous:** Node.js uses non-blocking I/O operations, efficiently handling many concurrent connections without slowing down or blocking other operations.

**NPM (Node Package Manager):** Node.js has a vast ecosystem of libraries and modules that can be easily integrated into applications. NPM is a package manager that simplifies installing, updating, and managing these modules.

**Fast Execution:** Node.js is known for its fast execution of code due to the V8 engine's optimization.

**Cross-Platform:** Node.js is compatible with various operating systems, making it a versatile choice for developers.

Node.js has gained popularity for building web servers, APIs, and [microservices](https://www.almabetter.com/bytes/articles/microservices-architecture), and many large companies and organizations use it for its efficiency and scalability. It's especially valuable for real-time applications like chat applications, online gaming, and streaming services, where responsiveness and performance are crucial. Additionally, it has a vibrant and active community, continuously developing and maintaining a wide range of modules and libraries, making it a powerful tool for web development.

### Step 1: Open the Terminal

Uninstall Node Ubuntu - Begin the uninstallation process by launching a terminal window on your Ubuntu system. You can do this using the keyboard shortcut Ctrl + Alt + T or by searching for "Terminal" in the Ubuntu Dash.

### Step 2: Checking Node.js and npm Versions

How to uninstall Node JS in Ubuntu - Before you proceed with uninstalling Node.js, it's a good practice to determine which versions are currently installed. To check the Node.js version, use the following command:

**Uninstall node from Ubuntu-**

```plaintext
node -v
```

For npm (Node Package Manager), execute the following:

**Uninstall Node JS in Ubuntu-** 

```plaintext
npm -v
```

Take note of these versions as you may need them for future reference when reinstalling Node.js.

_Check out the_ [_Node JS tutorial_](https://www.almabetter.com/bytes/tutorials/nodejs)_!_

### Step 3: Uninstall Node JS Ubuntu Using APT

How to uninstall node in Ubuntu - it relies on the APT (Advanced Package Tool) package manager for handling software installations. To uninstall Node js Ubuntu, you'll start by removing the Node.js package. Enter the following command in the terminal:

**Node uninstall command Ubuntu-**

```plaintext
sudo apt-get remove nodejs
```

This command will effectively remove the Node.js package. Still, it will not address the global npm packages. If you wish to remove npm as well, use the following command:

```plaintext
sudo apt-get remove npm
```

### Step 4: Removing Global npm Packages

After uninstalling Node.js, you may want to consider removing any global npm packages to free up disk space. To list the globally installed npm packages, run the following:

```plaintext
npm list -g --depth=0
```

You can manually uninstall Node js Ubuntu for each package using the npm uninstall -g command, followed by the package name.

### Step 5: Verification of Uninstallation

To ensure that Node.js and npm have been successfully uninstalled, you can recheck their versions by executing the following commands:

**Uninstall node and npm Ubuntu-**

```plaintext
node -v
npm -v
```

If the uninstallation is successful, these commands will result in error messages indicating that the programs are not found.

### Step 6: Clean up

Node js uninstall Ubuntu - While Node.js and npm have been uninstalled, some residual configuration files or directories may remain. To remove these, run

```plaintext
sudo apt-get autoremove
```

This command will eliminate any packages that were automatically installed to meet the dependencies of Node.js and npm.

### Step 7: Inspect for Remaining Files

How to uninstall node from Ubuntu - Occasionally, configuration files or directories linked to Node.js or npm might not be automatically removed. To search for any remaining files or directories, use

```plaintext
whereis node
whereis npm
```

If any locations are listed, navigate to those directories and delete any remaining files.

_Check out our_ [_pay after placement courses_](https://www.almabetter.com/bytes/articles/top-pay-after-placement-courses-in-india) _like the_ [_Full Stack Web Development Course_](https://www.almabetter.com/courses/full-stack-web-development)_._

## Conclusion

To Uninstall Node JS Ubuntu system is a systematic process ensuring clean removal. Following these steps, you can effectively eliminate Node.js and npm. If you decide to reinstall Node.js in the future, you can easily do so by following the installation instructions for Ubuntu as provided on the official Node.js website. The compatibility and synergy between Node.js and Ubuntu make them an excellent choice for developers seeking a robust environment for JavaScript development on the server side.

Node.js is a JavaScript runtime allowing developers to create server-side applications. Read this blog to learn how to uninstall Node JS Ubuntu. Click here!

How to Uninstall Node Js in Ubuntu.webp

Web Development

How to Uninstall Node JS in Ubuntu? (Step by Step Guide)

Artificial Intelligence, or AI, is a multidisciplinary field that encompasses several domains, each with its unique characteristics and applications. [Applications of AI](https://www.almabetter.com/bytes/articles/applications-of-artificial-intelligence) are rapidly expanding across various sectors, transforming industries, enhancing efficiency, and improving the quality of life. These domains of AI are instrumental in shaping the way we interact with technology, from [AI stocks in India](https://www.almabetter.com/bytes/articles/ai-stocks-in-india) to applications in Artificial Intelligence in Psychology and [Artificial Intelligence Engineering](https://www.almabetter.com/bytes/articles/artificial-intelligence-engineering). To gain a comprehensive understanding of AI, it's essential to answer the question, "What are the three domains of AI?" In this comprehensive guide, we will explore the three primary domains of AI and delve into their subcategories, advantages, applications, and techniques. So, let's embark on this journey through the exciting world of AI!

## Understanding the Concept of Domains of AI

The term "Domains of AI" refers to the various specialized areas within artificial intelligence. These Artificial Intelligence domains deal with specific problems, techniques, and applications, making it easier to categorize and understand the vast field of AI. The 3 domains of AI, namely Narrow AI, General AI, and Artificial Superintelligence, each represent distinct levels of artificial intelligence capabilities, from specialized task performance to the potential of human-level cognition and beyond.

### 1\. Narrow or Weak AI

Narrow AI, also known as Weak AI, is the domain of artificial intelligence that specializes in performing specific tasks or solving particular problems. In this domain, AI systems are designed and trained for a well-defined and limited range of activities. These systems are not capable of generalizing their knowledge to perform tasks beyond their predefined scope.

For example, virtual personal assistants like Siri or Alexa fall under the category of Narrow AI. These AI systems are excellent at understanding and responding to voice commands, setting reminders, or providing weather updates. However, they lack the ability to engage in a general conversation or perform tasks that require a broader understanding of the world.

### 2\. General AI

General AI, also referred to as Strong AI or Artificial General Intelligence (AGI), represents the domain of AI that aims to replicate human-level intelligence and cognitive abilities in machines. AGI systems possess the capability to understand, learn, and adapt to a wide range of tasks and situations, similar to a human being.

While General AI is a long-term aspiration in the field of AI, we have not yet achieved it. Most of the AI systems in use today, including the most advanced ones, are still considered Narrow AI. Achieving General AI remains a significant challenge due to the complexity of human cognition and the need for machines to possess common sense, intuition, and a deeper understanding of the world.

### 3\. Artificial Superintelligence

Artificial Superintelligence (ASI) is the concept of AI systems that surpass human intelligence in every aspect. ASI is an advanced theoretical domain that envisions AI entities with the potential to outperform humans in virtually every intellectual task. These entities would possess superhuman cognitive abilities and problem-solving skills.

It's important to note that ASI is largely a futuristic and speculative domain, and we have not yet come close to developing such superintelligent AI systems. The idea of ASI raises important ethical and existential questions, as the emergence of superintelligent AI could have profound implications for humanity.

## Domains of Artificial Intelligence

Now that we have gone through “what are the domains of AI”, let's take a closer look at the key aspects of these:

### 1\. Machine Learning

[Machine Learning](https://www.almabetter.com/bytes/tutorials/data-science/introduction-to-machine-learning) is a pivotal domain within AI, characterized by its ability to enable computers to learn and make decisions based on data without explicit programming. This domain can be further divided into various subdomains and techniques.

#### What is Machine Learning?

Machine Learning is the process by which computers improve their performance on a specific task by learning from data. Unlike traditional programming, where rules are explicitly provided, machine learning systems develop rules and patterns from the data they receive.

#### How does Machine Learning work?

Machine Learning operates on a simple premise: providing the system with data and allowing it to learn patterns from that data. The system then uses these patterns to make predictions, classify information, or automate decisions.

#### Why is Machine Learning important?

Machine Learning's importance stems from its ability to handle complex and large datasets, automate tasks, and make predictions, which has far-reaching applications in industries such as healthcare, finance, and more.

#### Advantages of Machine Learning:

*   Efficient decision-making based on data.
*   Automation of repetitive tasks.
*   Improved accuracy and precision.
*   Scalability to handle large datasets and complex problems.

#### Applications of Machine Learning:

Machine Learning has a broad range of applications, including:

*   Predictive Analytics
*   Recommendation Systems
*   Fraud Detection
*   Autonomous Vehicles
*   Speech Recognition

#### Machine Learning Techniques:

Within Machine Learning, various techniques are employed, such as:

*   [Supervised Learning](https://www.almabetter.com/bytes/tutorials/data-science/supervised-learning)
*   [Unsupervised Learning](https://www.almabetter.com/bytes/tutorials/data-science/unsupervised-learning)
*   [Reinforcement Learning](https://www.almabetter.com/bytes/articles/reinforcement-learning)

### 2\. Deep Learning

Deep Learning is a subset of Machine Learning that focuses on the use of artificial neural networks to model and solve complex problems. It has gained immense popularity due to its ability to handle unstructured data and achieve state-of-the-art results in various applications.

#### What is Deep Learning?

Deep Learning involves neural networks with multiple layers (deep neural networks) that can automatically learn to extract features from data, making it suitable for tasks like image and speech recognition.

#### Why is Deep Learning important?

Deep Learning's importance lies in its remarkable performance on tasks involving unstructured data, such as images, text, and audio. It has revolutionized fields like computer vision and natural language processing.

#### Advantages of Deep Learning:

*   Exceptional performance in tasks like image and speech recognition.
*   Feature extraction from raw data.
*   Reduced manual feature engineering.

#### Applications of Deep Learning:

*   Deep Learning is widely applied in:
*   Image Classification
*   Natural Language Understanding
*   Autonomous Vehicles
*   Healthcare Diagnostics
*   Gaming and Robotics

#### Deep Learning Techniques:

Deep Learning encompasses techniques like:

*   [Convolutional Neural Networks](https://www.almabetter.com/bytes/articles/convolutional-neural-networks) (CNNs)
*   [Recurrent Neural Networks](https://www.almabetter.com/bytes/articles/recurrent-neural-network) (RNNs)
*   [Generative Adversarial Networks](https://www.almabetter.com/bytes/articles/generative-adversarial-networks-GANs-connects-imagination-to-reality) (GANs)

### 3\. Natural Language Processing

[Natural Language Processing](https://www.almabetter.com/bytes/articles/basics-of-natural-language-processing) (NLP) is a domain that focuses on enabling machines to understand, interpret, and generate human language. It plays a crucial role in applications such as chatbots, language translation, and sentiment analysis.

#### What is Natural Language Processing?

NLP involves the interaction between computers and human language. It encompasses tasks like language understanding, language generation, and language translation.

#### Why is Natural Language Processing important?

NLP's significance lies in its ability to bridge the communication gap between humans and machines. It enables chatbots to understand and respond to user queries, automates language translation, and extracts insights from text data.

#### Advantages of Natural Language Processing:

*   Improved human-machine interaction.
*   Automation of language-related tasks.
*   Insights from text data.
*   Multilingual support.

#### Applications of Natural Language Processing:

NLP is used in various applications, including:

*   Chatbots and Virtual Assistants
*   Sentiment Analysis
*   Language Translation
*   Information Extraction
*   Text Summarization

#### Natural Language Processing Techniques:

NLP employs techniques like:

*   Tokenization
*   Part-of-Speech Tagging
*   Named Entity Recognition
*   Word Embeddings (Word2Vec, GloVe)

### 4\. Computer Vision

[Computer Vision](https://www.almabetter.com/bytes/articles/what-is-computer-vision) is a subdomain of AI that deals with enabling machines to interpret and understand visual information from the world. It has applications in image analysis, facial recognition, and even autonomous vehicles.

#### What is Computer Vision?

Computer Vision enables machines to process and interpret visual data. It involves tasks like object detection, image classification, and video analysis.

#### Why is Computer Vision important?

Computer Vision's importance lies in its ability to enable machines to "see" and interpret their surroundings. This has far-reaching applications in fields like healthcare, transportation, and security.

#### Advantages of Computer Vision:

*   Object recognition and classification.
*   Automation of visual inspection.
*   Enhanced safety and security.

#### Applications of Computer Vision:

Computer Vision is used in various applications, including:

*   Facial Recognition
*   Autonomous Vehicles
*   Medical Image Analysis
*   Quality Control in Manufacturing
*   Augmented Reality

#### Computer Vision Techniques:

Computer Vision techniques include:

*   Image Segmentation
*   Feature Extraction
*   Convolutional Neural Networks (CNNs)
*   Object Tracking

### 5\. Data Science

[Data Science](https://www.almabetter.com/bytes/articles/what-is-data-science) is not limited to AI, but it plays a vital role in the AI landscape. It involves the collection, analysis, and interpretation of data to make informed decisions.

#### What is Data Science?

Data Science is an interdisciplinary field that combines techniques from statistics, computer science, and domain expertise to extract valuable insights from data.

#### Why is Data Science important?

Data Science is crucial for AI because it provides the data required for training and testing AI models. It helps organizations make data-driven decisions and predictions.

#### Advantages of Data Science:

*   Informed decision-making.
*   Predictive analytics.
*   Improved business operations.

#### Applications of Data Science:

Data Science has applications in various domains of artificial intelligence, such as:

*   Healthcare Analytics
*   Fraud Detection
*   Customer Segmentation
*   Financial Forecasting
*   Recommender Systems

#### Data Science Techniques:

Data Science employs techniques like:

*   Data Cleaning and Preprocessing
*   Statistical Analysis
*   Machine Learning
*   Data Visualization
*   AI Domains in Action

Now that we have explored the primary domains of AI and their subcategories, let's take a look at how AI is making a significant impact in real-world applications.

[Artificial Intelligence in Psychology](https://www.almabetter.com/bytes/articles/artificial-intelligence-in-psychology) is an emerging field that combines the principles of psychology and AI to enhance mental health services, diagnosis, and therapy. This domain leverages [AI techniques](https://www.almabetter.com/bytes/articles/ai-techniques) to support psychologists and therapists in their work.

AI Engineering bridges the gap between AI research and its practical application in engineering projects. It holds the potential to transform industries and improve the quality of life.

## The Advantages of AI

The domains of AI discussed above offer numerous advantages across various sectors. Here's a recap of the key [advantages of AI](https://www.almabetter.com/bytes/articles/advantages-and-disadvantages-of-artificial-intelligence):

**Efficiency:** AI systems excel at specific tasks, improving efficiency and accuracy.

**Cost Savings:** Automation of tasks through AI can lead to significant cost reductions in industries like manufacturing and customer service.

**Scalability:** AI applications can be easily scaled to handle large volumes of data and tasks.

**Rapid Progress:** Advances in AI have led to significant breakthroughs in various industries, from healthcare to finance.

**Innovation:** AI encourages the development of new products and services, leading to increased innovation in multiple domains.

**Data-Driven Decision-Making:** AI enables organizations to make informed decisions by analyzing vast amounts of data.

**Automation:** AI automates repetitive tasks, freeing up human resources for more creative and strategic roles.

## Conclusion

Artificial Intelligence has emerged as a transformative force, touching every aspect of our lives, from the financial market with AI stocks in India to the realm of psychology and engineering. Understanding the question "What are the domains of artificial intelligence?" is the first step in unraveling the diverse landscape of AI applications and techniques. The domains of AI, including Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, and Data Science, are at the forefront of this technological revolution. As AI continues to evolve, it is important to harness its advantages while being mindful of ethical considerations. The future of AI is filled with promise, and its impact on society will only grow in the years to come.

Explore the diverse and far-reaching domains of AI from Machine Learning, to Natural Language Processing. Discover how AI is reshaping technology in this blog!

Domains of AI (Artificial Intelligence).webp

Exploring The Major Domains of AI (Artificial Intelligence)

Crack your next HTML interview! Explore the top 100 HTML5 and HTML questions and answers for 2024. From basics to advanced tips, ace your interview with confidence!

Advantages and Disadvantages of MS Excel.webp

What are the Advantages and Disadvantages of MS Excel

Merge sort is one of the most efficient sorting algorithms available, widely used due to its reliable performance and time complexity characteristics. Understanding the time complexity of merge sort helps in analyzing its efficiency compared to other sorting algorithms like quicksort or bubble sort. In this article, we will delve into the time complexity of Merge Sort, breaking it down step-by-step to understand how it operates and why it is considered efficient.

## Introduction to Merge Sort

Merge sort is a comparison-based sorting algorithm that follows the divide-and-conquer paradigm. Developed by John von Neumann in 1945, merge sort works by recursively dividing the unsorted list into smaller sublists until each sublist contains a single element. Then, it merges these sublists to produce a sorted list. This process is repeated recursively until the entire array is sorted. Merge Sort has an average and worst-case time complexity of O(n log n), making it a reliable choice for sorting large datasets. This systematic approach ensures that merge sort is both stable and has predictable performance characteristics.

## The Divide-and-Conquer Approach

### Dividing the Array

The first step in Merge Sort is dividing the array into two roughly equal halves. This division continues recursively until each sub-array contains a single element. The division process itself takes O(log n) time because each level of recursion halves the size of the array.

### Sorting and Merging

Once the array is divided into individual elements, the merging process begins. During merging, two sorted sub-arrays are combined into a single sorted array. This process involves comparing elements from each sub-array and placing the smaller element into the final sorted array. The merging process for each pair of sub-arrays takes linear time, O(n).

![The Merge Sort Process](https://almablog-media.s3.ap-south-1.amazonaws.com/merge_sort_process_67582544b0.png)

The Merge Sort Process

## Merge Sort Algorithm Time Complexity

In Merge Sort, the best, average, and worst-case time complexities are all O(n log n). This consistency is due to the algorithm always dividing the array into two halves and merging them, regardless of the initial order of elements.

### Best Case Time Complexity of Merge Sort

The best case for merge sort occurs when the array is already sorted. However, unlike other algorithms such as quicksort, merge sort’s time complexity does not improve with a sorted array because it still needs to divide and merge the array completely.

#### Best Case Time Complexity:

T(n)=O(nlogn)

Despite the array being sorted, merge sort still performs the division and merging steps, which means the best case time complexity remains O(nlogn).

### What is the Average Case Time Complexity of Merge Sort

The average case time complexity of merge sort reflects its performance for a random array. Since merge sort consistently divides the array and processes each element in a systematic manner, the average case is similar to the best case.

#### Average Case Time Complexity:

T(n)=O(nlogn)

This makes merge sort a reliable option for sorting, as its performance does not degrade significantly with different input data patterns.

### Worst Case Time Complexity of Merge Sort

The worst case for merge sort occurs when the array is in reverse order or any other disordered state. Even in these scenarios, merge sort maintains its efficiency because it follows the same divide-and-conquer steps.

#### Worst Case Time Complexity:

T(n)=O(nlogn)

Since merge sort consistently splits and merges subarrays, its worst-case time complexity is also O(nlogn), making it a robust choice for sorting large datasets.

## Analyzing the Time Complexity of Merge Sort

To understand why merge sort has a time complexity of O(n log n), we need to look at the recurrence relation that defines its behavior:

T(n) = 2T(n/2) + O(n)

This relation represents the two recursive calls on subarrays of size n/2 and the linear time O(n) needed to merge the sorted subarrays.

Using the master theorem for divide-and-conquer recurrences:

T(n) = aT(n/b) + f(n)

where a = 2, b = 2, and f(n) = O(n)

Here, log\_b a = log\_2 2 = 1, and since f(n) = O(n), it fits the case f(n) = O(n log\_b a ⋅ log^k n) for k = 0.

Therefore, by the master theorem:

T(n) = O(n log n)

This confirms that the time complexity of merge sort, in the best, average, and worst cases, is O(n log n).

## Space Complexity of Merge Sort

In addition to time complexity, understanding the space complexity of merge sort is crucial. Merge Sort requires additional space proportional to the size of the array being sorted, leading to a space complexity of O(n). This is because it uses a temporary array to hold elements during the merge process.

**Space Complexity:**

S(n) = O(n)

## Comparison with Other Sorting Algorithms

### Quick Sort

Quick Sort, another popular sorting algorithm, has an average-case time complexity of O(n log n) but can degrade to O(n^2) in the worst case. Unlike Merge Sort, Quick Sort is an in-place sorting algorithm, which means it requires less additional space.

### Bubble Sort and Insertion Sort

Both Bubble Sort and Insertion Sort have an average and worst-case time complexity of O(n^2), making them less efficient than Merge Sort for large datasets. These algorithms are generally more suitable for small or nearly sorted arrays.

### Heap Sort

Heap Sort also has a time complexity of O(n log n) but differs in that it uses a binary heap data structure to sort elements. While it is in-place like Quick Sort, it is not a stable sort, meaning the relative order of equal elements may not be preserved.

## Practical Applications of Merge Sort

Merge Sort is particularly useful in scenarios where stability is important, such as:

### Sorting Linked Lists

*   Linked lists benefit from Merge Sort's non-reliance on random access, making it more efficient than Quick Sort for this data structure.

### External Sorting

*   When sorting large datasets that do not fit into memory, Merge Sort is used in external sorting algorithms because it can handle large amounts of data by dividing it into manageable chunks.

## Code Implementation

Here's a simple implementation of Merge Sort in Python:

```python
def merge_sort(arr):
 if len(arr) > 1:
 mid = len(arr) // 2
 L = arr[:mid]
 R = arr[mid:]

 merge_sort(L)
 merge_sort(R)

 i = j = k = 0

 while i < len(L) and j < len(R):
 if L[i] < R[j]:
 arr[k] = L[i]
 i += 1
 else:
 arr[k] = R[j]
 j += 1
 k += 1

 while i < len(L):
 arr[k] = L[i]
 i += 1
 k += 1

 while j < len(R):
 arr[k] = R[j]
 j += 1
 k += 1

# Example usage
arr = [12, 11, 13, 5, 6, 7]
merge_sort(arr)
print("Sorted array is:", arr)
```

## Conclusion

Merge Sort is a highly efficient and stable sorting algorithm with a consistent time complexity of O(n log n). Its divide-and-conquer approach and its reliable performance across best, average, and worst-case scenarios make it a preferred choice for sorting large datasets. While it requires additional space, its stability and efficiency often outweigh this drawback, especially in applications like sorting linked lists and external sorting. By understanding the time complexity and practical applications of Merge Sort, developers can make informed decisions about when to use this algorithm for optimal performance.

If you found this article helpful and are eager to delve further into algorithms and data structures, explore our in-depth courses: [Data Science Training](https://www.almabetter.com/courses/full-stack-data-science), [Web Development Course](https://www.almabetter.com/courses/full-stack-web-development), and [Masters in Data Science](https://www.almabetter.com/degrees/masters-in-computer-science-data-science-ai). Boost your skills and master the latest technologies and methodologies in data science and web development.

Learn about the merge sort time complexity, an efficient sorting algorithm. Discover its best, average, and worst-case scenarios and practical applications

What is the __Time Complexity of Merge Sort.webp

What is the Time Complexity of Merge Sort Algorithm?

The "Hello, World!" program is a simple script that displays the text "Hello, World!" on the screen. It is often the first program written by beginners when they start learning a new programming language. Writing this program in Python is straightforward, thanks to its intuitive syntax. In this article, we will explore how to create a "Hello, World!" program in Python, discuss various ways to print "Hello, World!" using functions, and share multiple examples to understand how Python handles this basic task.

## Why Start with "Hello, World!"?

The "Hello, World!" program is a starting point for learning any programming language because it:

*   Introduces the basic syntax of the language.
*   Demonstrates how to print text to the screen.
*   Serves as a quick way to confirm that your Python environment is set up correctly.

Let's dive into the Python "Hello, World!" program and see how simple it can be to write your first piece of code.

## Writing a Basic Hello World Program in Python

The simplest way to write a "Hello, World!" program in Python is by using the print() function. Here's how:

**Code Example**

```plaintext
print("Hello, World!")
```

**Explanation**

In this example:

*   print() is a built-in function in Python used to output text to the screen.
*   The text "Hello, World!" is enclosed within double quotes, indicating that it is a string.
*   When you run this code, Python displays the output: Hello, World!.

This is how easy it is to write the most basic Python program.

## How to Print Hello World in Python Using Function

We can also print "Hello, World!" using a custom function. Functions allow us to create blocks of code that can be reused multiple times throughout a program. Here's an example of a function that prints "Hello, World!".

**Code Example**

```plaintext
def hello_world():
    print("Hello, World!")

hello_world()
```

**Explanation**

In this example:

1.  We define a function named hello\_world using the def keyword.
2.  Inside the function, we use the print() statement to output "Hello, World!".
3.  We call the hello\_world() function, which executes the code inside the function and prints the text.

## Different Ways to Print Hello World in Python

### Using Single Quotes

Python allows you to use single quotes to represent strings. Here's an example:

```plaintext
print('Hello, World!')
```

### Using Triple Quotes

Triple quotes can be used to span a string across multiple lines or for multi-line comments, but they can also be used to print a simple string:

```plaintext
print("""Hello, World!""")
```

### Using f-Strings

Introduced in Python 3.6, f-Strings provide a way to format strings in a concise and readable manner. Here's how you can use them to print "Hello, World!":

```plaintext
message = "Hello, World!"
print(f"{message}")
```

### Using String Concatenation

You can concatenate strings using the + operator:

```plaintext
print("Hello, " + "World!")
```

### Using Variables

You can store "Hello, World!" in a variable and then print it:

```plaintext
greeting = "Hello, World!"
print(greeting)
```

### Using a Loop

You can use a loop to print "Hello, World!" multiple times:

```plaintext
for _ in range(3):
    print("Hello, World!")
```

This code prints "Hello, World!" three times.

## Hello World Python Code Examples

Below are several other examples of "Hello, World!" programs to demonstrate how to print "Hello, World!" using different techniques.

### Hello World Program Using with Conditional Statements

Adding conditions allows the program to make decisions before printing "Hello World".

```plaintext
is_hello = True
if is_hello:
    print("Hello, World!")
else:
    print("Goodbye, World!")
```

### Hello World with User Input

You can also prompt the user to enter a greeting and then display it:

```plaintext
user_greeting = input("Enter your greeting: ")
print(user_greeting)
```

### Hello World Using a Class

Python supports object-oriented programming. Here's how you can use a class to print "Hello, World!":

```plaintext
class HelloWorld:
    def display_message(self):
        print("Hello, World!")

hw = HelloWorld()
hw.display_message()
```

### Hello World with Exception Handling

You can use exception handling to ensure your code runs smoothly, even in unexpected scenarios:

```plaintext
try:
    print("Hello, World!")
except Exception as e:
    print(f"An error occurred: {e}")
```

### Hello World in Python Using Lambda Function

You can use a lambda function to print "Hello, World!" in one line:

```plaintext
(lambda: print("Hello, World!"))()
```

## How to Run Hello World Python Program

To run your Python "Hello, World!" program:

1.  **Using an IDE**: Open an Integrated Development Environment (IDE) like PyCharm, VS Code, or Thonny. Create a new Python file, write your code, and press the Run button.
2.  **Using the Terminal**: Save your code in a file with a .py extension, for example, hello\_world.py. Open the terminal and type:  
    Copy code  
    python hello\_world.py
3.  **Using an Online Interpreter**: Visit an [online Python compiler](https://www.almabetter.com/online-compiler/python), paste your code into the editor, and run it to see the output.

## Common Errors in a Python Hello World Program

While writing a simple program like "Hello, World!", beginners may encounter a few common errors:

**1\. Syntax Error**: Forgetting the parentheses around print in Python 3.

*   Incorrect: print "Hello, World!"
*   Correct: print("Hello, World!")

**2.** Python 2 allowed print without parentheses, but in Python 3, parentheses are required.

**3\. Indentation Errors**: Python relies on indentation (spaces or tabs) to define code blocks. If you define a function but don't indent the print() statement inside the function, Python will raise an error:

```plaintext
def greet():
print("Hello, World!")  # This line should be indented.
```

## Why Python for "Hello, World!"?

Python is popular among beginners due to its readability and simplicity. It has a clean syntax that closely resembles the English language, making it easier to learn compared to other programming languages. Writing a "Hello, World!" program in Python only requires a single line of code, demonstrating how Python eliminates unnecessary complexity.

_Recommended Articles for Further Reading_

*   [_Variables in Python_](https://www.almabetter.com/bytes/tutorials/python/variables-in-python)
*   [_Exception Handling in Python_](https://www.almabetter.com/bytes/tutorials/python/exception-handling)
*   [_Indentation in Python_](https://www.almabetter.com/bytes/tutorials/python/indentation-in-python)
*   [_Factorial Program in Python_](https://www.almabetter.com/bytes/articles/factorial-program-in-python)
*   [_Armstrong Number in Python_](https://www.almabetter.com/bytes/articles/armstrong-number-in-python)
*   [_Leap Year Program in Python_](https://www.almabetter.com/bytes/articles/leap-year-program-in-python)
*   [_While Loop in Python_](https://www.almabetter.com/bytes/tutorials/python/while-loop-in-python)
*   [_For Loop in Python_](https://www.almabetter.com/bytes/tutorials/python/for-loop-in-python)

## Conclusion

Printing "Hello, World!" in Python is a great way to start learning the language. It provides a basic understanding of syntax, functions, and printing to the console. Whether you're a beginner or an experienced programmer, this simple program lays the foundation for writing more complex applications in Python. By exploring the various ways to print "Hello, World!", you get a glimpse of Python's flexibility and powerful features.

Learn how to print Hello World in Python with this guide. Learn code examples, functions, variables, and tips to effectively print Hello World in Python

Hello World in Python.webp

How to Print Hello World in Python

Some experts even believe that it has the potential to replace Google’s algorithm in terms of understanding human language. With the advancements in machine learning, ChatGPT has become increasingly sophisticated and can answer a wide range of questions with a high level of accuracy.

In this blog, we will discuss Chat GPT vs Google and compare whether ChatGPT is better than Google.

## ChatGPT vs Google: How Their Algorithm Works?

ChatGPT and Google are two advanced technologies that have gained much attention in recent times for their ability to understand and respond to natural language. While both ChatGPT and Google have their own unique capabilities, they are used for different purposes. ChatGPT is a sophisticated AI chatbot that is capable of understanding and responding to natural language, while Google is a powerful search engine that is used for finding specific information on the Internet.

In this section of Chat GPT vs Google, we will take a closer look at how the algorithms of ChatGPT and Google work, and how they differ from each other. We will explore the key features and technologies that drive these two powerful language models, and how they are used to understand and respond to natural language. This will provide a deeper understanding of the capabilities and limitations of both ChatGPT and Google, and help to determine which technology is better suited for specific tasks and applications.

## ChatGPT’s Uses

ChatGPT is a powerful language model that uses advanced [Artificial Intelligence](https://www.almabetter.com/bytes/articles/what-is-artificial-intelligence) and [Machine Learning algorithms](https://www.almabetter.com/bytes/articles/top-machine-learning-algorithms), specifically [NLP](https://www.almabetter.com/bytes/articles/introduction-to-nlp) (Natural Language Processing) techniques, to generate human-like responses in a conversational AI setting. The model utilizes large scale pre-training on a massive dataset of text to create a powerful language model. This allows Chat GPT to understand and respond to a wide range of queries, making it a highly sophisticated AI chatbot.

![Open AI ChatGPT](https://almablog-media.s3.ap-south-1.amazonaws.com/OPEN_AI_7ede421685.png)

OpenAI ChatGPT

One of the primary uses of ChatGPT is in natural language understanding and generation tasks. It can answer questions, summarize text, and generate written content with a high level of accuracy. This makes it a valuable tool for businesses and organizations looking to improve their customer service through AI-powered chatbots.

ChatGPT can also be used for other tasks such as text classification, language translation, and sentiment analysis. In these applications, it can analyze and understand the meaning of text, making it a powerful tool for data analysis and insights.

In addition to these uses, ChatGPT can also be used for creative applications such as writing fiction, poetry, and even screenplays. The model’s ability to understand and respond to natural language makes it a valuable tool for writers and content creators looking to generate new ideas and inspiration.

And there are a lot of similar Chat GPT websites that ask us to log in to fake us. Here you can find the original Chat GPT login from [OpenAi](https://chat.openai.com/auth/login?next=/chat)

## Google’s Uses

Google is a search engine that uses a machine learning-based algorithm known as RankBrain to deliver relevant search results to users. The RankBrain algorithm assesses the relationship between keywords and phrases in a user’s query and uses a mathematical formula to rank the search results. This allows Google to deliver the most useful and relevant information to users based on their search queries.

![Google Search Engine](https://almablog-media.s3.ap-south-1.amazonaws.com/search_engine_working_1c255cb476.jpg)

Google Search Engine

Google’s search engine uses a combination of techniques such as crawling, indexing, and ranking to present the most relevant results to users. Crawling refers to the process of discovering new or updated pages on the Internet. Indexing is the process of creating an index of all the words found on the pages and their location. In addition, ranking is the process of determining the relevance and importance of each page in relation to a user’s query.

Google’s machine learning-based algorithm, RankBrain, is constantly learning and adapting to improve the relevance and quality of search results. This means that the algorithm is able to understand the intent behind a user’s query and deliver results that are more relevant and useful. It also allows the algorithm to understand and interpret complex and ambiguous queries, making it easier for users to find the information they need.

| Feature | ChatGPT | Google |
| --- | --- | --- |
| **Up-to-date Information** | Limited to 2021 | Up-to-date |
| **Complete Information** | Can provide complete information, but may not always have the latest information | Comprehensive and up-to-date |
| **Accuracy** | High, but may not always have the most current information | High |
| **Format of Output** | Text-based | Text, voice, and visual |
| **Knowledge Limitation** | Limited to the information it was trained on | No limit |
| **Personalised Results** | No | Yes |
| **Language Processing Capabilities** | Very advanced | Advanced |

As shown in the above ChatGPT vs Google table, ChatGPT is a language model that uses a neural network with transformer architecture and a large dataset of text to generate human-like responses in a conversational AI setting. It is primarily used for natural language understanding and generation tasks such as answering questions, summarizing text, and generating written content.

Google, on the other hand, is a search engine that uses RankBrain to deliver relevant search results to users. It uses a combination of techniques such as crawling, indexing, and ranking to present the most relevant results to users based on their search queries. Google is primarily used for information retrieval and is a powerful tool for finding specific information on the Internet.

_Read our latest article "_[_DeepSeek vs ChatGPT_](https://www.almabetter.com/bytes/articles/deepseek-vs-chatgpt)_"_

## Conclusion

In conclusion of Google vs ChatGPT, ChatGPT is a sophisticated AI chatbot that is capable of understanding and responding to natural language, while Google is a powerful search engine that is used for finding specific information on the Internet. Both technologies are highly advanced and have their own unique capabilities, but they are used for different purposes. To gain a deeper understanding of ChatGPT and harness its capabilities to simplify your tasks, explore our comprehensive [ChatGPT tutorial](https://www.almabetter.com/bytes/tutorials/chatgpt).

If technologies like Artificial Intelligence and Data Science pique your interest, sign up for AlmaBetter’s [Full Stack Data Science course](https://www.almabetter.com/courses/full-stack-data-science) and earn a guaranteed job that pays Rs. 5-25 LPA.

Recently, there has been a lot of buzz on the Internet about ChatGPT, a language model powered by Artificial Intelligence. The model has garnered much attention due to its ability to understand and respond to natural language.

chatgpt-vs-google.png

Google vs ChatGPT: Is Chat GPT Better Than Google?

Frame 1000005439.jpg

Python

An Online Python Compiler is a web-based platform that enables users to write, execute, and test Python code without the need for local installations. It provides a virtual coding environment accessible through a web browser, allowing users to run Python scripts in real-time and receive immediate feedback on their code.

## Why Use an Online Python Compiler?

*   **Accessibility and Convenience:** Python online Compilers / Online Python Editors eliminate the need for local Python installations, making it convenient for users to write and test code from any device with internet access.
*   **Quick Prototyping:** Ideal for rapid prototyping and experimenting with Python code without the overhead of setting up a local development environment.
*   **Collaborative Coding:** Facilitates collaborative coding by allowing multiple users to work on the same Python script simultaneously, fostering efficient teamwork.
*   **Learning and Teaching:** Provides an excellent platform for learning Python or teaching programming concepts, as users can experiment with code examples and receive instant feedback.

## Features of Our Python Online Compiler

*   **Write, Run & Share:** Easily write Python code, execute it in real-time, and share your creations with others.
*   **Python 3 and 2.7 Support:** Our online compiler for Python accommodates both Python 3 and Python 2.7, ensuring flexibility for your coding preferences.

## Effortless Interaction

*   **Python Shell Integration:** Seamlessly interact with Python Shell directly in your browser.
*   **User Inputs:** Take user inputs using the STDIN textbox under the I/O tab for dynamic program execution.
*   **Debugging Made Easy:** Effortlessly debug your code for a smoother coding experience.

## Getting Started

**Sample Code:**

```python
# Sample Python program
print("Hello, World!")
```

**Python Tutorial & Syntax Help:**

Loops: Master If-Else, For, and [While loops](https://www.almabetter.com/bytes/tutorials/python/while-loop-in-python) with clear examples and [indentation](https://www.almabetter.com/bytes/tutorials/python/indentation-in-python) guidance.

```python
# If-Else example
a = 10
b = 5
if a > b:
    print("a is greater")
elif a == b:
    print("a and b are equal")
else:
    print("b is greater")
```

Collections: Explore Python's versatile collections - List, Tuple, Set, and Dictionary - with concise explanations.

```python
# List example
mylist = ["Apple", "Banana", "Cherry"]
print(mylist)

# Tuple example
coordinates = (10, 20, 30)
print(coordinates)

# Dictionary example
person = {"name": "John", "age": 30, "city": "New York"}
print(person)
```

## Supported Libraries

| **Library** | **Details** |
| --- | --- |
| NumPy | A library for working with arrays, simplifying operations and used extensively in numerical computing. |
| SciPy | A scientific computation library that builds on NumPy for efficient N-dimensional array manipulation. |
| Scikit-learn | Essential for machine learning, offering tools for data mining and analysis. |
| Pandas | Specialized in data manipulation and analysis, ideal for data processing and cleaning. |
| Matplotlib | A cross-platform library for data visualization and graphical plotting, complementing NumPy's numerical mathematics. |
| DOcplex | IBM's library for Mathematical Programming Modeling and Constraint Programming Modeling, enhancing decision optimization. |

## Python IDE Overview

*   **Accessible Web-Based Tool:** Code, edit, and execute Python in your browser without local installations.
*   **Real-Time Compilation:** Receive instant feedback on your code with real-time compilation.
*   **Learning Tools:** Benefit from [Python tutorials](https://www.almabetter.com/bytes/tutorials/python) and auto-completion features for an enhanced learning experience.

## Python Syntax Examples

Easily grasp essential syntaxes like If-Else, [For Loop](https://www.almabetter.com/bytes/tutorials/python/for-loop-in-python), While Loop, List, Dictionary, [Tuple and Set](https://www.almabetter.com/bytes/tutorials/python/tuples-and-sets-in-python) with illustrative examples.

### If-Else:

```python
# If-Else example
a = 10
b = 5
if a > b:
    print("a is greater")
elif a == b:
    print("a and b are equal")
else:
    print("b is greater")
```

### For Loop:

```python
# For Loop example
colors = ["Red", "Green", "Blue"]
for color in colors:
    print(color)
```

### While Loop:

```python
# While Loop example
n = 5
while n > 0:
    print(n)
    n -= 1
```

### List:

```python
# List example
fruits = ["Apple", "Banana", "Cherry"]
print(fruits)
```

### Tuple:

```python
# Tuple example
coordinates = (10, 20, 30)
print(coordinates)
```

### Set:

```python
# Set example
unique_numbers = {1, 2, 3, 4, 5}
print(unique_numbers)
```

### Dictionary:

```python
# Dictionary example
person = {"name": "John", "age": 30, "city": "New York"}
print(person)
```

## Python Dictionaries

Understand the importance of [Python dictionaries](https://www.almabetter.com/bytes/tutorials/python/dictionary-in-python) for versatile [data handling](https://www.almabetter.com/bytes/articles/data-handling) and algorithm implementation.

Online Python Compiler (Editor, IDE, Interpreter)

Python is a popular and versatile programming language used for a wide variety of tasks, including web development, data analysis, artificial intelligence, and more.

Python is a powerful, versatile, and high-level programming language. It is one of the most popular programming languages in the world and is used for a wide variety of tasks, including web development, data science, machine learning, artificial intelligence and more.

If you are new to Python, or if you are looking for a comprehensive python tutorial to help you learn python programming, AlamBetter’s advanced Python tutorial is the best platform to learn python. This is the top python tutorial for beginners as it is divided into easy-to-follow lessons, and it covers all the basics of Python programming. 

This Python programming tutorial is your ideal starting point to learn Python online for free. If you want to learn Python from scratch, this will help you understand the language, learn its concepts, and use it to solve your problems.

Here are the modules covered in this Python Tutorial:

- Getting Started with Python Programming Tutorial
- Basics of Python Programming
- Loops and Iterations in Python
- Data Structures in Python
- Comprehensions in Python
- Functions in Python
- OOPs in Python
- Python Libraries and Advanced Concepts


Python Tutorial.png

Getting Started with Python 

Basics of Python Programming

Loops and Iterations in Python

Data Structures in Python

Comprehensions in Python

Functions in Python

OOPs in Python

Python Libraries and Advanced Concepts

Python Tutorial 2024 - Learn Python Online for Free

DS & AI.png

GATE 2024 Data Science and AI

Explore this free tutorial to understand various concepts of GATE  Data Science and AI 2024 . Learn probability, algebra, calculus, etc.

The Graduate Aptitude Test in Engineering (GATE) is a highly competitive examination conducted at the national level in India. It is primarily designed to assess the knowledge and understanding of candidates in various engineering and science subjects. GATE is jointly conducted by the Indian Institute of Science (IISc) and the Indian Institutes of Technology (IITs) on a rotational basis.

To excel in GATE Data Science and AI 2024, candidates can choose a relevant paper based on their educational background and interests. They should thoroughly study the syllabus, practice previous year's questions, and consider pursuing higher studies or research in these fields at institutions that accept GATE scores.


##**Gate 2024 Exam Details:**

1. **Exam Name** - Graduate Aptitude Test in Engineering (GATE) Year 2024
2. **Conducting Body** - IISc Bangalore
3. **Exam Level** - National Level
4. **Eligibility Criteria** - Educational Qualifications, Age Limit (if any), Nationality (if applicable)
5. **Application Period** - August 31st, 2023
6. **Application Process** - Online Registration
7. **Admit Card Release **- January 3rd, 2024
8. **GATE Exam Date** - February 3,4,10, & 11, 2024 (tentative)
9. **Exam Duration** - 3 hours (180 mins)
10. **Exam Mode** - Computer-Based Test (CBT)
11. **Papers Offered **- List of GATE Papers (e.g., ME, EE, CE, etc.)
12. **Exam Centers** - Various cities across India
13. **Result Declaration** - inbetween March 23rd to May 31st, 2024
14. **Score Validity** - 3 years
15. **Application Fee** - All candidates: Rs. 1800 & Late fee Rs. 2300 and Female(SC,ST,PwD): Rs. 900 & Late Fee Rs. 1400
16. **Official Website** - gate2024.iisc.ac.in

DS & AI 1.png

Probability and Statistics

Linear Algebra, Calculus and Optimization

Programming, Data Structures, and Algorithms

Database Management and Warehousing

Machine Learning

Artificial Intelligence

GATE Data Science and AI 2024

React.png

React Fundamentals

An Online JavaScript Compiler is a web-based tool that allows users to write, test, and execute JavaScript code directly in a browser environment. It provides a virtual workspace where developers can experiment with JavaScript without the need for local installations, offering a quick and accessible way to run and debug code.

## Why Use an Online JavaScript Compiler?

**Accessibility and Portability:** Online JavaScript Compilers / JavaScript Online Editors eliminate the need for local setup, enabling users to write and run JavaScript code from any device with internet access. This level of accessibility enhances portability and flexibility in development.

**Rapid Prototyping:** Ideal for rapid prototyping and testing JavaScript code snippets. Developers can quickly iterate and experiment with different functionalities without the need for a comprehensive local development environment.

**Collaborative Development:** Facilitates collaborative coding by allowing multiple developers to work on the same JavaScript code simultaneously. This feature enhances teamwork and supports knowledge sharing among team members.

**Learning and Teaching:** Provides an interactive and user-friendly platform for learning JavaScript or teaching programming concepts. Beginners can experiment with code examples, receive immediate feedback, and enhance their understanding of JavaScript syntax and functionality.

## Key Features of Our Javascript Online Compiler

*   **Open-source:** Our JS compiler is open-source, ensuring transparency and community collaboration in enhancing the platform.
*   **Just-in-time Compiled Language:** JavaScript is a just-in-time compiled language, allowing for efficient execution and dynamic behavior in both browser and server environments.
*   **Embedded with HTML:** JavaScript is seamlessly embedded with HTML, bringing web pages to life by enhancing their interactivity and responsiveness.
*   **Syntax Help:** Benefit from syntax assistance to streamline your coding process and catch errors in real-time.
*   **STDIN Example:** Take advantage of user inputs using the STDIN example, enabling dynamic program execution.

## Effortless Interaction

*   **JavaScript Console Integration:** Interact seamlessly with the JavaScript console directly in your browser for quick debugging and testing.
*   **User Inputs:** Take dynamic user inputs using the STDIN textbox under the I/O tab for interactive program execution.
*   **Debugging Made Easy:** Effortlessly debug your code for a smoother coding experience with real-time error feedback.

## Getting Started

### Sample Code

```javascript
// Sample JavaScript program
console.log("Hello, World!");
```

### Syntax Help

#### **Variable Declaration**

```javascript
// Var, Let, Const examples
var oldWay = "Var (Function or global scope)";
let newWay = "Let (Global or block Scope)";
const constant = "Const (Global or block Scope)";
```

#### **Backtick Strings**

```javascript
// Backtick Strings examples
let name = "John";
let greetings = `Hello ${name}`;
const multiLineMsg = `
Hello
World!
`;
```

#### **Arrays**

```javascript
// Array example
let mobiles = ["iPhone", "Samsung", "Pixel"];
console.log(mobiles[0]);
```

#### **Arrow Functions**

```javascript
// Arrow Functions example
const numbers = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
const squaresOfEvenNumbers = numbers.filter(ele => ele % 2 == 0)
                                    .map(ele => ele ** 2);
console.log(squaresOfEvenNumbers);
```

## Supported Libraries

**jQuery:** A fast, small, and feature-rich [JavaScript library](https://www.almabetter.com/bytes/articles/javascript-libraries) for simplifying HTML document traversal and manipulation.

## JavaScript IDE Overview

*   **Accessible Web-Based Tool:** Code, edit, and execute JavaScript in your browser without local installations.
*   **Real-Time Compilation:** Receive instant feedback on your code with real-time compilation for efficient debugging.
*   **Learning Tools**: Benefit from [JavaScript tutorial](https://www.almabetter.com/bytes/tutorials/javascript) and auto-completion feature for an enhanced learning experience.

## JavaScript Syntax Examples

Easily grasp essential syntaxes like [variable declaration](https://www.almabetter.com/bytes/tutorials/javascript/variables-in-javascript), backtick strings, [arrays](https://www.almabetter.com/bytes/tutorials/javascript/arrays-in-javascript), arrow functions, and more with illustrative examples.

Online JavaScript Compiler (Editor)

Learn React with the best React JS tutorial and master how to build dynamic, user-friendly web applications using the powerful JavaScript library. Start today!

React.js is a dynamic JavaScript library that has revolutionized web development. If you're looking to learn React JS, there are various resources available, whether you're a beginner or an experienced developer. 

AlmaBetter offers a solid foundation for creating reusable UI components in their React js tutorial. The official React documentation is an excellent starting point, covering components and hooks. This React.js tutorial explores both basic and advanced React.js concepts, making it a valuable resource for beginners looking for a React js tutorial for beginners step by step with examples. 

For those who prefer a hands-on approach and searching for “How to learn React Js”, this tutorial is perfect for them. Let’s level up your expertise and kickstart your journey to becoming a React.js pro.

The modules covered in this React JS tutorial are:

1. Introduction to ReactJS
2. ReactJS Fundamentals
3. Working with React Components
4. React Router DOM
5. Advanced React Concepts
6. Redux and State Management
7. Optimizing the application

React Fundamentals.png

Introduction to ReactJS

ReactJS Fundamentals

Working with React Components

React Router DOM

Advanced React Concepts

Redux and State Management

Optimizing the application

React JS Tutorial 2024 - Learn React Online for Free

Docker.png

Docker

Explore Docker from basics to advanced concepts. Learn installation, commands, security, and orchestration. Master practical examples with this Docker tutorial.

Welcome to our Docker tutorial for beginners, a comprehensive guide designed to help you understand and master the essentials of Docker. Whether you're a beginner looking to dip your toes into the world of Docker or an experienced developer seeking to deepen your understanding, this tutorial provides a step-by-step approach to learning Docker effectively.

This tutorial is perfect for those searching for how to learn Docker from scratch, seeking information on how to learn Docker for free, or exploring a Docker basics tutorial. It will take you on a journey to unravel the world of Docker and equip you with the skills to tackle real-world challenges. Let's start learning Docker together, from the basics to advanced concepts. In this Docker tutorial for beginners, you will also explore Docker and Kubernetes tutorial, Docker Compose tutorial, and learn Docker and Kubernetes. Get ready to dive into the fundamentals and advance your knowledge in Docker and container orchestration.

Join us on this educational adventure and dive into the exciting realm of Docker!
The Docker tutorial covers the following modules:

- Module 1: Docker Overview
- Module 2: Working with Docker
- Module 3: Advanced Docker Concepts

Docker Overview

Working with Docker

Docker Tutorial 2024 - Learn Docker Online for Free

Heading.png

Dive into our comprehensive Artificial Intelligence tutorial and master the fundamentals of AI. From an introduction to advanced concepts, learn AI from scratch

Welcome to our Artificial Intelligence tutorial, your go-to resource for learning the essentials of AI. Whether you're a beginner or looking to deepen your understanding, this tutorial provides a step-by-step guide to help you learn Artificial Intelligence effectively. Discover the foundations, algorithms, and concepts that form the backbone of AI.

Whether you're a beginner or an enthusiast eager to learn AI, this tutorial caters to all. Embark on this journey to unravel the world of Artificial Intelligence and acquire the skills to tackle real-world challenges. Let's start learning AI together, from the basics to advanced concepts. 

This comprehensive AI tutorial is perfect for those searching for how to learn AI from scratch, seeking information on how to learn AI for free, or exploring an artificial intelligence tutorial for beginners. Join us on this educational adventure and dive into the exciting realm of Artificial Intelligence!

The modules covered in this AI tutorial are:

Module 1: Introduction to Artificial Intelligence

Module 2: AI Algorithms

Module 3: AI Concepts and Techniques

ArtificiaI-Intelligence-_AI_.webp

Introduction to Artificial Intelligence

AI Algorithms

AI Concepts and Techniques

Artificial Intelligence Tutorial 2024 - Learn AI for Free


card images.png

An Online SQL Compiler, specifically tailored for SQLite 3, is a web-based platform that provides developers with the ability to write, test, and execute SQL queries seamlessly. It offers a virtual environment for interacting with SQLite databases without the need for local installations.

## Why to Use an Online SQL Editor?

**Accessibility:** Eliminate the hassle of setting up a local database environment. Access and work on SQL queries from any location with an internet connection.

**Quick Prototyping:** Perfect for rapid prototyping and testing SQL queries without the need for a dedicated local database setup.

**Collaboration:** Collaborate efficiently with team members by working on SQL scripts simultaneously, promoting seamless teamwork.

## Key Features of our SQL Online Compiler

**Real-Time Execution:** Instantly execute SQL queries and see live results, allowing for quick adjustments and testing.

**Collaborative Coding:** Foster teamwork with real-time collaboration features, enabling seamless sharing and editing of SQL code within the platform.

**Syntax Highlighting and Auto-Completion:** Enhance coding efficiency with syntax highlighting for clarity and auto-completion for faster, error-free SQL development.

**Accessible Anywhere, Anytime:** Enjoy the flexibility of working on SQL projects from any location with internet access, eliminating the need for local installations.

## Effortless Interaction

**Integrated SQL Shell:** Seamlessly interact with the SQL Shell directly in the browser, simplifying the execution of queries and commands.

**User Inputs for Dynamic Execution:** Easily take user inputs using the STDIN textbox under the I/O tab, enhancing the flexibility of program execution.

**Debugging Made Easy:** Effortlessly identify and troubleshoot errors with built-in error highlighting and debugging features, ensuring a smoother coding experience.

**Efficient Learning Tools:** Access the [SQL tutorial](https://www.almabetter.com/bytes/tutorials/sql) and auto-completion feature within the compiler for an enhanced learning experience, making interaction with SQL more intuitive.

## Getting Started

### Sample Code

```plaintext
-- Sample SQL query
SELECT * FROM employees WHERE department = 'IT';
```

### Syntax Help

#### Create

The CREATE command is used to define and create a new table in the database.

```plaintext
CREATE TABLE table_name (
    column1 datatype,
    column2 datatype,
    ...
);
```

Example:

```plaintext
CREATE TABLE users (
    id INT AUTO_INCREMENT,
    username VARCHAR(50),
    password VARCHAR(50),
    PRIMARY KEY (id)
);
```

Explanation:

*   id is an integer column set to auto-increment with each new record, commonly used as the primary key.
*   username and password are variable character columns capable of holding strings up to 50 characters in length.
*   PRIMARY KEY (id) designates id as the [primary key](https://www.almabetter.com/bytes/tutorials/sql/primary-key-in-sql) of the table.

#### Alter

The [ALTER command](https://www.almabetter.com/bytes/tutorials/sql/alter-table-in-sql) allows the addition of a new column to an existing table.

```plaintext
ALTER TABLE table_name
ADD column_name datatype;
```

Example:

```plaintext
ALTER TABLE users
ADD email VARCHAR(100);
```

#### Truncate

The TRUNCATE command deletes all rows from a table without logging individual row deletions.

```plaintext
TRUNCATE TABLE table_name;
```

Example:

```plaintext
TRUNCATE TABLE users;
```

#### Drop

The DROP command removes a table, including all its rows, from the database.

```plaintext
DROP TABLE table_name;
```

Example:

```plaintext
DROP TABLE users;
```

#### Rename

The RENAME command changes the name of an existing table.

```plaintext
RENAME TABLE old_table_name TO new_table_name;
```

Example:

```plaintext
RENAME TABLE users TO customers;
```

## SQL IDE Overview

**Accessible Web-Based Tool:** Code, edit, and execute SQL queries in your browser without the need for local installations.

**Real-Time Compilation:** Receive instant feedback on your SQL code with real-time compilation, improving the development workflow.

**Learning Tools:** Access SQL tutorials and benefit from auto-completion features for an enhanced learning experience.

Online SQL Compiler (SQLite 3 Editor)

The SQL for Beginners Tutorial is a concise and easy-to-follow guide designed for individuals new to Structured Query Language (SQL). It covers the fundamentals of SQL, a powerful programming language used for managing relational databases. The tutorial introduces key concepts such as creating, retrieving, updating, and deleting data in a database using SQL queries.

SQL is a standard language for storing, manipulating, and retrieving data in databases. This SQL tutorial is a concise and easy-to-follow guide designed for individuals new to Structured Query Language (SQL). It covers the fundamentals of SQL, a powerful programming language used for managing relational databases. This online SQL tutorial introduces key concepts such as creating, retrieving, updating, and deleting data in a database using SQL queries.

If you are struggling to find how to learn SQL with no experience. AlmaBetter’s SQL tutorial for beginners provides a step-by-step journey through SQL concepts, from the fundamentals to advanced topics. Here you will learn SQL online from scratch. You'll learn how to create, retrieve, update, and manage data in relational databases. With practical examples and clear explanations, you'll gain the knowledge and confidence needed to work with SQL in real-world scenarios. Let's dive in and unlock the power of SQL together.

The Modules covered in our SQL Tutorials:

- Getting started with SQL
- Creating and Managing Databases in Postgres
- DDL Commands in SQL
- DML Commands in SQL
- Clauses in SQL
- Filtering in SQL
- JOINS in SQL
- SQL Advanced Topics