Python Online Training with Placement

To lay the bedrock of Python, let’s understand its core. In its very essence, Python is an object-oriented, high-level programming language with simple syntax suitable for desktop, web, and business applications.

Whether you are pursuing a career in data science or web development or work in AI or finance, Python is one of the most crucial skills you can learn. Its design philosophy focuses on readability and usability, the core programming language is quite small, and the standard library is enormous.

From automating tasks on your computer to programmatically generating and updating Excel spreadsheets, our Python training covers everything! Opt for our Python online course and write seamless programs that can do more than text pattern recognition with “regular expressions”.

In fact, Python’s massive library is one of its exquisite advantages as it offers different tools for programmers for performing different tasks with a few lines of code.

What Does the Object-Oriented Nature of Python Mean?
Python supports many programming approaches, which makes it a multi-paradigm language.

Along with its functional and procedural programming styles, the coding language also supports the object-oriented style of programming, where a developer can complete an entire programming project by curating Python objects in the code representing objects in the real world.

These objects contain both the functionality and data of the actual-world object, and this gives a realistic edge to the application, program, or game created using Python. 

Difference between Python and R
Most people confuse Python with R because they are two of the most popular programming languages. However, they are drastically different.

Python is a versatile language renowned for its general-purpose applications, including web development, automation, and machine learning. Its syntax is user-friendly, making it accessible to beginners.

Python's extensive libraries, like Pandas and NumPy, empower data manipulation and analysis.

On the other hand, R programming is customized for statistical analysis and data visualization. It boasts a wide range of specialized packages for statistical modeling and graphical representation, making it a favorite among statisticians and researchers.

R's syntax focuses on statistical concepts, which can be advantageous in an analytical context.

Why Python?
Globally developers love Python for its simplicity. Whether you are a complete beginner or a seasoned coder, Python can offer a seamless learning curve.

Python is one of the most powerful programming languages, as of now, and like its peers JavaScript, Java, and Ruby, Python skills can translate to some lucrative career paths.

You can use Python in Machine Learning, and AI, and the programming language is relatively straightforward and structured to learn.

In fact, imagine knowing a programming language that can write code everywhere from Uber ETAs to Netflix suggesting what shows you will enjoy, and Google finishing your sentences. Isn’t that amazing?

Python has a super cool best friend: data science. Those who learn Python can understand data science capabilities and handle vast datasets for tackling big business dilemmas.

Python is also known as the 'Swiss Army Knife' of coding, as it can work effortlessly on platforms like Linux, MacOS, and Windows. It has a profound presence in the future of tech, which is why it is growing in the job market, and Python dives into deep learning as well.

Do you need any more reasons to select the best Python course ? 

Tools and Techniques You can learn with our Python training online

• Python 3: The latest version ensures access to the language's newest features, enhancements, and security updates.
• Python Scripting and Automation: This enables automating repetitive tasks and creating efficient workflows.
• Python Game Development: Empowers the creation of interactive and entertaining games using Python's libraries and frameworks.
• Python GUI Desktop App Development: Allows building user-friendly desktop applications with graphical interfaces.
• Web Scraping: Facilitates the extraction of data from websites, enabling information gathering and analysis.
• Beautiful Soup: A Python library for parsing HTML and XML documents, streamlining web scraping tasks.
• Selenium Web Driver: Automates web browser interactions, crucial for testing and data extraction.
• Request: Simplifies HTTP requests, aiding in web scraping and API interactions.
• WTForms: Eases the creation of web forms in applications, enhancing user interaction.
• Data Science: Involves collecting, analyzing, and interpreting data to make informed decisions.
• Pandas: A powerful library for data manipulation and analysis, vital for data science tasks.
• NumPy: Provides support for arrays and mathematical functions, foundational for numerical computations.
• Matplotlib: Essential for creating various graphs and visualizations in data analysis.
• Plotly: Enables interactive and dynamic data visualizations, enhancing insights presentation.
• Scikit-learn: Offers tools for machine learning tasks, from classification to regression.
• Seaborn: A statistical data visualization library that simplifies the creation of informative plots.
• Turtle: A graphics library used for introducing programming to beginners through artistic creation.
• Front-End Web Development: Involves creating the visual elements of a website.
• HTML 5: The latest version of Hypertext Markup Language, used to structure web content.
• CSS 3: Cascading Style Sheets define the visual appearance of HTML elements.
• Bootstrap 4: A front-end framework that simplifies responsive web design and layout.
• Bash Command Line: A powerful interface for interacting with a computer's operating system.
• Git, GitHub, and Version Control: These are essential tools for tracking and collaborating on code changes.
• Backend Web Development: Focuses on the server-side logic and databases of web applications.
• Flask: A micro web framework for building scalable and maintainable web applications.
• REST: Representational State Transfer defines guidelines for creating APIs in web development.
• APIs: Application Programming Interfaces enable communication between different software systems.
• SQL: Structured Query Language is used for managing and querying relational databases.
• SQLite: It is a lightweight, embedded database system ideal for small-scale applications.
• PostgreSQL: A powerful, open-source relational database management system.
• Authentication: Ensures secure access to applications and data by verifying user identities.
• Web Design: Combines creativity and technical skills to design visually appealing and user-friendly websites.
• Deployment with GitHub Pages, Heroku, and GUnicorn: Techniques for making web applications accessible to users online.
• PyCharm, Jupyter Notebook, Google Colab: Integrated development environments that streamline coding, testing, and collaboration.

Want to learn programming and master the building blocks of Python programming from variables to data types? Learn Python training online with Inventateq now!