Full Stack Python

Enroll Now and Become a Certified Full Stack Python Developer
5/5

Descriptions

Python is one of the most versatile and in-demand programming languages today, powering applications in web development, data science, artificial intelligence, automation, and more. With its easy-to-read syntax and strong community support, Python is an ideal choice for both beginners and experienced developers. This comprehensive Python training program is designed to help students master Python programming through hands-on projects and industry-relevant exercises. Whether you are a fresher looking to start your career or a professional seeking to upskill, this course will equip you with the essential Python skills needed to excel in today’s tech industry.

Key Points

Course Lessons

Learn how to install Python and set up a development environment. Understand Python’s syntax, variables, data types, and user input handling. Explore basic programming concepts such as operators, expressions, and statements. Write and execute simple Python programs to build a strong foundation


Master conditional statements like if-else and nested conditions to control program execution. Learn how to use loops (for, while) to perform repetitive tasks efficiently. Understand the use of break, continue, and pass statements for better loop management. Develop problem-solving skills through real-world examples and coding exercises.


Learn how to define, call, and use functions to create modular and reusable code. Understand function parameters, return values, and lambda functions for concise operations. Dive into object-oriented programming (OOP) concepts such as classes, objects, constructors, and encapsulation. Implement inheritance and polymorphism to build scalable and structured applications.


Understand how to work with files in Python by reading, writing, and appending data. Learn different file-handling modes and how to manage large files efficiently. Implement error handling using try-except blocks to prevent program crashes. Use exception handling techniques to make applications more robust and user-friendly.

Explore powerful Python libraries like Pandas and NumPy for data manipulation and analysis. Learn how to clean, transform, and filter datasets to extract useful insights. Use visualization tools like Matplotlib and Seaborn to create line graphs, bar charts, and scatter plots. Apply data analysis techniques to real-world datasets for better decision-making.
Get introduced to machine learning fundamentals and understand different types of algorithms. Learn how to implement classification, regression, and clustering models using Scikit-learn. Work on predictive analytics and AI-based solutions for practical applications. Apply all learned concepts in a capstone project to gain hands-on industry experience.

Instructor

Joshua Hamilton

Data Science Expert

This course includes:

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