Python Programming: Learn Python from Scratch to AI and ML

Name: Python Programming: Learn Python from Scratch to AI and ML
Rating: 4.6 (889 reviews)

Learn Python Programming from basics to advance level, a complete beginner course with machine learning basics covered

Created byShahzad Khan, Munir Malik

Last updated 1/2026

English

What you'll learn

Learners will gain a solid foundation in Python programming, including variables, data types, operators, and basic syntax, enabling them to write simple program
Students will learn essential programming concepts such as loops, conditionals, functions, and error handling, which are critical for building efficient and str
Participants will explore Python's built-in data structures like lists, tuples, dictionaries, and sets, and understand how to manipulate and organize data effec
By completing hands-on exercises and mini-projects, learners will build problem-solving skills and apply Python to real-world scenarios.

Course content

6 sections • 36 lectures • 4h 23m total length

1. Introduction to Python: Installation and PyCharm IDE Setup5:51
2. Using the print() Function to Display Text, Numbers, and Variables4:05
3. Understanding Variables in Python with Practical Examples4:45
Learn how to create Python variables to store integers, floats, strings, and booleans, assign and print values, and apply case sensitivity with practical examples like a library book availability check.
4. Taking User Input Using the input() Function (Single & Multiple Inputs)4:34
Use Python's input() to get user input and store it in a variable. Learn to print prompts, handle strings, and split input into two numbers for processing.
5. Data Type Conversion in Python: Casting and Value Transformation7:22
6. String Indexing in Python Explained with Hands-On Examples3:54
7. Python String Methods: Working with and Manipulating Text Efficiently3:28

1. Python Arithmetic Operations: Performing Basic and Advanced Calculations4:18
Explore Python arithmetic operations such as addition, division, floor division, modulus, and exponentiation, using variables and print statements to display results.
2. Commonly Used Math Functions in Python Explained4:06
3. Conditional Statements in Python: if, elif, and else Explained3:57
4. Logical AND Operator in Python: Combining Multiple Conditions3:53
5. Logical OR Operator in Python: Handling Alternative Conditions3:41
6. Logical NOT Operator in Python: Negating Conditions Effectively2:46
7. Comparison Operators in Python: Building Conditions and Control Flow9:27

1. Python Fundamentals Recap: Reviewing Key Concepts9:30
2. While Loop in Python: Repetitive Execution and Flow Control5:18
3. For Loop in Python: Iterating Over Sequences Efficiently8:24
4. Lists in Python: Storing, Accessing, and Managing Data7:39
Explore how to store data in lists, print items, access by index including negative indices, slice ranges, modify elements, and concatenate and slice lists.
5. List Methods in Python: Modifying and Working with Lists8:38
6. Dictionaries in Python: Managing Data Using Key-Value Pairs8:21
Learn how to create and manipulate dictionaries in Python, print values by key, access and update entries, handle missing keys, and map digits to words with practical examples.

1. Exception Handling in Python: Managing and Debugging Errors6:28
Master Python exception handling with try and except blocks to validate input, convert to integers, and prevent crashes; learn to handle value error and zero division error.
2. Functions in Python: Creating Reusable and Modular Code10:43
3. Classes in Python: Understanding Object-Oriented Programming Basics13:26
4. Constructors in Python: Initializing Objects and Class Data14:41
5. Inheritance in Python: Extending and Reusing Class Functionality12:51

1. Working with Spreadsheets for AI and Machine Learning Tasks19:21
2. Introduction to Jupyter Notebooks for Data Science Projects6:39
3. Importing and Preparing Data for Machine Learning Models5:59
4. Essential Keyboard Shortcuts for an Efficient Data Science Workflow6:44
5. Training Machine Learning Models: Step-by-Step Process12:30
6. Evaluating Machine Learning Models: Accuracy Metrics and Techniques8:37
7. Exporting Trained Models: Saving and Deploying Machine Learning Solutions5:50
Save trained models with joblib, load them in future tasks, and reuse for predictions to save time and avoid retraining.

Requirements

This course is designed for absolute beginners, so no previous coding knowledge is required.
Learners should be comfortable using a computer, navigating files, and installing software.
Students will need a laptop or desktop with internet access to download Python and follow along with the course.

Description

Welcome to Python Course, where you Learn Python Programming from basics: Python Programming from basics to advance level, a complete beginner course with machine learning basics covered

In this fast-paced, hands-on course, you’ll revisit the core concepts of Python programming and strengthen your skills in record time. We’ll cover everything from data types, loops, and functions to more advanced topics like object-oriented programming and error handling. Each lesson is focused and practical, providing you with the tools you need to write clean, efficient Python code. You'll also work on mini-projects that apply the concepts learned in real-world scenarios. This course also emphasizes debugging and best practices to ensure you write reliable, high-quality code.

By the end of this course, you'll feel confident in your understanding of Python’s essentials, equipped to tackle more complex projects or advance to more specialized areas of programming. Whether you're preparing for a job interview, working on a project, or just brushing up on your Python knowledge, this course has got you covered. With clear explanations and practical exercises, you’ll be ready to take your Python skills to the next level and confidently apply them in your career.

Sure! Here’s an alternative ending line for your course description:

If you’re ready to sharpen your Python skills and unlock new opportunities, this course is the perfect starting point.

Who this course is for:

Individuals with no prior programming experience who want to start their coding journey with Python.
Those looking to build a strong foundation in Python to pursue careers in software development, data analysis, or automation.
Students, professionals, or hobbyists seeking to learn Python quickly for academic projects, career advancement, or personal growth.
Individuals transitioning into tech roles who need a beginner-friendly yet comprehensive introduction to Python.

Python Programming: Learn Python from Scratch to AI and ML

What you'll learn

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Course content

Module 1: Getting Started with Python7 lectures • 34min

Module 2: Python Logic, Operators & Control Flow7 lectures • 32min

Module 3: Loops & Core Data Structures in Python6 lectures • 48min

Module 4: Advanced Python & Object-Oriented Programming5 lectures • 58min

Module 5: Python Modules, Packages & Dependency Management4 lectures • 26min

Module 6: AI & Machine Learning Fundamentals and Workflow7 lectures • 1hr 6min

Requirements

Description

Who this course is for: