Understanding how Python works in real-world applications
Installing and setting up development environments
Working with variables, datatypes & operators
Writing conditional logic & loops
Creating functions and organizing code into modules & packages
Managing files, directories & exceptions
Object-Oriented Programming (Classes, Methods, Inheritance)
Regular expressions for pattern matching
Intro to Flask for creating simple APIs
Essential libraries: NumPy, Pandas, Matplotlib
Module 2: Foundations of AI, ML & Deep Learning
How AI has evolved & where Generative AI fits in Core concepts of Machine Learning
Why Deep Learning emerged as a breakthrough
Understanding limitations of ML vs the powers of DL
End-to-end ML pipeline overview
Module 3: Applied Math for Generative AI
Derivatives & gradients simplified
How optimization algorithms work
Basics of probability used in ML
Vectors, matrices & transformations
Understanding loss landscapes
