AI is transforming how we live, work, and play. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, the demand for expertise in AI and machine learning is growing rapidly. This course will enable you to take the first step toward solving important real-world problems and future-proofing your career.

This course of Artificial Intelligence with Python explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.

Learning outcomes:

1. Students will learn the fundamentals of artificial intelligence.

2. Students will learn the basics of machine learning

3. Students will learn some linear and polynomial machine learning models
4. Students will learn how to use machine learning to make AI
5. Students will learn the basics of DNN.

• Class 1


• Class 2


• Class 3


• Class 4


• ML vs Neural Network vs DL


• Class 5


• Class 6


• Class 7


• Class 8


• Class 9


• Class 10


• Class 11


• Class 12


• Class 13


• Class 14


• Class 15