The AI course comprises three levels. AI I covers fundamental concepts and techniques, providing a foundation in AI's history and applications. AI II explores advanced topics like natural language processing and neural networks. AI III delves into specialized areas such as generative adversarial networks, explainable AI, and ethics, offering expertise in cutting-edge applications across industries.
Concept: Intro to Python programming
Concept: Comments in Python and getting user inputs
Concept: What are "variables" in programming?
Concept: Data types in computer science
Concept: How to use arithmetic operators in Python
Concept: Python modules and turtle module
Concept: Rotating and turning with Turtle
Concept: Using loops to create patterns
Concept: Using conditionals with Turtle
Concept: Coding beautiful digital visual arts
Mini-Project:
Mini-Project:
Intro to Pygame:
Pygame user inputs events (keyboard and mouse)
Starter Project: Cube.io (Part I)
Starter Project: Cube.io (Part II)
AI I is an introductorycourse that covers fundamental concepts and techniques, such as problem-solvingusing search algorithms, knowledge representation, and basic machine learning.Students gain a foundation in AI's history, applications, and impact onindustries.
AI II builds on AI I,exploring advanced topics like natural language processing, computer vision,neural networks, and reinforcement learning. Students develop a deeperunderstanding of these concepts and their practical applications.
AI III focuses onspecialized topics and emerging trends. It covers areas like generativeadversarial networks, explainable AI, AI ethics, and real-world applications invarious industries. Students gain expertise in these cutting-edge areas.