Introduction to AI

Description

🧠 Module 1: Foundations of AI and Intelligent Systems

• What is Artificial Intelligence? Scope and applications

• Differentiating AI, Machine Learning, and Deep Learning with real-world use cases

• Generative AI: How tools like ChatGPT, DALL·E, and Midjourney work

• Real-World Productivity with AI: ChatGPT for writing/code, Notion AI for task management, Bard/Copilot for research

📐 Module 2: Mathematical Foundations for AI

• Refresher: Algebra, equations, exponents, functions

• Vectors and matrices: operations, transformations, applications in ML

• Coordinate Geometry and distance measures

• Intro to Linear Algebra: dot product, matrix multiplication, identity matrices

🤖 Module 3: How Machines Learn

• Neural Networks: What they are and how they mimic the brain

• Layers, neurons, weights, and activation functions

• Forward propagation walkthrough

• Gradients and backpropagation simplified

• Understanding loss functions, cost minimization, and optimization with examples (like SGD)

🔍 Module 4: Exploring AI in Action

• Hands-on: Try AI demos (face detection, object detection using OpenCV or Mediapipe)

• Play with AI image generation (DALL·E, Stable Diffusion, Playground AI)

• Use Text-to-Speech (TTS) and Speech Recognition tools (Whisper, Google STT)

• Create avatars or voices with tools like Ready Player Me, ElevenLabs, or Synthesia

💻 Module 5: Getting Started with AI Programming – PyTorch Basics

• What is PyTorch? Why is it used in AI/ML research?

• Install and set up a Python + PyTorch environment (locally or with Google Colab)

• Understanding Tensors and how they represent data

• Build a basic neural network from scratch

• Train the model on sample datasets (like MNIST)

• Track accuracy, loss, and visualize results using matplotlib

🏁 Project: Build and Present Your First AI Mini Project

• Ideas: Digit Recognizer, AI-based Calculator, Face Detection App, Art Generator

• Use modular thinking: input, model, output

• Train or use pre-trained models

• Present code, working demo, and your learnings