Week 1: Introduction to AI and Its Applications

• What is AI? History & Evolution

• Types of AI: Narrow vs. General

• Real-world AI: Healthcare, Finance, Gaming, Business

• Mini Project: Build a simple rule-based chatbot

Week 2: Machine Learning Essentials

• Supervised, Unsupervised & Reinforcement Learning

• Key Concepts: Features, Labels, Training, Overfitting

• Intro to Python libraries: NumPy, Pandas, Scikit-learn

• Lab: Predict housing prices using linear regression

Week 3: Deep Learning Fundamentals

• Neural Networks Explained (perceptrons, activation, backprop)

• CNNs, RNNs, Transformers (overview only)

• TensorFlow & PyTorch basics

• Lab: Image classification with CNN (MNIST)

Week 4: Natural Language Processing (NLP)

• Text Preprocessing: Tokenization, Stopwords, Lemmatization

• Embeddings: Word2Vec, BERT

• Introduction to Prompt Engineering

• Project: Sentiment analysis using HuggingFace Transformers

Week 5: Building AI-Powered Applications

• OpenAI API (ChatGPT, DALL·E)

• LangChain basics (memory, tools, agents)

• AI for Search, Summarization, Chatbots

• Mini Project: Build an AI-based travel assistant

Week 6: Ethics, Safety & Future of AI

• AI Bias, Privacy, and Regulations

• Responsible AI & Explainability

• Trends: AutoML, AGI, Open Source Models

• Capstone Project: Create an AI application (your choice)

🎯 Key Features

• Hands-on labs in Google Colab or Jupyter Notebooks

• Video lectures with downloadable notes

• Certificate of Completion

• Optional access to a private Discord server for Q&A