Week 1 – Python Programming Fundamentals

• Introduction to Artificial Intelligence
• Python installation and setup
  Running your first Python program
• Variables and data types
• Type conversion
• Input and output operations
• String formatting
• Debugging basics
• Operators and expressions
  
  

Week 2 – Control Flow and Logical Thinking

• If, Else, Elif statements
• Nested conditions
• Logical operators
• For loop and range
• While loop
• Break and continue
  
  

Week 3 – Data Structures and Functions

• Lists, indexing, slicing
• Tuples and Sets
• Dictionaries
• Functions and parameters
• Return values
• Lambda functions
  
  

Week 4 – Numerical Computing with NumPy

• NumPy arrays
• Array indexing and slicing
• Vector operations
• Matrix operations
• Broadcasting
• Statistical analysis using NumPy

Week 5 – Data Analysis with Pandas

• Pandas Series and DataFrames
• Reading CSV and Excel files
• Data cleaning
• Handling missing values
• GroupBy operations
• Data aggregation

Week 6 – SQL for AI and Machine Learning

• SELECT and WHERE
• GROUP BY and HAVING
• Joins
• Window functions
• Common Table Expressions

Week 7 – Machine Learning Foundations

• Supervised and Unsupervised learning
• Train-test split
• Linear regression
• Gradient descent
• Logistic regression
• Classification concepts
  
  Hands-on
• House price prediction model

Week 8 – Advanced Machine Learning Algorithms

• Decision Tree
• Random Forest
• XGBoost
• Ensemble learning
• Model evaluation metrics
  
  Hands-on
• End-to-end ML pipeline project

Week 9 – Deep Learning Fundamentals

• Neural networks
• Perceptron
• Activation functions
• Loss functions
• Backpropagation
• Neural network implementation
  
  

Week 10 – Computer Vision and Sequence Models

• Convolutional Neural Networks (CNN)
• Image classification
• Recurrent Neural Networks (RNN)
• LSTM networks
• Sequence modeling
  
  Hands-on
• Sentiment analysis system

Week 11 – Natural Language Processing (NLP)

• Tokenization
• TF-IDF
• Word embeddings
• Semantic similarity
• Cosine similarity
• Semantic search
  
  Hands-on
• Resume parser system

Week 12 – Transformers and Modern NLP

• Attention mechanism
• Transformer architecture
• BERT overview
• Fine-tuning
• Semantic search using transformers

Week 13 – Large Language Models and Prompt Engineering

• How LLMs work
• Prompt engineering
• Zero-shot prompting
• Few-shot prompting
• Chain of Thought prompting

Week 14 – Retrieval Augmented Generation (RAG)

• RAG architecture
• Embeddings
• Vector databases
• Chunking strategies
• RAG pipeline development
  
  Hands-on
• Build RAG chatbot

Week 15 – Agentic AI Systems

• Agentic AI
• Tool calling
• Memory systems
• Multi-agent systems
• Reasoning loops
  
  Hands-on
• Build AI assistant

Week 16 – LLM Optimization and Monitoring

• LLM APIs
• Rate limiting
• Logging and monitoring
• Handling hallucinations
• Evaluation techniques

Week 17 – API Development and Model Deployment

• REST APIs
• FastAPI framework
• Authentication
• Error handling
• Logging
  
  Hands-on
• Deploy ML model as API

Week 18 – Docker and Kubernetes

• Docker fundamentals
• Dockerfile creation
• Docker Compose
• Kubernetes basics
• 
  Hands-on
• Containerize ML application

Week 19 – Version Control and CI/CD

• Git and GitHub
• Branching strategies
• Pull requests
• Jenkins
• GitHub Actions
  
  Hands-on
• CI/CD pipeline implementation

Week 20 – Cloud Deployment and Final Capstone

• AWS EC2, S3, IAM
• AWS Lambda
• API Gateway
• SageMaker
• Cloud deployment
  
  Hands-on
• Deploy complete AI system on AWS