Complete Curriculum
Course Syllabus
A comprehensive 24-week journey from AI fundamentals to advanced applications
24 Weeks
8 Modules
120+ Hours
25+ Projects
Introduction to Artificial Intelligence
History and Evolution of AI
Types of Machine Learning: Supervised, Unsupervised, Reinforcement
Python Programming for AI
Mathematics for ML: Linear Algebra & Statistics
Setting Up Your AI Development Environment
Data Collection and Web Scraping
Exploratory Data Analysis (EDA)
Data Cleaning and Transformation
Feature Engineering Techniques
Working with Pandas & NumPy
Data Visualization with Matplotlib & Seaborn
Linear & Logistic Regression
Decision Trees & Random Forests
Support Vector Machines (SVM)
K-Nearest Neighbors (KNN)
Naive Bayes Classifier
Ensemble Methods & Boosting
Model Evaluation & Cross-Validation
Neural Network Architecture
Activation Functions & Backpropagation
TensorFlow & PyTorch Frameworks
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)
Transfer Learning Techniques
Hyperparameter Tuning
Text Preprocessing & Tokenization
Word Embeddings: Word2Vec, GloVe
Sequence Models & Attention Mechanisms
Transformer Architecture Deep Dive
BERT, GPT & Large Language Models
Building Chatbots & Text Classifiers
Image Processing Fundamentals
Object Detection & YOLO
Image Segmentation Techniques
Face Recognition Systems
Generative Adversarial Networks (GANs)
Real-time Video Analysis
Reinforcement Learning & Q-Learning
Generative AI & Diffusion Models
AI Ethics & Responsible AI
MLOps & Model Deployment
AI in Production: Scaling & Monitoring
Edge AI & Mobile Deployment
Industry Capstone Project
Portfolio Building & GitHub Optimization
AI Interview Preparation
Resume Building for AI Roles
Networking in the AI Community
Career Pathways in AI/ML
