Python AI/ML Development
Training

Month 1: Advanced Python & Data Engineering

• • Decorators, Generators, Context Managers, Lambda Functions
• • Advanced Pandas & NumPy Internals
• • Data Preprocessing Pipelines
• • Big Data Integration (PySpark Basics)
• • SQL & NoSQL Database Operations
• • REST APIs with Flask/FastAPI
• • Unit Testing, Debugging & Profiling

Month 2: Core AI/ML Algorithms

• • Supervised Learning: Random Forest, Gradient Boosting, XGBoost
• • Unsupervised Learning: Clustering, PCA, t-SNE
• • Hyperparameter Tuning: Grid, Random, Bayesian
• • NLP: Transformers, BERT Basics
• • Time Series: ARIMA, LSTM
• • Deep Learning with TensorFlow/Keras (CNNs, RNNs)
• • Model Interpretability (SHAP, LIME)

Month 3: Deployment & Real-World Apps

• • ML Model APIs (Flask/Django) & Docker
• • Real-time Data Streaming & Inference
• • Scalable ML Pipelines & MLOps
• • CI/CD, Monitoring & Retraining
• • AI Ethics, Fairness & Bias
• • Security in AI Deployments

Live Projects

• • Project 1: Data Pipeline & Feature Engineering
• • Project 2: Predictive Modeling & NLP
• • Project 3: ML Deployment & Monitoring Web App

Program Highlights

• ✅ 3 Deployment-Ready Projects
• ✅ Full-Stack Django Development
• ✅ ML Model Training + Web Integration
• ✅ Git, Render/Heroku Deployment
• ✅ Resume & GitHub Profile Support
• ✅ Monthly Challenges + Weekly Reviews
• ✅ Certification + Demo Day

Learning Track

• 📌 Python Programming
• 📌 Django Development
• 📌 AI/ML Fundamentals
• 📌 ML + Web Integration
• 📌 Project Showcase

Project Lineup

• 🚀 Project 1: CLI → Web (Student/Task Manager)
• 🌐 Project 2: Full-Stack Django App
• 🤖 Project 3: ML Web App (Price Prediction, Spam Filter)

Extras

• • Resume Workshop & Career Roadmap
• • GitHub Portfolio Review
• • Internship Certificate

Course 1: Advanced AI/ML Mastery

• • Ensemble Models: RF, XGBoost, CatBoost
• • Model Interpretability: SHAP, LIME
• • Deep Learning: CNNs, RNNs, LSTMs
• • NLP: Transformers, BERT, GPT
• • Time Series: ARIMA, Prophet
• • MLOps: Docker, Flask, CI/CD
• • Cloud ML Workflows (AWS/GCP/Azure)
• • Capstone AI/ML Project

Course 2: Generative AI Engineering

• • Generative Models: GANs, VAEs, Diffusion
• • NLP Models GPT, BERT Variants
• • Prompt Engineering & Optimization
• • Multimodal AI: Text-to-Image, Audio
• • Generative AI Apps: Chatbots, Content Tools
• • Deployment: APIs, Cloud Hosting
• • Responsible AI, Ethics & Safety
• • Capstone Generative AI Project