AI & ML Professional Track
Complete Curriculum
Get the comprehensive 20-week curriculum with week-by-week breakdown, 40+ hands-on projects, interview prep topics, and complete career support details.
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What's Inside the 12-Page PDF
Week-by-Week Breakdown
Detailed schedule for all 20 weeks with Saturday & Sunday topics, timings, and hands-on sessions
5 Learning Phases
Foundations, ML, Deep Learning, NLP/LLMs, AI Agents - with specific projects for each phase
40+ Portfolio Projects
Real-world projects: RAG systems, AI agents, MLOps pipelines, computer vision apps, and more
Interview Preparation
Topic-wise interview focus areas, common questions, and mock interview structure
Career Roadmap
Resume review, LinkedIn optimization, mock interviews, and salary negotiation guidance from the instructor
Bonus Week Details
AI-powered engineering: Claude Code, GitHub Copilot, Cursor, and 10x productivity tools
Common Questions
Is this curriculum updated for 2026?
Yes! We update content quarterly. This version includes AI Agents, RAG systems, and the latest LLM techniques that companies are hiring for in 2026.
How detailed is the week-by-week breakdown?
Very detailed. Each week includes Saturday & Sunday schedules with specific timings, topics, hands-on projects, interview focus areas, and homework assignments.
What if the schedule does not work for me?
All sessions are recorded in HD. You get lifetime access to recordings, course materials, and community support.
What career support do you provide?
We provide resume reviews, mock interviews, LinkedIn optimization, and portfolio guidance directly from the instructor. We do not promise job placement or referrals, but we do help you get genuinely interview-ready.
Ready to transform your career? Check out our courses or talk to a counselor.
ThriveWithAI
AI/ML Professional Track - Complete Syllabus
20-Week Curriculum | Sat & Sun 9 AM - 2:30 PM IST | July 2026 Cohort
Saturday Schedule:
- 9:00-10:30 - Data Science, AI, ML & GenAI Overview
- 10:45-12:15 - Python: Variables, Data Types, Functions
- 1:00-2:30 - Python: OOP Basics (Classes, Inheritance)
Sunday Schedule:
- 9:00-10:30 - NumPy Arrays & Operations
- 10:45-12:15 - NumPy Advanced: Linear Algebra Ops
- 1:00-2:30 - Project: Stock Portfolio Analyzer
Projects: Stock Portfolio Analyzer CLI, Automated Data Pipeline
Interview Focus: Python fundamentals, NumPy operations, OOP concepts
Saturday Schedule:
- 9:00-10:30 - Pandas: Series & DataFrames
- 10:45-12:15 - Data Cleaning & Transformation
- 1:00-2:30 - Grouping, Aggregation & Merging
Sunday Schedule:
- 9:00-10:30 - Matplotlib Fundamentals
- 10:45-12:15 - Seaborn for Statistical Visualization
- 1:00-2:30 - Project: EDA Dashboard
Projects: COVID-19 Data Tracker, Spotify Trends Analyzer
Interview Focus: Pandas operations, data cleaning, visualization choices
Saturday Schedule:
- 9:00-10:30 - Descriptive Statistics Deep Dive
- 10:45-12:15 - Probability Rules & Bayes Theorem
- 1:00-2:30 - Probability Distributions
Sunday Schedule:
- 9:00-10:30 - Hypothesis Testing Fundamentals
- 10:45-12:15 - Confidence Intervals & Statistical Tests
- 1:00-2:30 - Project: Statistical Analysis Report
Projects: E-commerce A/B Testing Platform, Insurance Risk Calculator
Interview Focus: Probability concepts, hypothesis testing, statistical significance
Saturday Schedule:
- 9:00-10:30 - Vectors & Matrices Operations
- 10:45-12:15 - Linear Transformations
- 1:00-2:30 - Eigenvalues & Eigenvectors
Sunday Schedule:
- 9:00-10:30 - SVD & Matrix Decomposition
- 10:45-12:15 - Linear Algebra in ML Context
- 1:00-2:30 - Project: Image Compression Tool
Projects: Image Compression Engine (PCA-based), 3D Data Visualization Tool
Interview Focus: Matrix operations, eigenvalues, SVD applications
Saturday Schedule:
- 9:00-10:30 - Derivatives & Partial Derivatives
- 10:45-12:15 - Chain Rule & Computational Graphs
- 1:00-2:30 - Gradient Descent Algorithms
Sunday Schedule:
- 9:00-10:30 - Optimization in ML Context
- 10:45-12:15 - A/B Testing & Experimentation
- 1:00-2:30 - Project: Gradient Descent Visualizer
Projects: Neural Network Training Visualizer, ML Algorithm Comparison Dashboard
Interview Focus: Gradient descent, learning rates, optimization challenges
Saturday Schedule:
- 9:00-10:30 - Linear Regression Deep Dive
- 10:45-12:15 - Polynomial Regression & Overfitting
- 1:00-2:30 - Feature Engineering Techniques
Sunday Schedule:
- 9:00-10:30 - Regularization: Lasso & Ridge
- 10:45-12:15 - Scikit-learn Pipelines
- 1:00-2:30 - Project: Real Estate Price API
Projects: Real Estate Price Prediction API, Airbnb Pricing Optimizer
Interview Focus: Regression assumptions, regularization, feature engineering
Saturday Schedule:
- 9:00-10:30 - Logistic Regression
- 10:45-12:15 - Decision Trees & Random Forest
- 1:00-2:30 - SVM & Naive Bayes
Sunday Schedule:
- 9:00-10:30 - Model Evaluation Metrics
- 10:45-12:15 - Handling Imbalanced Data
- 1:00-2:30 - Project: Customer Churn Predictor
Projects: Customer Churn Prediction, Credit Card Default Classifier
Interview Focus: Classification algorithms, metrics, imbalanced data
Saturday Schedule:
- 9:00-10:30 - Bagging & Boosting Theory
- 10:45-12:15 - XGBoost Deep Dive
- 1:00-2:30 - LightGBM & CatBoost
Sunday Schedule:
- 9:00-10:30 - Hyperparameter Tuning
- 10:45-12:15 - Cross-Validation Strategies
- 1:00-2:30 - Project: Fraud Detection System
Projects: Real-Time Fraud Detection Engine, Loan Approval System
Interview Focus: Boosting algorithms, hyperparameter tuning strategies
Saturday Schedule:
- 9:00-10:30 - K-Means & Hierarchical Clustering
- 10:45-12:15 - DBSCAN & Density-Based Clustering
- 1:00-2:30 - PCA & Dimensionality Reduction
Sunday Schedule:
- 9:00-10:30 - Anomaly Detection
- 10:45-12:15 - Recommendation Systems Intro
- 1:00-2:30 - Project: Customer Segmentation
Projects: Customer Segmentation Engine, Anomaly Detection Dashboard
Interview Focus: Clustering algorithms, PCA, anomaly detection
Saturday Schedule:
- 9:00-10:30 - Perceptrons & MLPs
- 10:45-12:15 - Activation Functions & Backprop
- 1:00-2:30 - TensorFlow Basics
Sunday Schedule:
- 9:00-10:30 - PyTorch Fundamentals
- 10:45-12:15 - Batch Norm, Dropout, Regularization
- 1:00-2:30 - Project: MNIST Classifier from Scratch
Projects: MNIST Classifier from Scratch, Fashion Classifier
Interview Focus: Neural network architecture, backpropagation, activation functions
Saturday Schedule:
- 9:00-10:30 - Convolutions & Pooling
- 10:45-12:15 - CNN Architectures (LeNet to ResNet)
- 1:00-2:30 - Data Augmentation Strategies
Sunday Schedule:
- 9:00-10:30 - Transfer Learning
- 10:45-12:15 - Fine-tuning Pre-trained Models
- 1:00-2:30 - Project: Medical Image Classifier
Projects: Medical X-ray Diagnosis, Product Visual Search
Interview Focus: CNN architectures, transfer learning, data augmentation
Saturday Schedule:
- 9:00-10:30 - Object Detection (YOLO, Faster R-CNN)
- 10:45-12:15 - Image Segmentation (U-Net, Mask R-CNN)
- 1:00-2:30 - Video Analysis & Tracking
Sunday Schedule:
- 9:00-10:30 - Edge Deployment (ONNX, TensorRT)
- 10:45-12:15 - Real-time Inference Optimization
- 1:00-2:30 - Project: Real-time Object Detection
Projects: Real-time Object Detection App, Autonomous Vehicle Simulator
Interview Focus: Object detection, segmentation, model optimization
Saturday Schedule:
- 9:00-10:30 - GANs: Architecture & Training
- 10:45-12:15 - VAEs & Latent Spaces
- 1:00-2:30 - Diffusion Models (DDPM)
Sunday Schedule:
- 9:00-10:30 - Stable Diffusion Internals
- 10:45-12:15 - ControlNet & Fine-tuning
- 1:00-2:30 - Project: Custom Image Generation
Projects: Custom Image Generation Pipeline, Style Transfer App
Interview Focus: GANs, diffusion models, generative AI applications
Saturday Schedule:
- 9:00-10:30 - Tokenization & Embeddings
- 10:45-12:15 - Word2Vec, GloVe, FastText
- 1:00-2:30 - RNNs & LSTMs
Sunday Schedule:
- 9:00-10:30 - Attention Mechanism Deep Dive
- 10:45-12:15 - Transformer Architecture from Scratch
- 1:00-2:30 - Project: Sentiment Analysis Engine
Projects: Sentiment Analysis Engine, Text Classification System
Interview Focus: Tokenization, embeddings, attention mechanism, transformers
Saturday Schedule:
- 9:00-10:30 - BERT, RoBERTa, DistilBERT
- 10:45-12:15 - GPT Family & Hugging Face Hub
- 1:00-2:30 - Named Entity Recognition
Sunday Schedule:
- 9:00-10:30 - Question Answering Systems
- 10:45-12:15 - Text Summarization & Generation
- 1:00-2:30 - Project: Legal Document Analyzer
Projects: Legal Document Analyzer, Customer Support Classifier
Interview Focus: BERT, GPT, Hugging Face, NLP tasks
Saturday Schedule:
- 9:00-10:30 - Fine-tuning with LoRA & QLoRA
- 10:45-12:15 - PEFT Techniques
- 1:00-2:30 - Training on Custom Data
Sunday Schedule:
- 9:00-10:30 - Prompt Engineering Patterns
- 10:45-12:15 - Chain-of-Thought, Few-Shot, ReAct
- 1:00-2:30 - Project: Domain-Specific Chatbot
Projects: Domain-Specific Chatbot, Custom LLM Assistant
Interview Focus: LoRA, QLoRA, prompt engineering, fine-tuning strategies
Saturday Schedule:
- 9:00-10:30 - Vector Databases (Pinecone, ChromaDB)
- 10:45-12:15 - Chunking & Embedding Strategies
- 1:00-2:30 - RAG Architecture Design
Sunday Schedule:
- 9:00-10:30 - Advanced RAG: Re-ranking & Hybrid Search
- 10:45-12:15 - RAG Evaluation & Optimization
- 1:00-2:30 - Project: Enterprise Knowledge Base
Projects: Enterprise RAG System (10K+ docs), Document QA Bot
Interview Focus: RAG architecture, vector databases, retrieval strategies
Saturday Schedule:
- 9:00-10:30 - Agent Architectures (ReAct, Plan-Execute)
- 10:45-12:15 - Tool Use & Function Calling
- 1:00-2:30 - LangChain Agents
Sunday Schedule:
- 9:00-10:30 - LlamaIndex Agents
- 10:45-12:15 - Memory Systems & Context Management
- 1:00-2:30 - Project: Autonomous Research Agent
Projects: Autonomous Research Agent, Multi-Agent System
Interview Focus: Agent architectures, tool use, LangChain/LlamaIndex
Saturday Schedule:
- 9:00-10:30 - MLflow & Experiment Tracking
- 10:45-12:15 - Docker & Containerization
- 1:00-2:30 - Kubernetes for ML
Sunday Schedule:
- 9:00-10:30 - FastAPI for Model Serving
- 10:45-12:15 - Monitoring & Drift Detection
- 1:00-2:30 - Project: End-to-End ML Pipeline
Projects: Production ML Pipeline with CI/CD, Model Monitoring Dashboard
Interview Focus: MLOps, Docker, Kubernetes, model serving, monitoring
Saturday Schedule:
- 9:00-12:15 - Capstone Presentations
- 1:00-2:30 - Code Review & Architecture Feedback
Sunday Schedule:
- 9:00-10:30 - System Design Interview Prep
- 10:45-12:15 - Mock Interviews & Resume Workshop
- 1:00-2:30 - Graduation & Next Steps
Deliverables: Production-ready capstone, optimized resume, interview readiness
Career Support: Mock interviews, LinkedIn optimization, job referrals
Claude Code
Multi-file editing, codebase understanding, debugging
GitHub Copilot
Inline completions, chat, test generation
Cursor IDE
AI-native development workflows
AI Workflows
TDD with AI, code review, refactoring
Ready to transform your career?
Website: thrivewithai.live | Email: hello@thrivewithai.live | Start Date: 11th July, 2026
ThriveWithAI | Professional AI/ML Training | Curriculum v2.0 - April 2026