18-Month AI Career Program

From Python Beginner to AI Engineer.

A meticulously structured, production-focused curriculum that transforms you from learning syntax to deploying large language models at scale.

Start Your Journey
18
Months
5
Career Phases
27+
Core Topics
27+
Real Projects
Beginner
Foundations
Machine Learning
Deep Learning & NLP
Generative AI
Production & Career
Job Ready
Phase 1

Foundations

Python, Math & Data

01
3 weeks

Python for Data Science

Start from zero and build strong Python fundamentals — variables, data types, loops, functions, OOP, file handling, and error handling. You'll write clean, readable code from day one with real exercises.

PythonOOPFile I/OException Handling

Hands-on Project

Automated Student Grade Tracker with file I/O and summary reports

Target Role

Junior Python Developer / Data Analyst

02
2 weeks

Data Analysis with Pandas & NumPy

Master the two most-used data science libraries. Learn to clean messy datasets, filter, group, aggregate, merge, and reshape data — exactly how data analysts work every day at top companies.

PandasNumPyData CleaningAggregation

Hands-on Project

IPL Match Dataset Analysis — uncover winning patterns and player performance

Target Role

Data Analyst / Business Intelligence Analyst

03
2 weeks

Data Visualisation & Storytelling

Turn raw numbers into compelling visuals. Build interactive charts with Matplotlib, Seaborn, and Plotly. Learn the principles of visual storytelling that make dashboards executives actually read.

MatplotlibSeabornPlotlyDashboarding

Hands-on Project

India COVID-19 Dashboard — interactive regional trend visualisation

Target Role

Data Analyst / BI Developer

04
2 weeks

SQL & Relational Databases

Write SQL that real data engineers write — complex JOINs, window functions, CTEs, subqueries, and performance optimisation. Work with PostgreSQL and MySQL on real schemas.

SQLPostgreSQLWindow FunctionsCTEs

Hands-on Project

E-commerce Sales Analytics Database — customer segmentation and revenue reporting

Target Role

Data Analyst / Backend Developer

05
2 weeks

Statistics & Probability for ML

Build the mathematical intuition that separates great ML engineers from average ones. Covers descriptive stats, distributions, hypothesis testing, A/B testing, Bayes' theorem, and correlation.

ProbabilityHypothesis TestingBayesian ThinkingA/B Testing

Hands-on Project

A/B Test Analyser — statistical significance calculator for marketing campaigns

Target Role

Data Scientist / ML Engineer

Phase 2

Machine Learning

Predictive Modeling

01
3 weeks

Machine Learning Fundamentals

Understand how machines actually learn. Gradient descent, bias-variance tradeoff, overfitting, cross-validation, and evaluation metrics explained with visual intuition — not just formulas.

Scikit-learnModel EvaluationFeature EngineeringCross-Validation

Hands-on Project

House Price Prediction System with end-to-end model evaluation pipeline

Target Role

Junior ML Engineer

02
3 weeks

Supervised Learning Algorithms

Deep dives into Linear Regression, Logistic Regression, Decision Trees, Random Forests, SVM, KNN, Gradient Boosting, and XGBoost. When to use each, and why.

Random ForestXGBoostSVMGradient Boosting

Hands-on Project

Loan Default Prediction Model for a fintech company — deployed as REST API

Target Role

ML Engineer / Data Scientist

03
2 weeks

Unsupervised Learning & Clustering

K-Means, DBSCAN, Hierarchical Clustering, PCA, t-SNE, and anomaly detection. These algorithms power recommendation engines, fraud detection, and customer segmentation at scale.

K-MeansPCAt-SNEAnomaly Detection

Hands-on Project

Customer Segmentation Engine for a D2C brand — actionable marketing cohorts

Target Role

ML Engineer / Data Scientist

04
2 weeks

Feature Engineering & Model Optimisation

The skill that separates Kaggle beginners from competition winners. Master encoding, scaling, imputation, feature selection, hyperparameter tuning with Optuna, and building robust ML pipelines.

OptunaPipelineHyperparameter TuningEncoding

Hands-on Project

Kaggle-ready ML pipeline for a tabular dataset — top 10% score target

Target Role

Senior ML Engineer

05
2 weeks

ML Model Deployment with FastAPI

Take your trained models to production. Build REST APIs with FastAPI, containerise with Docker, and deploy to cloud platforms. Learn versioning, monitoring, and serving at scale.

FastAPIDockerREST APIModel Serving

Hands-on Project

Production Spam Detection API — FastAPI + Docker + cloud deployment

Target Role

ML Engineer / MLOps Engineer

Phase 3

Deep Learning & NLP

Neural Networks

01
3 weeks

Neural Networks & Deep Learning

Build neural networks from scratch in NumPy, then in PyTorch. Understand backpropagation, activation functions, batch normalisation, dropout, and learning rate scheduling without the black-box mystery.

PyTorchBackpropagationBatch NormRegularisation

Hands-on Project

Handwritten Digit Recognition System — from scratch to 99.2% accuracy

Target Role

Deep Learning Engineer

02
3 weeks

Computer Vision with CNNs

Convolutional Neural Networks, object detection (YOLO), image segmentation, and transfer learning with pre-trained models like ResNet and EfficientNet. Build systems that see and understand images.

CNNYOLOOpenCVTransfer LearningResNet

Hands-on Project

Real-time Face Mask Detection System — OpenCV + YOLO + live camera feed

Target Role

Computer Vision Engineer — ₹12–22 LPA

03
2 weeks

Transformers & BERT

Understand the attention mechanism, multi-head attention, and the transformer architecture that powers every modern AI system. Fine-tune BERT, RoBERTa, and DistilBERT on domain-specific tasks.

BERTAttention MechanismHuggingFaceFine-Tuning

Hands-on Project

Legal Document Summariser — fine-tuned BERT on Indian legal corpus

Target Role

NLP Engineer / LLM Engineer — ₹15–28 LPA

04
2 weeks

Time Series Forecasting

ARIMA, SARIMA, Prophet, and LSTM-based forecasting. Build models that predict stock prices, sales demand, and energy consumption. Critical for fintech, retail, and supply chain roles.

ARIMALSTMProphetForecasting

Hands-on Project

Stock Price Movement Forecasting — LSTM with uncertainty quantification

Target Role

Data Scientist / Quantitative Analyst

05
2 weeks

Recommender Systems

Collaborative filtering, content-based filtering, matrix factorisation, and hybrid approaches. Build the engines behind Netflix recommendations, Amazon product suggestions, and Spotify Discover Weekly.

Collaborative FilteringMatrix FactorisationHybrid Systems

Hands-on Project

Movie Recommendation Engine — deployed with a React frontend and user dashboard

Target Role

ML Engineer / AI Engineer at product companies

Phase 4

Generative AI

LLMs & Agents

01
3 weeks

Natural Language Processing

Text preprocessing, TF-IDF, word embeddings (Word2Vec, GloVe), sentiment analysis, named entity recognition, and text classification. The foundation for every LLM-powered application.

NLTKspaCyWord2VecTransformers Basics

Hands-on Project

Multi-class News Category Classifier with custom embeddings and REST endpoint

Target Role

NLP Engineer / AI Engineer

02
2 weeks

Generative AI Fundamentals

GANs, VAEs, diffusion models, and the landscape of modern generative AI. Understand how Stable Diffusion, Midjourney, and DALL·E work under the hood. Generate images, audio, and text programmatically.

GANsDiffusion ModelsStable DiffusionVAEs

Hands-on Project

AI Art Generation Studio — fine-tuned Stable Diffusion on custom style dataset

Target Role

Generative AI Engineer — one of the hottest roles in 2025

03
2 weeks

LLM Engineering & Prompt Design

Go beyond basic ChatGPT prompting. Master few-shot prompting, chain-of-thought reasoning, prompt chaining, structured outputs, and building reliable LLM-powered applications with OpenAI and Gemini APIs.

Prompt EngineeringOpenAI APIGemini APIStructured Outputs

Hands-on Project

Intelligent Customer Support Bot — GPT-4 with fallback handling and cost controls

Target Role

LLM Engineer / AI Architect — ₹18–35 LPA

04
2 weeks

RAG — Retrieval Augmented Generation

Build AI systems that reason over your own documents without hallucinating. Chunking strategies, embedding models, vector databases (Pinecone, Weaviate, FAISS), and hybrid retrieval pipelines.

RAGPineconeFAISSLangChainEmbeddings

Hands-on Project

Company Knowledge Base Chatbot — RAG over 500-page PDF corpus, sub-2s latency

Target Role

AI Engineer / Solutions Architect — top demand role at startups

05
3 weeks

LLM Fine-Tuning & RLHF

Fine-tune open-source LLMs (Llama 3, Mistral, Phi-3) using LoRA and QLoRA on consumer hardware. Understand RLHF, DPO, and instruction tuning — the techniques that made ChatGPT actually useful.

LoRAQLoRALlama 3MistralRLHFDPO

Hands-on Project

Domain-Specific Medical Q&A Model — LoRA fine-tuned Llama 3 on clinical notes

Target Role

Senior AI Engineer / ML Research Engineer — rare, high-paying skill

06
2 weeks

AI Agents & Agentic Systems

Build autonomous AI agents that plan, use tools, browse the web, write code, and self-correct. ReAct agents, multi-agent orchestration with LangGraph and AutoGen, memory systems, and agent safety.

LangGraphAutoGenTool UseMemoryReAct

Hands-on Project

Autonomous Research Agent — crawls web, synthesises findings, writes reports

Target Role

Agentic AI Developer — the frontier of AI engineering in 2025

07
1 week

Vector Databases & Semantic Search

Deep dive into embedding models, approximate nearest-neighbour search (HNSW, IVF), and production vector database systems. Build semantic search engines that understand meaning, not just keywords.

PineconeWeaviateFAISSHNSWEmbeddings

Hands-on Project

Semantic Job Search Engine — 50K+ job descriptions, real-time query matching

Target Role

AI/ML Engineer at search-centric companies — Swiggy, Flipkart, Amazon

Phase 5

Production & Career

MLOps & System Design

01
2 weeks

MLOps & Production ML Systems

CI/CD for ML, experiment tracking with MLflow, model registry, A/B testing models in production, drift detection, and automated retraining pipelines. How Netflix and Uber run ML at scale.

MLflowCI/CDDrift DetectionModel RegistryAirflow

Hands-on Project

Full MLOps Pipeline — training, tracking, deployment, monitoring for a fraud model

Target Role

MLOps Engineer — ₹15–30 LPA, critically understaffed role

02
2 weeks

Cloud AI — AWS, GCP & Azure

Deploy AI workloads on the big three clouds. AWS SageMaker, GCP Vertex AI, Azure ML, serverless inference, GPU instance management, and cloud cost optimisation for ML workloads.

AWS SageMakerGCP Vertex AIServerlessGPU Instances

Hands-on Project

Auto-scaling Inference Service — SageMaker endpoint with load testing and cost report

Target Role

Cloud ML Engineer / Solutions Architect — cloud certifications supported

03
1 week

AI System Design

Design AI systems the way FAANG engineers do. Feature stores, embedding pipelines, online vs. offline serving, caching strategies, and how to answer ML system design interview questions at L5+ level.

Feature StoresSystem DesignInterview PrepArchitecture

Hands-on Project

Design Document — Instagram-scale recommendation system with full architecture review

Target Role

Senior ML Engineer / Staff Engineer at top product companies

04
1 week

Enterprise AI & AI Products

How enterprises buy, build, and deploy AI. Responsible AI, compliance, model governance, AI product management, and building internal AI tools that actually get adopted. For students targeting senior roles.

Responsible AIAI GovernanceProduct ManagementROI Modelling

Hands-on Project

AI Product Spec — end-to-end product requirements for an internal HR AI assistant

Target Role

AI Product Manager / AI Consultant — ₹18–40 LPA

05
6 weeks

Capstone Project & Placement Prep

Your final 6-week capstone — a production-grade AI system of your choosing, reviewed by industry mentors. Paired with intensive placement prep: mock interviews, resume polish, LinkedIn optimisation, and referrals.

Full-Stack AIPortfolioInterview PrepNegotiation

Hands-on Project

Your own AI product — mentored, deployed, and added to your portfolio

Target Role

Job-ready for ₹8–35 LPA AI roles across India and remotely

Apply Your Skills

You won't just learn AI.
You'll build with it.

Phase 5

ChatGPT Clone Architecture

Streaming LLM responses with memory and RAG.

Explore Project
Phase 3

Real-time Face Mask Detection

Live computer vision with YOLO and OpenCV.

Explore Project
Phase 4

Autonomous Research Agent

Multi-agent orchestration using LangGraph.

Explore Project
Phase 3

Stock Price Forecasting

LSTM time-series analysis for financial data.

Explore Project
Phase 4

Company Knowledge Base

RAG system using Pinecone and Llama-3.

Explore Project
Phase 5

Full MLOps Fraud Detection

CI/CD, model tracking, and Kafka streaming.

Explore Project

Roles You'll Be Prepared For

Our curriculum aligns perfectly with the most in-demand technical roles in the industry today.

Machine Learning Engineer
Data Scientist
Generative AI Engineer
NLP Engineer
Computer Vision Engineer
MLOps Engineer
AI Solutions Architect
Data Analyst
AI Product Manager

Your AI Career Starts Here.

18 months. 27+ Real projects. Production-grade AI skills. Stop watching tutorials and start building systems companies actually need.