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Become top 1% in GenAI Development

In 7 weeks you'll have built and deployed 6 production GenAI applications — from finetuned LLMs to autonomous agents — ready to show in any interview or client pitch.

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Trusted by 1,000+ Practitioners
Software Engineers · Data Scientists · Architects · CTOs · Project Managers
6+Live Projects
15+Industry Tools
10+Core Skills
7Weeks · Flexible
1:1Mentorship

Most courses teach you concepts. This one ships GenAI products.

Unlike video-only platforms, every module ends with a deployed, working application. Unlike bootcamps, you get dedicated 1-on-1 mentor access throughout. Unlike generic programs, this curriculum is built around the exact skills appearing in real GenAI job descriptions today.

Project-Centric

Every module ends with a deployed app, not a Jupyter notebook.

Industry Relevant

Real business use cases, real datasets, real constraints.

Expert Guided

Kaggle Grandmasters and enterprise AI veterans.

Portfolio Ready

6+ projects any hiring manager can evaluate immediately.

Detailed Curriculum

6 projects. End-to-end GenAI.

Every concept is paired with a production deployment. 6 weeks of content, 7 weeks of building.

ModTopic & FocusKey ToolsProject(s)
01LLM Foundations & PlaygroundsFinetuning · Prompt Engineering · Model Selection · Cost Management · Model BenchmarkingCustomer Support Assistant
02Finetuning for Real Use CasesLoRA · QLoRA · PEFT · PPO · DPO · GRPO · Unsloth AIDPO Fine-tuned Enterprise Security Compliance LLM
03Retrieval-Augmented GenerationVector DBs · Hybrid Search · HyDE · Embeddings Model · Re-ranking · RAG EvaluationOptimized RAG Application for Legal Query Resolution
04AI AgentsReAct · Multi-Agent · Agentic RAG · Memory · Tool Design · MCP · A2A Protocol · LangGraphAgentic AI based Contract Document Drafter
05Deployment & EvaluationAWS · vLLM · Ollama · DeepEval · TrueLens · TTFT · MLFlow · Docker · FastAPI · StreamlitConversational BI App
06LLMOpsPipeline Tracking · Guardrails · Incident Response · Grafana · PrometheusCapstone: Full AI Answer Engine

Concepts Covered
  • Transformers, attention mechanisms, and tokenization
  • Model benchmarks: MMLU, HumanEval, MT-Bench — how to read them
  • Model selection: cost, latency, and quality trade-offs
  • Prompt engineering: zero-shot, few-shot, chain-of-thought, ReAct
  • System prompt architecture for production reliability
  • Token budgeting and API cost management from day one
Tools
OpenAIClaudeGeminiLlamaHuggingFace
Project 01
Customer Support Assistant
Build an LLM-powered assistant that answers customer queries with reliable prompts, optimized responses, and cost-aware design.

Concepts Covered
  • Parameter-efficient finetuning: LoRA, QLoRA, PEFT
  • Preference alignment: PPO, DPO, GRPO
  • Building and curating instruction datasets
  • Accelerated finetuning with Unsloth AI
  • Evaluating a tuned model against its base
  • When finetuning beats prompting — and when it doesn't
Tools
LoRAQLoRAPEFTDPOUnsloth AI
Project 02
DPO Fine-tuned Enterprise Security Compliance LLM
Fine-tune an open model with DPO to enforce enterprise security-compliance policies in every response.

Concepts Covered
  • Vector databases and embedding models
  • Chunking strategies for real documents
  • Hybrid search: dense + sparse retrieval
  • HyDE and advanced retrieval strategies
  • Re-ranking for precision
  • RAG evaluation and answer-quality baselines
Tools
ChromaQdrantPineconeLlamaIndexLangChain
Project 03
Optimized RAG Application for Legal Query Resolution
Build a retrieval system that answers legal queries with cited, verifiable sources and a measured quality baseline.

Concepts Covered
  • ReAct and reasoning-and-acting loops
  • Multi-agent orchestration and agentic RAG
  • Agent memory and state management
  • Tool design and function calling
  • MCP and A2A interoperability protocols
  • Building agents with LangGraph
Tools
LangGraphCrewAILangChainMCP
Project 04
Agentic AI based Contract Document Drafter
Ship an agent that drafts and reviews contracts with tool use, memory, and hard failure boundaries.

Concepts Covered
  • Deploying on AWS with production constraints
  • Serving with vLLM and Ollama
  • Evaluation harnesses: DeepEval and TrueLens
  • Latency targets and TTFT optimization
  • Experiment tracking with MLFlow
  • Packaging apps with Docker, FastAPI, and Streamlit
Tools
AWSvLLMOllamaDeepEvalDocker
Project 05
Conversational BI App
Deploy a monitored conversational BI app with an eval harness gating every release.

Concepts Covered
  • Pipeline tracking and reproducibility
  • Guardrails and safety boundaries
  • Incident response for GenAI systems
  • Observability with Grafana and Prometheus
  • Drift, regression, and quality monitoring
Tools
GrafanaPrometheusMLFlowDocker
Capstone
Capstone: Full AI Answer Engine
Build and operate a full AI answer engine — search, retrieval, and cited responses — monitored and defended before a review panel.

What You Actually Learn
vs What Employers Need

Every row maps to a skill appearing in real GenAI job descriptions at TCS, Barclays, Accenture, and EY.

SkillTMLC BESTIIScIIT KGPIIIT HYDIIT MadrasupGrad
Curriculum Depth
LLM foundations & benchmarksFully coveredFully coveredFully coveredFully coveredFully coveredPartially covered
Finetuning — LoRA / QLoRA / PEFTFully coveredPartially coveredPartially coveredPartially coveredNot coveredPartially covered
Alignment — DPO / ORPO / PPOFully coveredNot coveredPartially coveredNot coveredNot coveredNot covered
RAG — full production pipelineFully coveredFully coveredFully coveredPartially coveredPartially coveredNot covered
Hybrid search & re-rankingFully coveredNot coveredNot coveredNot coveredNot coveredNot covered
HyDE & advanced retrieval strategiesFully coveredNot coveredNot coveredNot coveredNot coveredNot covered
Multi-agent systemsFully coveredFully coveredFully coveredPartially coveredNot coveredNot covered
Agent Memory and Tool DesignFully coveredPartially coveredPartially coveredNot coveredNot coveredNot covered
LLMOps — monitoring & guardrailsFully coveredNot coveredNot coveredNot coveredNot coveredNot covered
vLLM / Ollama production servingFully coveredNot coveredNot coveredNot coveredNot coveredNot covered
Industry Readiness
JD alignment score92%58%50%42%33%17%
Skills from real JD requirements12/127/126/125/124/122/12
Deployed portfolio projects6+ Apps1 Capstone1 Capstone1 CapstoneCase StudiesCase Studies
Tools employers actually use15+ Tools8-10 Tools8-10 Tools6-8 Tools4-6 Tools4-6 Tools
Price₹6,999₹1,60,000₹1,80,000₹1,40,000₹3,20,000₹2,99,000
Fully coveredPartially coveredNot covered
Technology Stack

15+ industry tools

Current, production-relevant — the same tools appearing in real job descriptions.

Large Language Models
GeminiOpenAIClaudeHugging FaceGemmaLlama 3
Vector Databases
ChromaQdrantPinecone
Agentic and Data Frameworks for LLMs
LangChainLangGraphCrewAIAutoGenLlamaIndex
Training, Inference and Serving LLMs
AWSLM StudioCerebriumvLLMUnslothOllama
LLMOps, LLM Evaluation and Deployment
DockerTruLensStreamlitFastAPIDeepEvalMLflowGrafanaPrometheus
Course Mentors

Learn from practitioners

Not just instructors. Learn from Kaggle-ranked practitioners who design, deploy, and scale AI systems for real business use cases.

Saurabh ShahaneKaggle Grandmaster
Saurabh Shahane
Founder & CEO, The Machine Learning Company
  • 9+ years building enterprise Data Science, GenAI, and AI solutions across multiple domains
  • 10,000+ professionals impacted through outcome-driven learning programs
  • Consulted global enterprises and startups on scalable Enterprise AI solutions
  • Built this program around hands-on, production-first learning
Chirag ChauhanKaggle Master
Chirag Chauhan
ML Engineer, The Machine Learning Company
  • 5+ years in ML/GenAI — specializing in finetuning, deploying, and serving LLM-powered solutions
  • Expert in agentic AI architectures integrating LLMs, tools, and orchestration layers
  • Experienced MLOps practitioner focused on scalable, reliable AI systems
  • Mentored 1,000+ learners in ML, GenAI, LLM deployment, and MLOps
Success Stories From the Program

What practitioners say

"I registered for Guided Projects because I wanted real-time DL projects with team deadlines — TMLC provided exactly what I needed. I gained skills like end-to-end ML pipelines, Streamlit integration, deployment, explainable AI, and MLOps. I recommend being part of it and to keep learning."

SKSandeep Kirwai
Data Scientist II, Pattern

"This has been an insightful learning curve for me. I learnt a lot more concepts and got to understand the ones I already knew more deeply, especially modeling. I'm far more confident engaging in projects now — this was my first attempt at a project post the capstone."

Natash NalyakaNatash Nalyaka
Data Analyst, Intelligra

"I had a wonderful experience with the guided projects program. The mentor is professional and has vast knowledge, so they're able to provide help wherever necessary. I'd recommend it to anyone who's interested."

Manasvi LoganiManasvi Logani
Data Scientist, Newgen Software
What's Included

One price. Complete access.

Live Cohort

Flexible scheduling around your work calendar.

Live 1:1 Support

Personal mentor access throughout the program.

Certificate

Industry-recognized, LinkedIn-ready credential.

GenAI Jobs Roadmap

For professional advancement and role transitions.

2 Years Access

All materials, recordings, and updates.

Job Opportunities

Referrals and research opportunities in select cases.

Community Access

Professional network of AI practitioners.

6+ Portfolio Apps

Production-grade, deployed, interview-ready.

Enrollment

Ready to invest in yourself?

GenAI Program
₹6,999₹14,000
Early Bird 50% Discount20/50 seats filledOnly 30 spots left at this price
  • 6+ Production-grade portfolio projects
  • Live 1:1 doubt support from expert mentors
  • Industry-recognized Certificate of Completion
  • Career Roadmap for GenAI Opportunities
  • 2 years access to all course materials
  • Professional AI community access
  • Job / research opportunities (selected cases)
Enroll Now — ₹6,999

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TMLC was Selected by Stanford Graduate School of Business

TMLC Academy was selected for the prestigious Seed Spark Program — chosen from 140+ startups across South Asia by the Stanford Graduate School of Business. A formal validation of educational excellence and innovation.

Selected from 140+ startups across South Asia
6th cohort of the Seed Spark Program
Recognised for educational excellence and innovation
Validation from one of the world's top business schools
FAQs

Before you Enroll

Comfort with Python and Git is enough. No prior ML or GenAI experience is required — we start from LLM foundations and build up.

Sessions are live with hands-on builds and reviews. Every session is recorded and shared the same day, so you never lose progress if you miss one.

7 weeks — 6 weeks of guided content paired with builds, plus a capstone week. Plan for roughly 8–10 hours per week.

All recordings, code repositories, datasets, slide decks, and project templates — plus 2 years of access to everything, including updates.

Live sessions run on weekends and select evenings, scheduled to work around a full-time job. Exact slots are shared with your cohort before kickoff.

Program fees are non-refundable once paid, so we encourage you to get every question answered before enrolling — message us on WhatsApp and we'll help you decide honestly, including whether this program is the right fit. See our Refund Policy for the narrow exceptions.

Your next role in AI starts with your first deployed project.

Join 1,000+ software engineers, data scientists, architects, and CTOs who are already building the future of enterprise AI.

Enroll Now — ₹6,999

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