Explore the Gen AI Engineer Programme starting 14 June 2026.
See DetailsA high-fidelity, hands-on syllabus designed specifically for software engineers. Build, test, evaluate, and scale multi-agent architectures, hybrid search RAG engines, and fine-tune models for production deployments.
14 Jun 2026
9 Weeks · Live
Sat & Sun
7 Projects
Start Date
14 June 2026
Duration
9 weeks · 54 hours
Format
Weekend cohort (Sat & Sun)
Projects
7 mini-projects + 1 capstone
Mode
Live online sessions
Weeks
Duration
Hours
Total contact time
Sessions
Weekend sessions
Projects
Build portfolio
This curriculum drops basic conceptual slides to focus purely on programming, API handling, and scalable systems implementation.
Software engineers transitioning into AI/ML roles
Backend developers building AI-powered products
Data engineers extending into GenAI pipelines
Technical leads evaluating AI tooling and architecture
Prompting, structured output, and function calling
Retrieval, embeddings, and vector databases
Tool use, memory, and multi-step reasoning
Orchestration with CrewAI, AutoGen, and LangGraph
Images, audio, and multimedia via APIs
LoRA and QLoRA with open-source LLMs
Observability, guardrails, RAGAS, and LangSmith
Scalable, secure, and cost-optimized systems
Learn how each tool fits into the workflow: choose models, ground responses with retrieval, coordinate agents, test quality, and deploy safely.
The section below is grouped by skill area so you can scan from left to right, then jump straight to the part you want to revisit.
Foundation Models
Frontier APIs and open-weight models for prompt orchestration, structured output, and multimodal generation.
OpenAI GPT-4o
OpenAI
Anthropic Claude 3.5 Sonnet
Anthropic
Google Gemini 1.5 Pro
DeepSeek-R1 (Reasoning)
Reasoning model
Qwen 2.5 / Gemma 2 (Local)
Local model
Agentic Frameworks
Frameworks for typed tools, multi-step orchestration, and conversational agent loops.
PydanticAI (Type-Safe)
Python ecosystem
LangGraph (State Graphs)
State graphs
CrewAI (Role Orchestration)
Orchestration
AutoGen (Conversational Agents)
Conversational agent
Vector Search & RAG
Retrieval backends and indexing layers used to ground generation in domain knowledge.
ChromaDB (Local Store)
Local model
pgvector (SQL Search)
PostgreSQL
Neo4j (Knowledge Graphs)
Knowledge graph
LlamaIndex (Data Loading)
Data loading
Cohere Re-ranker
Re-ranking
Production & Ops
Tracing, guardrails, deployment, and evaluation tools for production systems.
LangSmith (Tracing)
Tracing
Guardrails AI (Safety)
Safety
DeepEval (Auto-Testing)
Auto-testing
LiteLLM (API Gateway)
API gateway
Modal (Serverless Deploy)
Serverless deploy
Click each curriculum phase to explore detailed weekly breakdowns, topics covered, and integrated project milestones.
All repositories, starter code bases, and sandbox API environments are provided upon cohort launch.
Guided builds throughout the programme lead into a final capstone experience.
Track your progressive journey across the 9 weeks, transitioning from foundation calls into complete cloud-deployed agents.
W1
14 Jun
W2
20 - 21 Jun
W3
27 - 28 Jun
W4
4 - 5 Jul
W5
11 - 12 Jul
W6
18 - 19 Jul
W7
25 - 26 Jul
W8
1 - 2 Aug
W9
8 - 9 Aug
A structured loop designed to fit your busy schedule while ensuring continuous coding improvements.
1.5-hour interactive sessions covering core architecture, math/reasoning models, and live programming walkthroughs.
Get the project skeleton code and step-by-step guidance to implement and test the weekly mini-project in your portfolio.
Join our weekly interactive Q&A session to debug code, discuss architectural patterns, and review advanced models.
Get help from assistants and connect with your cohort members on design choices, bugs, and project reviews.
No generic tutorials. You will build, document, test, and deploy functional applications to live servers.
OpenAI / Anthropic APIs · NumPy · Vector Math
Write vanilla code to make raw model calls, handle context windows, token limits, temperature controls, and compute embedding cosine similarity from scratch using NumPy.
PydanticAI · Jinja2 · JSON Schemas
Build a robust invoice and email data extraction pipeline with type-safe schema validations, retry loops, and self-correcting validation prompts.
ChromaDB · Embedding Models · Document Chunking
Ingest multi-format corporate manual PDFs, implement semantic and recursive character chunking, and create an optimized local vector store index database using ChromaDB.
LlamaIndex · Cohere Re-rank · HyDE
Overcome naive RAG retrieval precision limits by adding Hypothetical Document Embeddings (HyDE), query expansion, and cross-encoder re-ranking pipelines.
Tavily Search · ReAct Loop · LangSmith
Build an autonomous search agent that plans, triggers web searches, parses DOM trees, summarizes results, cites reference links, and loops until the user's query is resolved.
LangGraph / CrewAI · Message Queues · State Graphs
Design a stateful multi-agent system where specialized researcher, writer, and editor agents pass task states, handle feedback reviews, and compile detailed guides.
Modal / HuggingFace Spaces · Guardrails AI · LiteLLM · LangSmith
Design and develop a custom AI solution from scratch. You will structure a stateful multi-agent system or RAG pipeline, integrate Guardrails AI to prevent jailbreaks and hallucinations, optimize query latency, and deploy it to a serverless cloud backend with full logging and tracing via LangSmith.
The demand for engineers who can move beyond basic API wrappers and engineer production systems is growing exponentially.
₹18L - ₹35L / yr
Design, prompt, and orchestrate LLM systems, build reactive agents, and integrate foundation models into enterprise products.
₹25L - ₹45L / yr
Lead the selection of open-source vs. proprietary models, evaluate guardrails, structure vector database schemas, and optimize token costs.
₹16L - ₹30L / yr
Build robust retrieval pipelines, implement hybrid search (dense & sparse), design document splitters, and handle chunk embedding indexes.
₹15L - ₹28L / yr
Build interactive full-stack applications with AI features (real-time chat, structured JSON generation, and multimedia generation).
+210%
AI Jobs Growth (YoY)
+30-40%
Salary Premium for AI Engineers
9,000+
Companies Actively Hiring AI Engineers
This credential verifies that
Jane Doe
has successfully completed the demanding curriculum, project milestones, and capstone deployment requirements of the
Generative AI Engineer Programme
Authorized Signatory
ID: DBA-GAI-2026-0849
Earning this certificate represents real achievement. You must build, review, and deploy 7 mini-projects and a final capstone to get certified.
Every credential includes a secure URL hosted on our site for employers to verify your achievement and inspect your project implementations.
Easily showcase your certificate on your LinkedIn profile with a direct add credential link.
Unlike generic completions, your verified certificate links directly to your public GitHub capstone and live server deployment.
Our program leaders are hands-on software engineers building and scaling production AI systems every day.
Senior AI Engineer · Program Lead
IIT Madras · University of Birmingham alumni
Built production-grade multi-agent systems and RAG search engines in fintech, healthtech, and education spaces. Expert in agentic loops, prompt evaluation, and guardrail architectures.
Connect on LinkedInFounding Engineer · AI Architect
DBA Consultants lead
Specializes in scaling vector search indexing, model fine-tuning (LoRA/QLoRA), serverless deployments, and optimizing token costs for enterprise AI architectures.
Connect on LinkedInAccelerate your builds with production-ready code boilerplates and support resources.
Skip the bootstrap setup. Access clean blueprints for Next.js, FastAPI, LangGraph, PydanticAI setups, and Docker configurations.
Join a private channel of software engineers, technical leads, and founders building with AI. Share logs, get code reviews, and request job referrals.
All live classes, coding critiques, and templates are archived in 1080p. Review codebase iterations, updates, and templates anytime.
Try the programme risk-free. If you're not completely satisfied with the depth, structure, or hands-on builds within the first 7 days, request a full refund. No questions asked.
