College students
Practical Gen AI for College Students: Build, Deploy, Get Hired
Build, deploy, get hired: 12 weeks from prompting and Python APIs to deployed RAG apps and agents, ending in a portfolio-grade capstone.
Duration
12 weeks (3 months)
Format
2 × 2 h live per week + Wednesday lab clinic
Batch size
20-30 online
Live hours
48 live + 12 lab/doubt hours + ~5 hours/week of project work
For UG/PG students and fresh graduates. Phase 1 builds foundations and a first deployed app, Phase 2 covers RAG end to end, and Phase 3 covers agents plus career prep (resume, LinkedIn, GitHub, mock interviews). Three deployed demos by the end.
Who it's for: UG/PG students (B.Tech/BCA/MCA/B.Sc/MBA-tech) and fresh graduates aiming for AI/software roles, internships or freelancing. Basic Python helps; we include a refresher.
You leave with
- Prompt LLMs well: few-shot, chain-of-thought, structured JSON output, evaluation
- Write Python that calls LLM APIs (Gemini, plus OpenAI-compatible APIs) securely and cheaply
- Build and deploy RAG apps with embeddings, a vector database, citations and evaluation
- Build tool-using agents with function calling, ReAct, and LangGraph or Google ADK
- Ship a portfolio: 3 deployed apps, clean GitHub repos, README + demo videos
- Be job-ready: AI-assisted (honest) resume, LinkedIn, interview practice, freelancing basics
Assessment & certificate
- 3 quizzes
- Weekly GitHub assignments (mentor-reviewed)
- Milestone demos Week 4 and Week 8 (15% each)
- Capstone 50%
- Participation/peer reviews 20%
- IndMinds Certificate of Completion (75% attendance + all 3 demos). 'With Distinction' for 80% or more overall and a capstone live at a public URL. The certificate links to the student's GitHub portfolio.
Syllabus
A working demo every step.
Open any module to see topics, hands-on labs, the working demo and the deliverable.
Week 4: deployed LLM app (Phase 1)
Week 8: deployed RAG web app with citations and eval scores (Phase 2)
Week 12: portfolio-grade capstone with agent/RAG (final Demo Day)
Example cohorts: Winter cohort Tue 5 Jan 2027 to Demo Day Sat 27 Mar 2027; Summer cohort Tue 4 May 2027 to Demo Day Sat 24 Jul 2027 (timed around semester exams).
- Weekday-evening batch: Tue & Thu 7:30-9:30 PM IST
- Weekend batch: Sat & Sun 10:00 AM-12:00 PM IST
Lab/doubt clinic Wed 8:30-9:30 PM IST; Discord community; 1:1 code review per phase
Phase 1: Foundations
Week 1Gen AI & LLM Fundamentals + Setup
Topics
- How LLMs work: tokens, context window, temperature, top-p
- Model landscape: Gemini, GPT, Claude, Llama/Gemma (open vs closed)
- Prompting basics; where LLMs fail (hallucination, bias)
- Dev setup: VS Code, Python venv, Git & GitHub
Hands-on
- Prompt experiments in Google AI Studio
- Create GitHub account + first repo, commit, push
Working demo: A prompt-comparison notebook published on GitHub
Deliverable: Repo #1 + Quiz 1
Week 2Advanced Prompting & Evaluation
Topics
- Few-shot, role, chain-of-thought, prompt chaining, ReAct preview
- Structured output (JSON schema), system instructions
- Prompt evaluation: test sets, rubrics, LLM-as-judge
- Career corner: how recruiters screen AI resumes
Hands-on
- Build an eval harness for 20 test prompts
- JSON extractor for invoices/resumes
Working demo: CLI tool that turns any job description into structured JSON skills
Deliverable: Prompt library + eval report
Week 3Python for AI + APIs
Topics
- Python refresher: functions, dicts, files, exceptions
- HTTP, REST, requests, JSON
- API keys and secrets: .env, never commit keys, rate limits
- Calling the Gemini API (Python SDK), streaming responses
Hands-on
- Weather/news API mashup
- First Gemini API script with streaming
Working demo: Script that summarizes any news URL using an LLM
Deliverable: Repo #2
Week 4Your First LLM App + Deployment
Topics
- Streamlit/Gradio UIs
- Cost and latency basics; caching
- Deploying to Streamlit Community Cloud / Hugging Face Spaces
- Writing a great README + 60-second demo video
Hands-on
- Build and deploy a resume-bullet improver / cover-letter assistant
Working demo: MILESTONE DEMO 1: a deployed LLM app with a public URL, shown live in class
Deliverable: Phase 1 demo + code review
Phase 2: Build with RAG
Week 5Embeddings, Vector DBs & Semantic Search
Topics
- Embeddings and similarity
- Vector databases: Chroma, FAISS, pgvector (Supabase)
- Chunking strategies, metadata filters
- Semantic vs keyword vs hybrid search
Hands-on
- Semantic search over your college syllabus/notes
Working demo: Search UI that finds the right notes page for a natural-language question
Deliverable: Repo #3 + Quiz 2
Week 6RAG Pipeline End-to-End
Topics
- Retrieve, augment, generate; grounding and citations
- PDF parsing, OCR basics, multilingual (Indian-language and global) documents
- Prompt templates for RAG; 'I don't know' behaviour
- Frameworks: LangChain/LlamaIndex vs plain Python
Hands-on
- Chat-with-PDF app with page citations
Working demo: RAG chatbot answering from 3 PDFs with page-level citations
Deliverable: RAG app v1
Week 7Evaluating & Hardening RAG
Topics
- RAG evaluation: faithfulness, relevance (RAGAS-style metrics)
- Reducing hallucinations; reranking
- Guardrails, prompt injection, PII handling
- Cost/latency optimization
Hands-on
- Eval suite for your RAG app; fix the worst 3 failures
Working demo: Before/after eval scores dashboard
Deliverable: Eval report
Week 8Backend & Production Deployment
Topics
- FastAPI backend, auth basics
- Docker basics
- Deploy to Render/Railway/Google Cloud Run (free tiers)
- Logging and monitoring
Hands-on
- Wrap the RAG app in FastAPI + simple frontend; deploy
Working demo: MILESTONE DEMO 2: a deployed 'chat with your docs' RAG web app with citations and eval scores
Deliverable: Phase 2 demo + code review
Phase 3: Agents & Career
Week 9Function Calling & Agents
Topics
- Tool use / function calling
- ReAct loop, planning, memory
- Frameworks: LangGraph or Google Agent Development Kit (ADK)
- When NOT to use agents
Hands-on
- Agent with 3 tools: web search, calculator, Google Sheets/Calendar
Working demo: An agent completing a multi-step task live (e.g. research and fill a Sheet)
Deliverable: Repo #4 + Quiz 3
Week 10Multi-step Agents, MCP & Responsible AI + Capstone Kickoff
Topics
- Multi-agent patterns, human-in-the-loop
- Model Context Protocol (MCP) intro
- Responsible AI: bias, privacy, licensing, safety
- Capstone scoping: problem, users, architecture, success metric
Hands-on
- Capstone proposal + architecture diagram approved by mentor
Working demo: Capstone skeleton deployed (hello-world end-to-end)
Deliverable: Capstone spec
Week 11AI for Careers + Capstone Build
Topics
- AI-assisted resume and LinkedIn, done honestly (no fabricated experience)
- GitHub profile README, pinned repos, portfolio site
- Mock technical interview: LLM/RAG system-design questions; HR round
- Freelancing/internship hunting: Internshala, LinkedIn, Upwork basics
Hands-on
- Resume + LinkedIn review; mock interview in pairs
- Capstone build sprint with mentor office hours
Working demo: Capstone beta demo to peers (feedback round)
Deliverable: Resume, LinkedIn, portfolio site
Week 12Polish & DEMO DAY
Topics
- Testing, UX polish, README, architecture diagram, 2-minute demo video
- Pitching your project in interviews
Hands-on
- Final deployment + Demo Day
Working demo: FINAL DEMO: a portfolio-grade deployed app presented live
Deliverable: Capstone submission + certificate
Final working demo
Portfolio-Grade Deployed Gen AI App
Solve a real problem with a RAG and/or agent app that is deployed at a public URL. Examples: placement-prep interview coach grounded on company JDs; multilingual farmer advisory bot grounded on government scheme PDFs; college notes tutor with quizzes; small-business WhatsApp/web order assistant; AI video-script generator. Must include: a public deployed URL, a GitHub repo with a clean README (problem, architecture diagram, setup, eval results), a 2-minute demo video, basic evaluation, and no secrets in the repo.
Format: Live online Demo Day: 5-minute pitch + live demo + 3-minute Q&A from the panel (instructor + invited industry/recruiter guests). Best projects featured on indminds.com and LinkedIn (with the student's consent).
- Works end-to-end at a public URL 30%
- Technical depth (RAG/agent quality, eval) 25%
- Code quality and README 15%
- Real-world usefulness 15%
- Presentation 15%
Fees & enrolment
Fees. Enrol in one message.
Next batch: Winter cohort 2027 (Tue & Thu 7:30-9:30 PM IST), Tue 5 Jan 2027 → Demo Day Sat 27 Mar 2027 (example dates: confirm before launch).
EMI: 3 monthly instalments
3 × ₹5,500
₹5,500 now, then 2 monthly payment links
Book your seat
₹1,000 now, ₹13,999 later
₹1,000 now (adjusted against the fee); balance due 7 days before the batch starts
Prices are plus GST as applicable. All fees are non-refundable (policy).
| Option | Amount |
|---|---|
| Full payment (suggested)Standard | ₹14,999 |
| Early-bird (14+ days before start)First 10 seats | ₹12,999 |
| EMI: 3 monthly instalmentsVia Razorpay EMI/cardless EMI or a direct auto-debit schedule | ₹5,500 x 3 (₹16,500) |
| Group of 3+ friends10% off | ₹13,499 per student |
| College bootcamp (20+ students, invoiced to the college/TPO)Offline/hybrid at campus | ₹9,999 per student |
- Registration: ₹1,000 seat-booking (non-refundable, adjusted against the fee)
- Tools: Labs use free tiers (Gemini API via Google AI Studio, free deployment tiers). No paid API spend is required.
- Group, corporate and early-bird options are arranged on request: write to us.
Before you join
- College student or recent graduate
- Basic programming in any language (Python refresher included)
- Laptop that can run VS Code and Python
What you need
- Laptop (8 GB RAM recommended), Chrome, VS Code, Python 3.11+
- GitHub account
- Google AI Studio (free Gemini API key)
- Free deployment tiers: Streamlit Community Cloud / Hugging Face Spaces / Render / Cloud Run
- Optional: Supabase (pgvector), Docker
FAQ
Questions, answered.
Do I need to know Python?
Basics help. Week 3 includes a refresher, and pre-course videos are shared on enrolment.
Will I have to pay for APIs?
No. Labs use free tiers. Paid usage is optional.
Is there a placement guarantee?
No. We give you a deployed portfolio, resume/LinkedIn review and mock interviews, but we don't promise jobs.
EMI available?
Yes: 3 x ₹5,500.
Can my college host this?
Yes. There's a campus bootcamp rate for 20+ students, invoiced to the college.
Refunds?
All fees are non-refundable once paid (no refunds for missed sessions, change of mind or partial attendance).
Is GST included?
Prices are shown plus GST as applicable.