For Working Professionals & Leaders · 20% OFF TILL DEC 2026 · SAVE ₹5,000 · INCL. GST
GAIL Certification + Applied GenAI, RAG & Agentic AI Engineering (4-Month Master Track)
20% OFF Launch Offer till Dec 2026: ₹20,000 (incl. GST · Regular ₹25,000). Master Google Cloud GAIL Certification AND build 3 deployed Python, RAG & Multi-Agent AI apps in 16 weeks (80 live hours).
Duration
4 months (16 weeks), 64 live hours + 16 hours lab & exam clinic (80 hours total)
Format
2 × 2 h live classes + 1 h Wednesday lab clinic per week (IST)
Batch size
15-25 learners per cohort for personal code reviews and architecture feedback
Live hours
64 hours live + 16 hours lab/exam clinic (80 hours total)
Our flagship 16-week (4-month, 80-hour) integrated track combining complete Google Cloud Generative AI Leader (GAIL) Certification Prep with deep hands-on Python, Production RAG, Vector Databases, FastAPI/Docker & Multi-Agent AI Engineering. Flat 20% off till December 2026 (₹20,000 incl. GST vs ₹25,000 regular).
Independent certification prep, not official Google training. Independent certification prep + hands-on AI engineering programme by IndMinds. Not affiliated with, endorsed by, or sponsored by Google Cloud. The USD 99 Google Cloud exam registration fee is paid separately to Google.
Who it's for: Working IT professionals, software engineers, tech leads, solution architects, and ambitious final-year students/graduates who want BOTH the official Google Cloud Generative AI Leader (GAIL) certification preparation AND deep hands-on Python, RAG, Vector DB, FastAPI/Docker & Multi-Agent production engineering.
You leave with
- Pass-ready mastery of all 5 Official Google Cloud GAIL Modules and 4 Exam Domains (~30% / ~35% / ~20% / ~15%), verified through 8 domain quizzes and two full 55-question timed mock exams
- Write production Python for LLM APIs (Gemini, OpenAI/Claude compatible), structured JSON outputs (Pydantic), streaming, retries, and token cost control
- Architect and deploy a production RAG application with semantic chunking, vector databases (ChromaDB / pgvector), hybrid search, grounded citations, and automated RAG evaluation
- Build and deploy multi-step AI Agents using function calling, Google ADK / LangGraph, Model Context Protocol (MCP), and Google Cloud Agent Studio / Agent Platform
- Containerize and ship 3 public, portfolio-grade AI applications with FastAPI, Streamlit/Next.js, Docker, and Google Cloud Run
- Deliver a Dual Capstone on Demo Day: (1) an Executive Enterprise GenAI Architecture & SAIF Governance Proposal + (2) a Live Deployed Production RAG & Multi-Agent System, backed by resume/LinkedIn/GitHub review and mock interviews
Assessment & certificate
- 8 GAIL domain quizzes (15 questions each, auto-graded)
- GAIL Domain 1 Checkpoint (Week 4)
- 2 Full Timed GAIL Mock Exams (Week 9 & Week 13 — 55 scenario questions in 90 minutes each)
- 3 Deployed Engineering Milestones (Week 4 LLM App, Week 8 RAG App, Week 12 Multi-Agent App)
- Final Dual Capstone (Week 16 Demo Day)
- IndMinds Dual Master Certificate in 'Generative AI Leadership (GAIL Prep) & Applied GenAI Engineering' (requires 75%+ attendance, 3 deployed apps, 75%+ on Mock Exam 2, and Dual Capstone presentation). 'With Distinction' awarded for 80%+ on Mock Exam 2 and a live production URL. The official Google Cloud Generative AI Leader certification is awarded by Google upon passing the proctored exam.
Complete Protected Curriculum
A working demo every step.
Open any module to see topics, hands-on labs, the working demo and the deliverable.
Week 4 (Month 1 End): Milestone Demo #1 — Deployed Python LLM App with Structured JSON & Prompt Evaluation + GAIL Domain 1 Checkpoint
Week 8 (Month 2 End): Milestone Demo #2 — Deployed Production RAG Web App with Citations & Eval Harness
Week 9 & Week 13: Two Full 55-Question, 90-Minute Timed GAIL Mock Exams
Week 12 (Month 3 End): Milestone Demo #3 — Containerized Multi-Agent System (LangGraph / Google ADK + FastAPI + Cloud Run)
Week 16 (Month 4 End): Final Dual Capstone Demo Day — Executive Enterprise GenAI Proposal + Live Production Agent/RAG System + GAIL Exam Slot Booking
16 weeks (4 months): Month 1 (Weeks 1-4) GenAI Foundations, Prompt Engineering & Python LLM App -> Month 2 (Weeks 5-8) Google Cloud GenAI Offerings, Vector DBs & Production RAG -> Month 3 (Weeks 9-12) Agent Studio, LangGraph/ADK Multi-Agents, FastAPI/Docker & GAIL Mock Exam 1 -> Month 4 (Weeks 13-16) Enterprise Strategy, SAIF Security, GAIL Mock Exam 2, Career Prep & Dual Capstone Demo Day.
- Weekend Track: Sat & Sun 10:00 AM-12:00 PM IST + Wed 8:00-9:00 PM IST Lab/Exam Clinic
- Weekday Evening Track: Tue & Thu 8:00-10:00 PM IST + Sat 11:00 AM-12:00 PM IST Lab/Exam Clinic
Weekly 1-hour Lab & Exam Clinic + Discord/WhatsApp community + 1:1 code & architecture review per month
Month 1: GenAI Foundations & Prompt Engineering
Week 1GAIL Module 1 & Modern LLM Architecture
Topics
- AI vs ML vs Deep Learning vs Generative AI; why foundation models changed software engineering
- How LLMs work: tokens, embeddings, context windows, pre-training, RLHF, multimodal models
- Data lifecycle, structured vs unstructured data, labeled vs unlabeled data
- ML training paradigms: supervised, unsupervised, reinforcement learning
- Hallucinations, latency, token economics, and when NOT to use an LLM
Hands-on
- Lab 1: Explore Google AI Studio & Gemini 2.5; benchmark 3 prompts across text, image, and PDF inputs
- Build a 5-case hallucination & failure-mode stress test
Working demo: Live walkthrough of your 5-case LLM stress test showing where raw models succeed vs hallucinate
Deliverable: GitHub setup + Hallucination audit report + GAIL Quiz 1 · Exam domains: 1 Fundamentals (1.1, 1.2) · Google learning-path: GAIL Module 1
Week 2GAIL Module 2 & Advanced Prompt Engineering + Eval
Topics
- Google's foundation model landscape: Gemini (Nano, Flash, Pro, Ultra), Gemma open weights, Imagen, Veo, Chirp, Lyria
- Model selection trade-offs: context size, cost, latency, privacy, edge (LiteRT) vs cloud
- Zero-shot, few-shot, role prompting, Chain-of-Thought, ReAct, and prompt chaining
- Sampling parameters: temperature, top-p, top-k, max output tokens, safety filters, system instructions
- Building a 20-case golden evaluation set to score prompts objectively
Hands-on
- Lab 2: Official Google AI Studio Parameter Playground lab (temperature 0 vs 1 vs 2) + build a 10-template prompt library
- Run a 20-case evaluation table comparing v1 vs v2 prompts
Working demo: Live side-by-side parameter demo + structured prompt evaluation scorecard
Deliverable: Prompt library + 20-case eval sheet + GAIL Quiz 2 · Exam domains: 1 Fundamentals (1.2, 1.3); 3 Techniques (3.2) · Google learning-path: GAIL Module 2 & Module 4
Week 3Python for AI Engineers, Async APIs & Structured JSON
Topics
- Fast-track Python 3.11+ for AI: virtual environments, typing, async/await, httpx, environment variables
- Calling Gemini & OpenAI-compatible APIs from Python: multi-turn chat, system prompts, streaming tokens
- Guaranteed structured outputs using Pydantic schemas and JSON mode
- Production resilience: exponential backoff retries, rate-limit handling, token counters, and cost logging
Hands-on
- Lab 3: Build a CLI & Python module that extracts structured JSON (Pydantic) from messy invoices, resumes, or meeting notes with 100% schema validity
Working demo: Run the Python JSON extractor live on 3 unseen messy documents with real-time token and cost logging
Deliverable: GitHub repo: Python LLM & Structured Output toolkit · Exam domains: 3 Techniques (3.2) · Google learning-path: Practical Engineering I
Week 4GAIL Module 3 (AI Layers & Responsible AI) + MILESTONE 1 DEPLOYED APP
Topics
- The 5 layers of an enterprise GenAI stack: Infrastructure (TPUs/GPUs), Models, Platform (Agent Platform / Vertex AI), Agents, Applications (Workspace / Gemini Enterprise)
- Responsible AI & Google's Secure AI Framework (SAIF): fairness, bias, privacy, explainability, human-in-the-loop
- Building & deploying web UIs for AI in Python (Streamlit / Gradio) to a public URL
Hands-on
- Lab 4: GAIL Domain 1 Checkpoint Quiz (25 questions) + Build and deploy Milestone App #1 (Deployed LLM Web App with streaming, JSON export, and guardrails)
Working demo: MILESTONE DEMO 1: Every learner demos their live deployed LLM web app at a public URL
Deliverable: Public URL #1 + GitHub repo + GAIL Domain 1 Checkpoint Score · Exam domains: 1 Fundamentals (1.4); 4 Strategy (4.3) · Google learning-path: GAIL Module 3
Month 2: Cloud Offerings, Vector DBs & Production RAG
Week 5GAIL Module 4 (I): Gemini Workspace, Gems & NotebookLM Enterprise
Topics
- Google Workspace with Gemini across Gmail, Docs, Sheets, Slides, Meet, and Vids
- Building custom Gems for repeatable team workflows
- Gemini Enterprise & Gemini Notebook (NotebookLM Enterprise) for multi-document grounding and synthesis
- Agent Platform (Vertex AI) vs Google AI Studio: decision matrix for enterprise architects
Hands-on
- Lab 5: Build 2 role-specific Gems + ground Gemini Notebook on a 10-document policy/research corpus
Working demo: Live demo of custom Gems + Gemini Notebook answering cited cross-document questions
Deliverable: Enterprise tool-selection matrix + Gem configs + GAIL Quiz 3 · Exam domains: 2 Offerings (2.1, 2.2) · Google learning-path: GAIL Module 4
Week 6Embeddings, Semantic Search & Vector Databases (Theory + Python)
Topics
- How text & multimodal embeddings work: cosine similarity, dot product, dimensionality, and domain drift
- Document ingestion pipeline: PDF/Markdown/HTML parsing, fixed vs recursive vs semantic chunking, overlap & metadata tags
- Vector databases in practice: ChromaDB (local/persistent) and Postgres pgvector (Supabase)
- When semantic search fails on exact keywords/SKUs and how hybrid search (BM25 + dense vectors) fixes it
Hands-on
- Lab 6: Ingest 30+ pages of real PDFs in Python, generate Gemini embeddings, index into ChromaDB, and benchmark 3 chunking strategies
Working demo: Live notebook/script showing top-k retrieved chunks and similarity scores for 5 tricky queries
Deliverable: Ingestion & vector search pipeline in GitHub + GAIL Quiz 4 · Exam domains: 3 Techniques (3.3) · Google learning-path: GAIL Module 4 (III) + Engineering II
Week 7End-to-End RAG Architecture: Citations, Re-Ranking & Eval
Topics
- The complete RAG loop: Retrieve -> Re-rank -> Augment -> Generate with strict source citations
- Google Cloud grounding offerings: Agent Search (Vertex AI Search), RAG APIs, Grounding with Google Search
- Preventing hallucinations: strict 'Answer ONLY from context or say I don't know' prompts + citation verification
- Evaluating RAG systems: context precision/recall, faithfulness, answer relevance, and prompt-injection defense
Hands-on
- Lab 7: Build both a no-code grounded RAG agent in Google AI Studio/Agent Search AND a full custom Python RAG pipeline with inline [Doc, Page] citations and a 20-question eval script
Working demo: Ask your Python RAG engine 3 in-scope questions (returns cited answers) and 2 out-of-scope/adversarial questions (cleanly refuses)
Deliverable: Evaluated RAG engine + 20-question accuracy scorecard + GAIL Quiz 5 · Exam domains: 2 Offerings (2.4); 3 Techniques (3.3) · Google learning-path: GAIL Module 4 (III) + Engineering II
Week 8FastAPI + Docker + Cloud Deployment & MILESTONE 2 RAG APP
Topics
- Turning Python AI scripts into production REST APIs with FastAPI: Pydantic request/response models, async streaming endpoints, CORS, API key auth
- Containerizing AI backends with Docker (`Dockerfile`, `.dockerignore`, multi-stage builds)
- Deploying to Google Cloud Run / Render / Hugging Face Spaces with environment secrets and persistent vector storage
Hands-on
- Lab 8: Wrap your RAG pipeline in FastAPI + UI, containerize with Docker, and deploy to a public cloud URL
Working demo: MILESTONE DEMO 2: Live demo of your publicly deployed RAG web app uploading a new PDF and answering with citations
Deliverable: Public URL #2 (Deployed RAG App) + Swagger `/docs` endpoint + GitHub repo · Exam domains: 2 Offerings (2.1, 2.4) · Google learning-path: Engineering II
Month 3: AI Agents, Cloud APIs & GAIL Mock Exam 1
Week 9Customer Engagement Suite, Pre-Built Cloud AI APIs & GAIL MOCK EXAM 1
Topics
- Google Cloud Customer Engagement Suite: Conversational Agents, Agent Assist, Conversational Insights, CCaaS
- Pre-built Google Cloud AI APIs: Document AI, Speech-to-Text, Text-to-Speech, Translation, Vision, Video Intelligence, Natural Language
- Selecting pre-built APIs vs RAG vs fine-tuning for enterprise RFPs
Hands-on
- Lab 9: Architect an omnichannel customer support workflow combining Document AI, Translation, and Conversational Agents
- GAIL MOCK EXAM 1: Full 55-question, 90-minute timed exam weighted across all 4 domains (17/19/11/8 split)
Working demo: Live walkthrough of your CX architecture flow + domain-by-domain review of Mock Exam 1
Deliverable: GAIL Mock Exam 1 Score Report + Personal Domain Remediation Plan · Exam domains: 2 Offerings (2.3, 2.5) · Google learning-path: GAIL Modules 4-5
Week 10GAIL Module 5 (I): Agent Architecture & Tool Calling in Python
Topics
- What makes an AI Agent: reasoning loop (ReAct), memory, planning, and external tools
- Deterministic vs generative vs hybrid agents; extensions, functions, data stores, and plugins
- Implementing Function Calling / Tool Use in Python: defining JSON tool schemas, executing Python tools safely, and feeding tool outputs back to the model
Hands-on
- Lab 10: Official Google 'Build your own agent' lab in AI Studio + Build a Python agent with 3 live tools (SQL/CSV query tool, web/RAG lookup tool, and calculator/calendar tool)
Working demo: Live demo of your Python agent chaining 2+ tool calls to solve a multi-step user request
Deliverable: Multi-tool Python Agent repo + GAIL Quiz 6 · Exam domains: 2 Offerings (2.4, 2.5) · Google learning-path: GAIL Module 5 + Engineering III
Week 11Multi-Agent Systems: LangGraph, Google ADK & Model Context Protocol (MCP)
Topics
- Stateful agent workflows and multi-agent orchestration (Router, Researcher, Coder/Analyst, Critic/Verifier)
- Building production agent graphs with LangGraph / Google Agent Development Kit (ADK)
- Model Context Protocol (MCP): connecting agents to standardized data sources and enterprise tools
- Human-in-the-loop approval gates, max-step budgets, and tool-error recovery
Hands-on
- Lab 11: Build a 3-node multi-agent workflow (Planner -> RAG/Tool Executor -> Critic) with a human-approval checkpoint
Working demo: Live trace walkthrough showing state transitions, tool calls, and critic self-correction on a complex task
Deliverable: LangGraph / ADK Multi-Agent repository + GAIL Quiz 7 · Exam domains: 2 Offerings (2.4) · Google learning-path: Engineering III
Week 12GAIL Module 5 (II): Enterprise Agent Platform, MLOps & MILESTONE 3 AGENT
Topics
- Gemini Enterprise Agent Platform (Vertex AI): Model Garden, Model Builder, AutoML, Agent Builder, Agent Search
- MLOps for GenAI: Model Registry, versioning, evaluation pipelines, drift & performance monitoring, Feature Store
- Fine-tuning options (supervised tuning, RLHF, distillation, LoRA) vs RAG: cost and maintenance trade-offs
Hands-on
- Lab 12: Deploy your Multi-Agent + RAG workflow as Milestone App #3 + complete GAIL Quiz 8
Working demo: MILESTONE DEMO 3: Live demonstration of your deployed Multi-Agent application with tool calling and trace logging
Deliverable: Public URL #3 (Deployed Agent App) + Production MLOps Checklist + GAIL Quiz 8 · Exam domains: 2 Offerings (2.1, 2.4); 3 Techniques (3.1) · Google learning-path: GAIL Module 5
Month 4: Enterprise Strategy, GAIL Exam Mastery & Dual Capstone
Week 13Business Strategy, ROI Modelling, SAIF Security & GAIL MOCK EXAM 2
Topics
- Executive GenAI selection framework: scale, customization, latency, privacy, connectivity, and build-vs-buy TCO
- Top-down + bottom-up transformation strategy, change management, and KPI/ROI calculation
- Secure AI in depth: Google SAIF, IAM least privilege, VPC Service Controls, Security Command Center, data residency & DLP
Hands-on
- Lab 13: Conduct a full SAIF security & ROI audit on your Capstone architecture
- GAIL MOCK EXAM 2: Fresh 55-question, 90-minute timed exam under strict exam conditions (target 80%+)
Working demo: Live presentation of your Capstone ROI & SAIF risk model + Mock Exam 2 deep-dive review
Deliverable: GAIL Mock Exam 2 Score Report (80%+ target) + SAIF Audit Document · Exam domains: 4 Business Strategy (4.1, 4.2, 4.3) · Google learning-path: GAIL Modules 1 & 5
Week 14Dual Capstone Build Sprint: Architecture, Code & Evaluation
Topics
- Scoping a high-impact Dual Capstone that satisfies both hiring managers and enterprise architecture panels
- End-to-end engineering sprint: combining FastAPI, Vector DB/RAG, Multi-Agent tools, UI polish, and automated eval suite
- Writing the 6-page Executive GenAI Proposal (business case, Google Cloud architecture diagram, model/RAG choices, SAIF security, and 12-month ROI)
Hands-on
- Lab 14: 1:1 mentor architecture & code review; deploy Capstone beta and run 25-test evaluation harness
Working demo: Capstone Beta Demo in breakout rooms with peer & instructor red-team testing
Deliverable: Deployed Capstone Beta + 6-Page Executive Proposal Draft · Exam domains: All 4 Domains · Google learning-path: Capstone Sprint
Week 15AI Career Accelerator (Resume, GitHub, System Design Interviews) & GAIL Exam Booking
Topics
- Structuring an AI Engineer / GenAI Leader resume and LinkedIn profile around 3 deployed URLs and quantified eval metrics
- GitHub portfolio makeover: pinned repositories, architecture diagrams, 2-minute Loom/video demos, clean READMEs
- Mock Technical & Leadership Interviews: LLM/RAG system-design scenarios + GAIL situational business questions
- Step-by-step official Google Cloud GAIL Exam registration walkthrough (online-proctored vs Pearson VUE test centre)
Hands-on
- Lab 15: Live paired mock interviews (1 technical RAG/Agent system design + 1 executive GAIL scenario) + book your official Google Cloud GAIL exam slot
Working demo: Live 5-minute interview pitch of your portfolio + confirmed GAIL exam readiness sign-off
Deliverable: Polished Resume, LinkedIn, GitHub Portfolio + GAIL Exam Registration · Exam domains: All 4 Domains · Google learning-path: Career & Exam Prep
Week 16Final Exam Cram Clinic & DUAL CAPSTONE DEMO DAY
Topics
- Rapid-fire 60-minute GAIL exam cram: high-frequency exam traps, Google Cloud product naming cheatsheet, time-management strategy for 50-60 questions in 90 minutes
- Production launch checklist: logging, error boundaries, README, and demo script
- Grand Finale Dual Capstone Demo Day in front of instructors and invited industry guests
Hands-on
- Final Dual Capstone Presentation: 5-minute Executive Proposal pitch + 5-minute live deployed RAG/Agent demo + 4-minute panel Q&A
Working demo: FINAL DUAL CAPSTONE DEMO: Live pitch of the Enterprise GenAI Proposal + live full-stack RAG & Multi-Agent application at a public URL
Deliverable: Dual Capstone Submission + IndMinds Dual Master Track Certificate (with Distinction at 80%+) · Exam domains: All 4 Domains · Google learning-path: All Modules
Final working demo
Dual Master Capstone: Executive Enterprise GenAI Proposal + Deployed Production RAG & Multi-Agent System
Every graduate ships a two-part flagship capstone: (1) A 6-8 page Executive Architecture & Business Proposal mapped to Google Cloud's GAIL framework (use case, KPI/ROI model, Google Cloud solution layer, model trade-offs, grounding design, SAIF security & Responsible AI rollout), AND (2) A live, publicly deployed full-stack RAG & Multi-Agent application in Python (FastAPI + Vector DB + LangGraph/ADK + Docker/Cloud Run) with a clean GitHub repository, architecture diagram, evaluation scorecard, and 2-minute demo video.
Format: Live online Demo Day (Week 16): 5-minute executive proposal pitch + 5-minute live software demo + 4-minute Q&A from the review panel. Recorded with LinkedIn-ready portfolio clips.
- Live End-to-End Deployed Application (RAG + Agent + UI at a public URL) 30%
- Technical Engineering Depth (Retrieval accuracy, tool-calling reliability, evaluation harness, clean code) 25%
- Executive Business Case, ROI & Google Cloud Architecture Alignment 20%
- SAIF Security, Guardrails & Responsible AI Governance 15%
- Demo Day Pitch & GitHub Documentation 10%
About the Google Cloud exam (taken separately)
- Length
- 90 minutes
- Format
- 50-60 multiple-choice questions
- Registration fee
- USD 99 (plus tax where applicable), paid directly to Google Cloud when registering; NOT included in the course fee
- Languages
- English, Japanese, Spanish, Portuguese
- Delivery
- Online-proctored or onsite-proctored (test centre: search 'Google Cloud' in the Pearson VUE locator)
- Prerequisites
- None required by Google; Python basics taught from scratch in Phase 1
- Validity
- 3 years
- Renewal
- Renewal exam available within the renewal eligibility period (see Renewal FAQs on the certification page)
Google's page does not give a passing score or retake policy, so we don't state one.
Direct Batch Selection & Instant Razorpay Enrolment
Select your live batch slot & register online (incl. GST).
Next open cohort: 4-Month Master Track — Weekend Batch (Sat & Sun 10:00 AM–12:00 PM IST + Wed Lab) (Starts Sat 7 Nov 2026 · 16 Weeks (4 Months)). All prices include GST.
20% Launch Offer (Valid till Dec 2026 · incl. GST)
₹20,000 (incl. GST)
Flat 20% off regular ₹25,000 fee · All-inclusive of GST · Full 4-month (80h) GAIL + Applied GenAI & Agentic AI Master Track.
Standard Full Programme Fee (Regular ₹25,000 · incl. GST)
₹25,000 (incl. GST)
Standard fee after December 2026 · All-inclusive of GST.
Prices are inclusive of GST. All fees are non-refundable (policy).
| Option | Amount |
|---|---|
| Standard Dual Master Track (full payment)Save ₹5,000 (combines ₹15,000 GAIL Prep + ₹15,000 Practical GenAI Engineering) | ₹25,000 |
| Early-bird (first 10 seats / 14+ days before start)Save ₹7,500 off the combined standalone fees | ₹22,500 |
| 2 Instalments50% at enrolment, 50% at Week 7 | ₹13,000 + ₹13,000 (₹26,000) |
| 3 Monthly EMIsPaid before Months 1, 2 and 3 | ₹8,750 x 3 (₹26,250) |
| Corporate / Group of 3+GST invoice issued to company or group | ₹21,500 per learner |
- Registration: ₹1,000 seat reservation (adjusted in full against tuition)
- Exam fee: USD 99 + tax, paid directly to Google Cloud when booking your exam in Week 15-16. Not included.
- Group, corporate and early-bird options are arranged on request: write to us.
Regular ₹25,000 → ₹20,000 (incl. GST) till Dec 2026 · Saves ₹10,000 vs ₹30k separate
Step 1 · Select Your Live Batch Slot
2 live slots openStep 2 · Register & Pay Instantly (incl. GST)
Before you join
- Open to IT professionals, engineers, tech leads, managers, and final-year college students / fresh graduates
- Basic familiarity with any programming language is helpful (Week 3 includes a complete hands-on Python for AI refresher from scratch)
- A laptop (8 GB+ RAM recommended) with Chrome, VS Code, Python 3.11+, and a free Google account
What you need
- Laptop (Windows, Mac, or Linux) with 8 GB+ RAM, Chrome, VS Code, Python 3.11+, and Git
- Google Account (Gemini, Google AI Studio, NotebookLM, Google Cloud free trial for Agent Studio / Cloud Run)
- Open-source & free-tier engineering stack: FastAPI, Pydantic, ChromaDB / Supabase pgvector, LangGraph / Google ADK, Streamlit, Docker
- GitHub account for portfolio repositories
Where to go next
- Official Google Cloud Generative AI Leader Certification Exam (booked in Week 15-16)
- Google Cloud Professional Machine Learning Engineer or Cloud Architect track
- IndMinds Custom Enterprise AI Consulting & Partner Referrals
FAQ
Questions, answered.
Why choose this 4-Month Rs 25,000 Combined Track over the standalone Rs 15,000 courses?
Taking standalone GAIL Certification Prep (₹15,000) and standalone Practical GenAI Engineering (₹15,000) separately costs ₹30,000 across 24 weeks. This integrated 16-week (4-month) Master Track gives you 100% of both curricula—full Google Cloud GAIL exam mastery PLUS 3 deployed Python/RAG/Agent production apps—for ₹25,000, saving you ₹5,000 and 8 weeks.
Do I need prior Python or AI experience?
No prior AI experience is required. Weeks 1-2 start from foundational GenAI concepts and prompt engineering, and Week 3 teaches Python for AI APIs from the ground up with copy-paste starter templates and weekly lab clinics.
Is the USD 99 Google Cloud GAIL exam fee included?
No. Google Cloud charges USD 99 (plus applicable tax) directly when you register for the official exam on Google's certification portal. We guide you through registration step-by-step in Week 15 after you score 80%+ on Mock Exam 2.
Can I pay in instalments or EMI?
Yes. You can pay in 2 instalments of ₹13,000 each (at enrolment and Week 7) or 3 monthly EMIs of ₹8,750 each.
What if I start in the Rs 15,000 GAIL or College track and want to upgrade?
You can upgrade to the 4-Month Dual Master Track anytime within the first 4 weeks by paying only the ₹10,000 difference.
Refunds?
All fees are non-refundable once paid (no refunds for missed sessions, change of mind or partial attendance).
Is GST included in the listed fee?
Yes — all listed course fees are 100% inclusive of GST. There are no extra taxes added at checkout.