Working professionals
Generative AI Leader Certification Prep (Google Cloud)
12 weeks of live, lab-heavy prep for Google Cloud's Generative AI Leader exam, with a working demo every week and a capstone agent/RAG demo.
Duration
12 weeks (3 months)
Format
2 × 2 h live per week · Sat & Sun or Tue & Thu evenings
Batch size
15-25 learners
Live hours
48 hours live + ~3-4 hours/week self-study and labs
Independent certification prep for IT professionals, team leads and managers. Covers all four exam domains with weekly labs in Gemini, Gemini Notebook, Google AI Studio and Agent Studio, 8 quizzes and 2 full mock exams. No coding needed.
Independent certification prep, not official Google training. IndMinds runs this as independent certification prep. It is not official Google training, and IndMinds is not affiliated with or endorsed by Google. You pay the exam fee (USD 99 plus tax, per Google's certification page) to Google Cloud yourself. It is not included in the course fee.
Who it's for: Working IT professionals, team leads, managers, pre-sales, consultants and business analysts who want the Google Cloud Generative AI Leader certification. No coding needed.
You leave with
- Explain the core gen AI ideas the exam tests: AI/ML/DL, foundation models, LLMs, multimodal and diffusion models, ML approaches and the ML lifecycle
- Match Google Cloud gen AI offerings to business needs: Gemini app/Gems, Gemini Enterprise, Workspace with Gemini, Gemini Notebook (NotebookLM), Agent Platform (formerly Vertex AI), Model Garden, Agent Search, Customer Engagement Suite and pre-built AI APIs
- Use prompting techniques (zero/one/few-shot, role, chaining, CoT, ReAct), sampling parameters, grounding and RAG to improve model output
- Build a working Gemini agent with grounding/RAG in Google AI Studio or Agent Studio without writing code
- Write a gen AI business proposal covering use-case selection, model choice, secure AI (SAIF, IAM), responsible AI, privacy and ROI measurement
- Score 80% or more on two full-length timed mock exams, then register for and sit the real exam
Assessment & certificate
- 8 weekly quizzes (15 questions each, auto-graded)
- Domain 1 checkpoint (Week 4)
- Mock Exam 1 (Week 8) and Mock Exam 2 (Week 11), 55 original questions in 90 minutes, weighted by domain
- Weekly working demos
- Capstone (rubric above)
- IndMinds Certificate of Completion (attend 75% or more, submit the capstone, score 70% or more on Mock 2). The Google Cloud certification itself is awarded only by Google after you pass the official exam.
Syllabus
A working demo every step.
Open any module to see topics, hands-on labs, the working demo and the deliverable.
A working demo every week (see each week)
Week 4: Domain 1 checkpoint + landscape-map demo
Week 8: Mock Exam 1 + live CX journey demo
Week 11: Mock Exam 2 + capstone dry run
Week 12: final capstone, a business proposal + live agent/RAG demo
Example cohort: starts Sat 7 Nov 2026, Mock 1 in Week 8, Mock 2 in Week 11, Capstone Demo Day Sun 24 Jan 2027 (weekend batch). Learners should book their exam for Weeks 13-15.
- Weekend batch: Sat & Sun 10:00 AM-12:00 PM IST
- Weekday-evening batch: Tue & Thu 8:00-10:00 PM IST
Optional 30-min doubt clinic Wed 9:00 PM IST; WhatsApp/Discord study group
Week 1Orientation + Module 1: Gen AI, Beyond the Chatbot
Topics
- How the exam works: format, 4 domains and weightings, and the rebranded product names (Agent Platform, Agent Studio, Agent Search, Gemini Notebook)
- The four ways to use gen AI: create, summarize, discover, automate
- Gen AI vs traditional AI; where gen AI creates business value
- Gemini app basics; choosing work tasks for gen AI
Hands-on
- Lab 1: Gemini app: create, summarize, discover and automate one real work task each
- Set up a Gemini Notebook (NotebookLM) with the official study guide, as the study guide itself recommends
Working demo: Each learner shows a Gemini Notebook built on the exam guide answering 3 exam-style questions with citations, plus one real work task done 4 ways
Deliverable: Personal 'gen AI opportunity log' with 5 use cases from your own job; Quiz 1 · Exam domains: 1 Fundamentals (1.1 use cases); 4 Business strategy (4.1) · Google learning-path: Module 1
Week 2Module 2: Unlock Foundational Concepts (I): AI, ML and data
Topics
- AI vs ML vs deep learning vs gen AI; NLP
- Supervised, unsupervised and reinforcement learning
- Structured vs unstructured data, labelled vs unlabelled data, data quality and accessibility
- The ML lifecycle (ingest, prepare, train, deploy, manage) and the Google Cloud tools for each stage
Hands-on
- Lab 2: sort 20 real business datasets into structured/unstructured and labelled/unlabelled, then pick an ML approach for each
- Map an end-to-end ML lifecycle for an Indian use case (e.g. bank KYC document processing)
Working demo: A Gemini Gem ('ML Concept Coach') that quizzes you on Domain 1 terms, demoed live
Deliverable: ML lifecycle one-page diagram; Quiz 2 · Exam domains: 1 Fundamentals (1.1, 1.2) · Google learning-path: Module 2
Week 3Module 2: Unlock Foundational Concepts (II): foundation models and their limits
Topics
- Foundation models, LLMs, multimodal and diffusion models, prompt tuning, fine-tuning
- Choosing a foundation model: modality, context window, security, availability and reliability, cost, performance, customization
- Limits: data dependency, knowledge cutoff, bias, fairness, hallucinations, edge cases
- Fixes: grounding, RAG, prompt engineering, fine-tuning, human in the loop (official 'Summary of techniques' handout)
Hands-on
- Lab 3: Google AI Studio: make Gemini hallucinate on a post-cutoff question, then fix it with grounding
- Model-selection worksheet for 3 business cases
Working demo: Before/after demo: the same prompt without and with Grounding with Google Search in AI Studio
Deliverable: Model-selection matrix; Quiz 3 · Exam domains: 1 Fundamentals (1.1); 3 Techniques (3.1) · Google learning-path: Module 2
Week 4Module 3: Navigate the Landscape
Topics
- The 5 layers: infrastructure, models, platforms, agents, applications
- Google models: Gemini, Gemma, Imagen / Nano Banana, Veo; first-party, open and third-party models in Model Garden
- AI-optimized infrastructure: TPUs, GPUs, AI Hypercomputer; Google's open approach and enterprise readiness
- AI at the edge: LiteRT, Gemini Nano
Hands-on
- Lab 4: tour Model Garden and compare 3 models (first-party, open, third-party) for one use case
- Generate an image and a short storyboard with Google's image/video models where available
Working demo: A 3-minute 'landscape map' walkthrough placing your company's AI tools into the 5 layers
Deliverable: Landscape map; Domain 1 checkpoint test (25 questions, timed) · Exam domains: 1 Fundamentals (1.3, 1.4); 2 Offerings (2.1) · Google learning-path: Module 3
Week 5Module 4: Gen AI Apps, Transform Your Work (I): productivity
Topics
- Gemini app and Gemini Advanced (Google AI plans); Gems
- Google Workspace with Gemini: Gmail, Docs, Sheets, Slides, Meet, Vids
- Gemini Enterprise: enterprise search, Gemini Notebook API, custom agents
- Gemini Notebook / NotebookLM Enterprise for document understanding
Hands-on
- Lab 5: build 2 Gems for your role (e.g. status-report writer, RFP analyser)
- Workspace with Gemini workflow: summarize a long email thread into a Doc into Slides (use a trial or personal account if work accounts are restricted)
Working demo: Live demo of your Gems running on a real (sanitized) work input
Deliverable: Gem configs + productivity ROI estimate (hours saved per month); Quiz 4 · Exam domains: 2 Offerings (2.2) · Google learning-path: Module 4
Week 6Module 4 (II): Prompt engineering and sampling parameters
Topics
- Zero-, one- and few-shot, role prompting, prompt chaining
- Chain-of-thought, ReAct, metaprompting; reusing prompts, saved info
- Sampling parameters: token count, temperature, top-p, safety settings, output length
- System instructions
Hands-on
- Lab 6: the official 'Parameter playground in Google AI Studio' exercise, extended: same pitch prompt at temperature 0 / 1 / 2 and different top-p values
- Build a prompt library (10 reusable templates) for your team
Working demo: Side-by-side parameter demo plus a few-shot prompt that turns messy notes into structured JSON
Deliverable: Prompt library; Quiz 5 · Exam domains: 3 Techniques (3.2, 3.3 parameters) · Google learning-path: Module 4
Week 7Module 4 (III): Semantic search, vector databases, grounding and RAG
Topics
- Semantic search and embeddings; vector databases
- Grounding with first-party enterprise data, third-party data and world data
- RAG steps: retrieve, augment, generate, iterate
- Google grounding offerings: pre-built RAG with Agent Search, RAG APIs, Grounding with Google Search
- Transparency and trust (Google Cloud transparency resources)
Hands-on
- Lab 7: official 'RAG in action' try-it (Grounding with Google Search) in AI Studio
- Build a no-code RAG assistant over 5-10 company policy PDFs (Gemini Notebook, then an Agent Search data store if you have a Cloud trial)
Working demo: A policy Q&A assistant that answers with citations and says 'not found' when the answer isn't in the documents
Deliverable: RAG design canvas (sources, chunking, grounding type, evaluation); Quiz 6 · Exam domains: 3 Techniques (3.3); 2 Offerings (2.4 RAG offerings) · Google learning-path: Module 4
Week 8Customer experience and pre-built AI APIs + MOCK EXAM 1
Topics
- Customer Engagement Suite: Conversational Agents, Agent Assist, Conversational Insights, Contact Center as a Service
- External search: Agent Search, Google Search
- Pre-built APIs: Speech-to-Text, Text-to-Speech, Translation, Document Translation, Document AI, Vision, Video Intelligence, Natural Language; API Library
Hands-on
- Lab 8: design a contact-centre journey that says which API or agent handles each step
- Mock Exam 1: 55 original questions in 90 minutes, weighted by domain (about 17/19/11/8), with a domain-wise score report
Working demo: Your CX journey shown as a clickable flow, with one step running live (e.g. Translation or Speech-to-Text in the console or AI Studio)
Deliverable: Mock 1 score report + personal remediation plan · Exam domains: 2 Offerings (2.3, 2.5) · Google learning-path: Modules 4-5
Week 9Module 5: Gen AI Agents, Transform your Organization (I): agents and tooling
Topics
- What an agent is; parts: model, tools, reasoning loop
- Deterministic, generative and hybrid agents
- Agent tooling: extensions, functions, data stores, plugins
- Agent Studio vs Google AI Studio: when to use which (official comparison handout)
Hands-on
- Lab 9: official 'Build your own agent' try-it: Cymbal Manufacturing support chatbot with system instructions in AI Studio
- Add a data store / grounding to the agent
Working demo: Your support agent handling 5 scripted customer questions live, including one it must refuse or hand off
Deliverable: Agent spec (goal, persona, tools, guardrails, hand-off rules); Quiz 7 · Exam domains: 2 Offerings (2.4, 2.5) · Google learning-path: Module 5
Week 10Module 5 (II): Agent Platform for builders and running models in production
Topics
- Gemini Enterprise Agent Platform (formerly Vertex AI): Model Garden, Model Builder, AutoML, Agent Search, custom agents
- MLOps: Model Registry, versioning, performance tracking, drift monitoring (Model Monitoring), Feature Store, Pipelines, automatic model upgrades, KPIs
- Building apps: Gemini API keys, Cloud Run / Cloud Run functions, Apps Script, AppSheet
- Agent Studio quickstart: send text prompts to Gemini
Hands-on
- Lab 10: generate a Gemini API key and run the official Python quickstart (instructor-guided, copy-paste level)
- Agent Studio quickstart in a Google Cloud free trial project (optional; the instructor demos it for anyone without a trial)
Working demo: Your Week 9 agent called from a 10-line script or Apps Script, showing the same agent reached from code
Deliverable: Production-readiness checklist for your capstone; Quiz 8 · Exam domains: 2 Offerings (2.4, 2.1); 3 Techniques (3.1 monitoring) · Google learning-path: Module 5
Week 11Business strategy, secure AI and responsible AI + MOCK EXAM 2
Topics
- Choosing a gen AI solution: needs (scale, customization, interaction, privacy, latency, connectivity) and resources (people, money, time)
- Top-down + bottom-up strategy, change management, measuring impact and ROI
- Secure AI: SAIF, secure-by-design infrastructure, IAM, Security Command Center, workload monitoring
- Responsible AI: transparency, privacy (anonymization, pseudonymization), bias, fairness, accountability, explainability
Hands-on
- Lab 11: SAIF risk review of your capstone agent
- Mock Exam 2: a fresh set of 55 questions in 90 minutes, under exam conditions
Working demo: Capstone dry run: 5-minute proposal plus the agent running live, with peer feedback
Deliverable: Mock 2 score report (target 80%+); capstone proposal draft · Exam domains: 4 Business strategy (4.1, 4.2, 4.3) · Google learning-path: Modules 1 & 5 (strategy)
Week 12Final revision, exam registration and CAPSTONE DEMO DAY
Topics
- Revision driven by each learner's mock-exam weak areas
- Official sample questions walkthrough
- Registration step by step: certification page, then Register; choosing online-proctored (check the online testing requirements) or a Pearson VUE test centre; ID and room rules
- Exam-day strategy for 50-60 questions in 90 minutes
Hands-on
- Each learner books an exam slot in the session (fee paid by the learner to Google Cloud)
- Capstone Demo Day
Working demo: Final capstone: live presentation of the business proposal plus a working agent/RAG demo
Deliverable: Capstone submission + course completion certificate · Exam domains: All · Google learning-path: All 5
Final working demo
Gen AI Business Proposal + Working Agent/RAG Demo
Pick a real problem from your organization or industry (e.g. HR policy assistant, IT helpdesk triage, insurance claim document Q&A). Write a 6-8 page proposal covering the use case, value hypothesis and KPIs, the solution layer (Workspace with Gemini / Gemini Enterprise / custom agent on Agent Platform) and why, model choice with trade-offs, grounding/RAG design, security (SAIF, IAM), responsible AI and privacy, rollout and change plan, and cost/ROI. Build a working prototype in Google AI Studio, Agent Studio, Gemini Notebook or Gemini Enterprise: an agent grounded on sample documents that cites its sources and refuses out-of-scope questions.
Format: Live online Demo Day: 8-minute pitch + 5-minute live demo + 5-minute Q&A from the panel (instructor + an invited industry guest). Recorded, with LinkedIn-ready clips.
- Business case and KPIs 25%
- Correct use of Google Cloud offerings 25%
- Working demo quality (grounded, cited, safe) 30%
- Security and responsible AI 10%
- Presentation 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)
- Languages
- English, Japanese, Spanish, Portuguese
- Delivery
- Online-proctored or onsite-proctored (test centre: search 'Google Cloud' in the Pearson VUE locator)
- Prerequisites
- None
- 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.
Fees & enrolment
Fees. Enrol in one message.
Next batch: GAIL prep: Weekday-evening batch (Tue & Thu 8-10 PM IST), Start date to be announced.
Prices are plus GST as applicable. All fees are non-refundable (policy).
| Option | Amount |
|---|---|
| Full paymentStandard | ₹30,000 |
| Early-bird (paid 14+ days before start)10% off, optional promo | ₹27,000 |
| 2 instalments2nd instalment due by Week 5 | ₹15,500 + ₹15,500 (₹31,000) |
| Corporate / group of 3+ from the same company15% off, single invoice | ₹25,500 per person |
- Registration: None (seat confirmed on payment)
- Exam fee: USD 99 + tax, paid directly to Google Cloud. Not included.
- Group, corporate and early-bird options are arranged on request: write to us.
Other batches: GAIL prep: Weekend batch (Sat & Sun 10 AM-12 PM IST)
Before you join
- No coding or certification needed (Google lists no prerequisites)
- Comfortable with English technical reading (exam languages: English, Japanese, Spanish, Portuguese)
- A personal Google account; optionally a Google Cloud free trial for Agent Platform labs
What you need
- Laptop with Chrome and a stable internet connection, webcam for sessions
- Personal Google account (Gemini app, Google AI Studio, Gemini Notebook / NotebookLM)
- Optional: Google Cloud free-trial project (Agent Platform, Model Garden, Agent Studio, Agent Search)
- Optional: Google Workspace with Gemini (trial or work account)
FAQ
Questions, answered.
Is this official Google training?
No. It's independent certification prep from IndMinds, built on Google's public exam guide, study guide and learning path. IndMinds isn't affiliated with Google.
Is the exam fee included?
No. Google lists the registration fee as USD 99 plus tax where applicable. You pay it to Google Cloud when you register.
What is the exam like?
90 minutes, 50-60 multiple-choice questions, taken online-proctored or at a test centre, valid for 3 years (per Google's certification page).
Do I need to code?
No. The exam is business-level. Labs are no-code or copy-paste, and the optional Python step is fully guided.
Do you guarantee I'll pass?
No one can guarantee a result. You get 2 full mock exams with domain-wise feedback, and we recommend booking the exam only after scoring 80% or more on Mock 2.
I missed a class?
Recordings go up within 24 hours, and the Wednesday doubt clinic covers catch-up questions.
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.