RAG
Connect AI to your own documents so answers use information you control.
AI5 PROFESSIONAL CERTIFICATE · BY TGC INDIA · UPDATED AUGUST 2026
Generative AI Master Program
MASTER GENERATIVE AI, RAG, MULTIMODAL AI, AUTOMATION & AGENTIC WORKFLOWS
Master Generative AI, RAG, multimodal AI, automation and agentic workflows—then deliver a tested AI solution without needing prior coding knowledge.
Use AI → Control AI → Create with AI → Ground AI on knowledge → Automate with AI → Build AI agents → Deliver an AI solution.
16 WeeksBeginner to AdvancedNo Coding PrerequisiteOnline + ClassroomProject-Based
22+years in training
20,000+learners across TGC
5classroom locations
Live onlinejoin from anywhere
BEYOND PROMPT ENGINEERING
Move from AI user to AI workflow builder to AI systems practitioner.
LLMs → Prompt & Context Engineering → AI Research → Multimodal AI → RAG & Knowledge Systems → AI Automation → AI Agents → Production AI
The core route is no-code or low-code. Technical terms are introduced through diagrams, live demonstrations and guided builds before optional API or framework examples.
TECHNICAL TERMS, PLAIN LANGUAGE
Start with the idea. Then build it.
The course explains each system in everyday language before showing its parts and working method.
Embeddings
Turn meaning into numerical representations that help AI find related information.
Vector search
Find information by meaning, not only exact keywords.
APIs
Let one application request an AI model or another software service.
Agentic AI
AI that can plan steps, use approved tools and work toward a defined goal.
MCP
A common way for AI applications to connect with approved tools and data.
NEXT START OPTIONS
Choose a live batch.
COURSE OVERVIEW
What this course
is built to do.
Progress from using leading AI models to designing prompt systems, research workflows, multimodal content, grounded knowledge assistants, automations and practical AI agents. The course stays accessible to beginners while introducing the architecture, testing and controls needed for usable AI systems.
Each module combines a live trainer demonstration, guided lab, assignment and review before the next stage.
CONNECTED CAREER DIRECTIONS
Generative AI SpecialistAI Automation SpecialistGenAI Application BuilderAI Workflow SpecialistAI Adoption SpecialistAI Research SpecialistAI Content & Multimodal Specialist
IS THIS COURSE RIGHT FOR YOU?
Choose it for the right reason.
You want a broad career route from AI use to AI solution building
You need hands-on work in RAG, automation, multimodal AI and agents
You want technical concepts explained without a Python prerequisite
YOUR LEARNING ARC
From guided foundation to finished work.
Use AI
Models, research, prompting and verification.
Control AI
Context, structured output, grounding and evaluation.
Build with AI
Multimodal work, RAG, APIs, n8n and agents.
Deliver
Guardrails, cost checks, documentation and capstone presentation.
INDUSTRY TASKS
Practise the work, not only the tool.
- Build a source-backed company knowledge assistant
- Create an n8n automation with approvals and error paths
- Build and test a tool-using AI agent
PRO
LED
LED
YOUR TRAINING TEAM
Learn from experienced working professionals.
Live demonstrations, guided practice and direct project feedback are part of the course. Trainers update examples and tool coverage as professional practice changes.
WHAT YOU WILL BE ABLE TO DO
Course outcomes
01
Select and control suitable AI models
A tested model scorecard and repeatable prompt and context system.
02
Research and create across multiple AI formats
Source-checked research plus a text, image, video and voice campaign.
03
Build grounded AI knowledge systems
A working RAG assistant with retrieval tests and source-backed responses.
04
Create connected AI automations
An n8n workflow using structured data, model APIs, approvals and error handling.
05
Build practical AI agents
A tool-using multi-step agent with permissions, human review and failure controls.
06
Test and present a usable AI solution
A documented capstone covering architecture, data, cost, guardrails and results.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
DETAILED COURSE FLOW
8 learning modules
Use AI → Control AI → Create with AI → Ground AI on knowledge → Automate with AI → Build AI agents → Deliver an AI solution.
Weeks 1–2 — Generative AI & LLM foundations
Understand modern Generative AI at a practical level and select a suitable model for each task.
CORE TOPICS
- LLMs, tokens, context windows and multimodal models
- Capabilities, limits and model comparison
- Hallucinations, privacy and data handling
- Responsible use, human verification and AI-assisted workflows
GUIDED PRACTICE
Compare leading models on the same professional task and record quality, speed, limits and suitable use.
MODULE DELIVERABLE
Model-selection scorecard and safe-use checklist
Weeks 3–4 — Prompt & context engineering
Move beyond one-off prompts and design repeatable AI work with controlled context and output formats.
CORE TOPICS
- Role, task, context, constraints and examples
- Zero-shot, few-shot, prompt templates and chaining
- Structured and JSON output, system instructions
- Long context, reasoning workflows, prompt testing and reusable systems
GUIDED PRACTICE
Design, test and revise a reusable AI workflow for a real professional or business task.
MODULE DELIVERABLE
Prompt and context workflow project
Weeks 5–6 — AI research & knowledge work
Turn web pages and documents into source-checked research, organised knowledge, reports and presentations.
CORE TOPICS
- Deep research, web research and source verification
- PDF and document analysis, extraction and comparison
- Summaries, reports and research-to-presentation workflows
- Notebook-based knowledge systems with ChatGPT, Gemini, Claude, Perplexity and NotebookLM
GUIDED PRACTICE
Build a research and knowledge workflow for a selected subject or organisation.
MODULE DELIVERABLE
AI research and knowledge project
Weeks 7–8 — Multimodal Generative AI
Combine text, images, video and voice in one controlled content or campaign workflow.
CORE TOPICS
- Text-to-image, image-to-image, editing and composition control
- Product visuals and character-consistency concepts
- Text-to-video, image-to-video, camera and motion prompting
- Voiceovers, multilingual voice and basic AI audio workflows
GUIDED PRACTICE
Create a coordinated multimodal campaign using current leading image, video and voice models.
MODULE DELIVERABLE
Multimodal AI campaign
Weeks 9–10 — RAG & AI knowledge systems
Connect AI to approved documents and knowledge so answers are grounded in information you control.
CORE TOPICS
- RAG, private knowledge and document preparation
- Chunking, embeddings, semantic search and vector search
- Retrieval, grounding, context injection and citations
- Failure cases, retrieval testing, RAG evaluation, access and privacy
GUIDED PRACTICE
Create and test a document or company knowledge assistant through a no-code or low-code workflow.
MODULE DELIVERABLE
RAG knowledge assistant
Weeks 11–12 — AI automation & API workflows
Connect AI models with business applications through structured, supervised automation.
CORE TOPICS
- n8n triggers, actions, structured data and workflow logic
- APIs, keys, security, webhooks and model API demonstrations
- Data passing, email, documents and CRM workflow examples
- Human approvals, error handling and basic cost awareness
GUIDED PRACTICE
Build an AI-powered n8n business workflow with an approval point and an error path.
MODULE DELIVERABLE
AI automation project
Weeks 13–14 — Agentic AI & AI agents
Build a multi-step AI system that can use approved tools while remaining controlled and testable.
CORE TOPICS
- LLM vs chatbot vs workflow vs agent
- Goals, tool calling, memory, planning and agent loops
- Single-agent work, multi-agent concepts and agentic automation
- n8n AI Agents, LangChain and LangGraph concepts, MCP, permissions, reliability and cost control
GUIDED PRACTICE
Build an AI agent that completes a multi-step task using tools and human approval where needed.
MODULE DELIVERABLE
Agentic AI project
Weeks 15–16 — Production AI & capstone
Move from a prototype to a usable AI solution with testing, controls, documentation and a clear presentation.
CORE TOPICS
- Prompt, RAG and agent evaluation
- Accuracy checks, hallucination control and guardrails
- Privacy, permissions, latency, token cost and monitoring
- Human oversight, deployment concepts, documentation and solution presentation
GUIDED PRACTICE
Deliver a working solution and explain the problem, architecture, models, knowledge, workflow, testing and result.
MODULE DELIVERABLE
Portfolio-ready final capstone
HOW THE TRAINING WORKS
Learn it. Apply it. Get it reviewed. Improve it.
Every important skill moves through explanation, demonstration, guided use and independent application. Trainer feedback is used to revise the work before it becomes part of the final portfolio.
Concept briefing
The trainer explains the principle, use case, limitations and the quality standard expected.
Live demonstration
A complete task is demonstrated while the trainer explains decisions, checks and common mistakes.
Guided lab
Learners repeat the method with support, ask questions and correct problems during the session.
Applied assignment
The same method is used on a different brief so the learner must make independent decisions.
Review and revision
Work is checked against a rubric, revised after feedback and prepared for project presentation.
PROGRESS IS CHECKED THROUGHClass exercisesModule deliverablesProject reviewsFinal capstone presentation
PORTFOLIO WORK
Projects you can show
Reusable prompt workflow
Plan, produce, test and present a finished piece with trainer feedback.
AI research and knowledge workflow
Plan, produce, test and present a finished piece with trainer feedback.
Multimodal AI campaign
Plan, produce, test and present a finished piece with trainer feedback.
RAG knowledge assistant
Plan, produce, test and present a finished piece with trainer feedback.
AI business automation
Plan, produce, test and present a finished piece with trainer feedback.
Tool-using AI agent
Plan, produce, test and present a finished piece with trainer feedback.
Final Generative AI capstone
Plan, produce, test and present a finished piece with trainer feedback.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
TOOLS COVERED
Foundation models
ChatGPT / OpenAIGeminiClaude
Research & knowledge
PerplexityNotebookLMDeep-research features in current leading models
Multimodal AI
Current leading image modelsCurrent leading video modelsRunwayElevenLabsCurrent voice and audio models
Automation & application building
n8nOpenAI APIGemini APIAnthropic / Claude API conceptsWebhooksStructured data
RAG & agentic AI
EmbeddingsVector searchRetrieval pipelinesTool callingAI agentsLangChain conceptsLangGraph conceptsMCP
Students work with leading current AI models. Specific models demonstrated may change as stronger models become available. The programme teaches transferable methods and does not require mastery of one vector database or agent framework.MASTER PROGRAM + SPECIALIST DEPTH
Build a broad GenAI system, then choose a deeper route.
The Master Program covers each layer as part of one connected solution. Specialist programmes go further in their own production or technical track.
COMMON QUESTIONS
Before you apply
Do I need coding knowledge?
No coding prerequisite is required for the core programme. Optional technical and API demonstrations are included for learners who want more depth.
＋Is this only a ChatGPT course?
No. Students work across leading Generative AI models and learn AI research, multimodal AI, RAG, automation and agentic workflows.
＋Will I learn RAG?
Yes. RAG and knowledge-grounded AI systems form a dedicated two-week module with a working knowledge-assistant project.
＋Will I learn AI agents?
Yes. You will learn agent goals, tool use, memory, planning, approvals, failure handling and practical multi-step agent building.
＋Will I learn n8n?
Yes. n8n is used for practical AI automation and agentic workflow exercises.
＋Will I learn APIs?
Yes. You receive practical exposure to AI APIs, webhooks, structured data and application connections without needing prior programming knowledge.
＋Will the tools remain current?
Yes. The course teaches transferable methods and uses leading current AI models. Demonstrated models may change as stronger options become available.
＋Is the programme suitable for beginners?
Yes. It starts with Generative AI foundations and moves step by step into RAG, automation, agents and production checks.
＋What will my final portfolio contain?
Six hands-on module projects plus a capstone showing the problem, AI architecture, models, knowledge, workflow, testing and result.
＋Do I need coding experience?
No, unless the course level says otherwise. Your advisor will check the right starting level.
＋Are classes live or recorded?
Classes are trainer-led in the classroom or live online. Recordings may support revision but do not replace class.
＋Will I receive a certificate?
Yes. Course completion requires attendance, assignments and the final project.
＋Can working professionals join?
Yes. Weekday, weekend and selected fast-track schedules are available.
＋NEXT BATCH
Choose your course.
Choose your schedule.
Online or offline. Weekdays or weekends. Regular or fast track. Speak with an AI5 Academy advisor about the right starting level.