Gen AI Certification Program

Why should you take the Gen AI Certification Program?

• 100 hours of live Instructor-led Virtual Training
• 26 hours of projects, mentorship and guest lectures
• Low-code/No-code AI solution building and multi-modal AI workflows
• Hands-on with 12+ Gen AI tools
• 15 mini projects and 1 capstone project + 2 partner-powered projects
• Certification by NASSCOM

Who should take the Gen AI Certification Program?

• Working Professionals - BFSI, Marketing, HR, Ops, Finance, Retail, Sales looking to boost productivity with AI.
• Business and Creative Roles - Product Managers, Marketers, Designers, and Content creators integrating GenAI into workflows.
• Students and Graduates - Learners in Computer science, Business, or Design building industry-ready AI skills.
• Entrepreneurs and Founders - Founders aiming to build AI products, automate processes, or explore startup use cases.
• Curious Learners - Anyone exploring tools like ChatGPT, DALL·E, or the wider impact of GenAI.

Curriculum

Module 1

• What is Artificial Intelligence (AI) and Machine Learning (ML)
• Artificial General Intelligence (AGI) vs Narrow AI
• Generative AI with pre-trained foundation models
• How AGI/Generative AI is disrupting industries and career options
• Large Language Models (LLMs) and how they are developed
• LLM mechanics - tokens, context window, token limits, vector embeddings
• Four ways of working with LLMs
• Prompt Engineering demos
• Agentic AI/AI Agents - examples
• Retrieval-Augmented Generation (RAG) - use cases
• Innovations in AI-Humanoids, NVIDIA Digital Human, Project R2X, Edge AI
• Overview of frontier AI systems like OpenAI's GPT-5
• Aligning your career to the AI wave

Module 2

• Introduction to Natural Language Processing (NLP)
• Prompt Engineering for chatbots, voicebots, and enterprise assistants
• Use cases in customer support, education, and internal automation
• Advanced Prompt Engineering - structured prompts, multi-step reasoning, tone/style control

Module 3

• Pre-trained foundation models for image data
• Vision Language Models (VLMs) - use cases
• Multimodal LLMs
• Image captioning and summarisation
• Visual Question Answering (VQA)
• Image generation
• Object detection and segmentation
• Visual search applications
• AI for video content - tagging, summarisation, generation
• Using Google Gemini, Veo, OpenAI, Amazon Nova for visual tasks

Module 4

• Pre-trained foundation models for audio data
• Speech-to-text and Text-to-speech workflows
• AI tools for audio-AssemblyAI, ElevenLabs, Whisper
• Voice cloning and custom voice generation
• Audio sentiment and emotion detection
• Using Google, OpenAI, Amazon Nova for audio tasks
• Building an audio transcription and search pipeline
• Applications in podcasts, accessibility tools, and automated meeting notes

Module 5

• How AI Agents work
• Connecting AI with apps and cloud
• Getting Data from websites
• Using APIs and easy connectors
• Smart document handling
• Recognising objects with AI
• Ready-to-use AI agents

Module 6

• Building a RAG chatbot with Langflow (no-code)
• Building an AI agent with Langflow (no-code)
• Creating custom workflows with Langflow integrations (databases, APIs, vector stores)
• Building AI solutions with Claude Desktop
• Automating tasks with n8n.io-triggers, nodes, and integrations
• Creating AI-powered data pipelines with no-code tools
• Designing multi-step automation combining text, image, and audio models
• Deploying no-code AI apps to web interfaces for end-users
• Integrating APIs from OpenAI, Anthropic, Hugging Face, and Google AI into no-code platforms
• Implementing security and access control in no-code AI solutions

Module 7

Understanding domain-specific GenAI applications, benefits, and adoption challenges:

• Banking and Financial Services
• Insurance
• Retail and E-commerce
• CPG, Industrial Products, Oil and Gas, Pharma
• Media and Entertainment
• Finance and Accounting, Auditing
• Supply Chain and Manufacturing
• Marketing and Sales
• Customer Service
• HR

Module 8

• Responsible AI framework and ethics principles
• AI safety with guardrails and prompt filtering
• Hands-on: Configuring and testing guardrails in LLM workflows
• AI regulations across geographies - US, EU, India, China
• Sovereign AI-localised models and data policies
• Bias detection and mitigation strategies
• Risk assessment frameworks for AI deployment

Module 9

• Capstone project planning - defining a real-world GenAI use case
• Selecting datasets, tools, and execution approach
• Building, testing, and refining the solution
• Portfolio creation - showcasing projects on GitHub, Notion, LinkedIn
• Resume and LinkedIn optimisation for GenAI roles
• Presenting projects to an industry review panel

Tools you will learn in the Gen AI Certification Program:

• ChatGPT
• Make
• ElevenLabs
• Claude
• InVideo AI
• Veo
• Lovable
• NotebookLM
• Gemini
• Sora
• DALL·E
• OpenAI API
• HeyGen
• n8n
• LangFlow
• LangChain
• Vector DB
• Streamlit