AI Ready: practical AI for everyone

You will learn

1. What AI is, and is not, in 2026
2. The landscape: assistants, agents, open models
3. Setting up free accounts safely
4. Privacy: what never to paste into an AI tool
5. Your baseline skills check

Hands-on lab

1. Give three assistants the same five tasks: summarise, explain, plan, calculate, create
2. Score each answer for accuracy, usefulness and speed
3. Note where each one shines and where it fails

Tools you will use

• ChatGPT
• Claude
• Gemini
• Microsoft Copilot

You will learn

1. Rules vs. learning: what machine learning is
2. Data, models and predictions
3. Neural networks, intuitively
4. How large language models predict the next token
5. Context windows, memory and reasoning models
6. Why AI hallucinates, and how to reduce it

Hands-on lab

1. Train a three-class image classifier in your browser, then break it with biased data
2. Count the tokens in a paragraph in English and in Hindi
3. Make a model hallucinate, then fix it by grounding it in a source

Tools you will use

• Teachable Machine
• TensorFlow Playground
• Tokenizer playground
• 3Blue1Brown
• Karpathy talks

You will learn

1. Anatomy of a strong prompt: role, task, context, format
2. Examples and reusable templates
3. Asking AI to reason, critique and improve
4. Context engineering: files, projects and memory
5. Custom assistants you can reuse
6. The four-check habit for verifying output

Hands-on lab

1. Rewrite five weak prompts and compare the before and after
2. Build a custom assistant for a task you do every week
3. Test it on three real cases and refine its instructions

Tools you will use

• Custom GPTs
• Claude Projects
• Gemini Gems

You will learn

1. AI search vs. chat: when to use which
2. Deep research agents
3. Studying from your own sources, with audio overviews
4. Checking citations and spotting fabricated sources
5. AI as a tutor: quizzes, flashcards, Socratic mode
6. Academic integrity: what is allowed and how to disclose it

Hands-on lab

1. Pick a question from your field and run a deep research report
2. Open and verify every citation it gives
3. Load the verified sources into NotebookLM and generate a study guide

Tools you will use

• Perplexity
• NotebookLM
• Deep Research
• Google Scholar
• Consensus

You will learn

1. Writing and editing in your own voice
2. Data analysis: upload a sheet, ask questions, chart it
3. Slides and documents in minutes
4. Generating and editing images
5. Short videos and voice-overs
6. Translation, including Indian languages
7. Meeting notes and email

Hands-on lab

1. Analyse a real public dataset and find three insights
2. Turn them into a five-slide deck with AI visuals
3. Make a 60-second narrated video, then translate it into a second language

Tools you will use

• ChatGPT data analysis
• Gemini in Sheets
• Gamma
• Canva
• Napkin AI
• ElevenLabs
• Sarvam AI
• Bhashini

You will learn

1. Thinking in workflows: trigger, steps, output
2. Adding AI steps to automations
3. Vibe coding: describe an app and AI builds it
4. Fixing bugs and making changes by conversation
5. Publishing and sharing your app
6. Keeping data and API keys safe

Hands-on lab

1. Automate one task: a form reply is summarised by AI and filed in a sheet
2. Build a quiz, calculator or portfolio site by describing it
3. Publish it and share the link with three people for feedback

Tools you will use

• n8n
• Zapier
• Make
• Lovable
• Bolt
• Replit
• Google AI Studio

You will learn

1. Chatbots vs. agents: tools, plans and actions
2. Browser and computer-use agents
3. MCP: how AI connects to your apps
4. Coding agents for non-coders
5. Voice and multimodal AI
6. Open and on-device models
7. Where agents fail, and how to supervise them

Hands-on lab

1. Give an agent a multi-step task, such as comparing five universities’ AI policies in a table
2. Log every step, error and correction it makes
3. Run a small open model on your own laptop and compare it with a frontier model

Tools you will use

• ChatGPT agent
• Claude connectors
• Gemini
• Model Context Protocol
• Ollama
• LM Studio
• Hugging Face

You will learn

1. Bias and fairness
2. Privacy and data protection: India’s DPDP Act, GDPR and the EU AI Act
3. Deepfakes, voice clones and scams
4. Copyright and who owns AI output
5. The environmental cost of AI
6. Disclosure and AI-use policies

Hands-on lab

1. Red-team a chatbot: try to make it break its own rules
2. Take a deepfake-spotting challenge and explain the clues
3. Write an AI-use policy for your class, team or business

Tools you will use

• Gandalf prompt-injection game
• Deepfake spotting quizzes
• Policy templates

You will learn

1. AI across fields: business, education, health, engineering, law, creative work, public service
2. Mapping tasks: automate, augment or keep human
3. Skills employers are asking for
4. AI-assisted job search: resume, portfolio, mock interviews
5. Building a habit of keeping up

Hands-on lab

1. Map ten tasks in your target role to the right AI tool, or to “no AI”
2. Build an AI-assisted resume and add your app as a portfolio site
3. Practise a voice mock interview and review the feedback

Tools you will use

• ChatGPT
• Claude
• Gemini
• Canva
• LinkedIn
• Voice mode

You will learn

1. Pick a problem for a club, department, family business or employer
2. Plan it: users, tools, success measure
3. Build it with AI
4. Test it with real users
5. Present it in a three-minute demo

Hands-on lab

1. Write a one-page plan and get peer feedback
2. Build and test with at least three users
3. Record a three-minute demo and a short reflection

Tools you will use

• Any tools from the course