About Gen AI
Put generative AI to work in real products
Chatbots, copilots and image tools are changing every job. Learn how large language models work, how to prompt them well and how to build apps on top of them.
- Sales grew 12% on strong web demand.
- Returns fell, thanks to better sizing guides.
- Next step: expand the top two product lines.
What is generative AI?
It is AI that creates new content, such as text, code, images and plans, instead of only sorting or predicting. Four kinds of work show up again and again.
Software that can write, draw and reason
Large language models learn patterns from huge amounts of text and can answer questions, draft documents and explain ideas. Your job is to guide them with good instructions, connect them to company data and check what they produce.
Write and summarize
Draft emails, summarize reports, translate and answer questions.
Build faster
Generate, explain and fix programs with an AI assistant.
Create visuals
Produce and edit pictures from a written description.
Finish tasks
Systems that plan steps and use tools to get work done.
The six steps of every project
You will repeat this cycle on practical use cases until it feels natural.
Pick the task
Choose a problem where AI can save time or improve quality.
Choose a model
Compare models on quality, speed, cost and privacy.
Write the prompt
Give clear instructions, examples and a format for the answer.
Add your data
Use retrieval (RAG) so answers come from trusted documents.
Test and evaluate
Check accuracy, safety and tone on real examples.
Launch and monitor
Release it, watch cost and quality, and keep improving.
Why learn generative AI
Useful in almost every job
Marketing, finance, HR, support and engineering teams all use AI to work faster and better.
Easy to begin
Prompting needs no coding, so you can start on day one.
Quick results
See a working prototype in hours, not months.
Many paths
Move into engineering, product, consulting or leadership.
Tools employers ask for
LLM APIs, Python, retrieval with vector databases and agent frameworks appear in more and more job descriptions.
Future ready
The core skills carry over as new models and tools appear.
AI can sound confident and still be wrong. Strong practitioners always check outputs and design for accuracy, privacy and safety.
Roles you can aim for
Job titles vary by company, but these are the common starting points and next steps.
Generative AI engineer
Builds apps and features powered by language and image models.
Python · LLM APIs · RAGPrompt engineer / AI specialist
Designs and tests prompts so AI gives reliable results.
Prompting · EvaluationConversational AI developer
Creates chatbots, voice assistants and agents for customers and staff.
Agents · APIs · PythonAI product manager
Decides which AI features to build and how to measure success.
Product skills · AI toolsLLM / ML engineer
Fine-tunes, deploys and monitors models in production.
Python · Cloud · MLOpsAI consultant
Helps companies find use cases and adopt AI responsibly.
Strategy · PrototypingWhat you will be able to do
Technical skills
- Prompt engineering: write clear, testable instructions.
- Python and APIs: connect models to your own apps.
- RAG: answer from documents using vector search.
- Agents: let AI plan steps and use tools.
Thinking and responsibility
- Evaluation: measure quality and catch wrong answers.
- Safety: reduce bias, leaks and made-up facts.
- Use-case design: pick work where AI truly helps.
- Communication: explain AI results and limits to others.
Who it is for
Graduates
Students from any stream preparing for an AI-ready career.
Working professionals
Anyone who wants to use AI to do their job better.
Developers
Engineers adding LLMs and agents to their products.
Leaders
Managers and founders deciding where AI fits in the business.
Where generative AI is used
Results depend on practice and projects. A portfolio of working, well-tested AI projects matters more than a certificate alone.
Questions people ask
Do I need coding experience?
Not to start. Prompting needs no code. Building apps uses basic Python, taught step by step.
Do I need an AI or math background?
No. The ideas are explained in plain language, with hands-on practice.
Is generative AI a safe career bet?
AI is changing how work is done. People who can use it well and check its output are in demand, and the course focuses on those skills.
Which tools and models will I use?
You learn principles that work across models, then practice with popular tools. Check the syllabus for the exact list.
Ready to start your generative AI journey?
Join the next batch and learn to build with AI that writes, draws and reasons.
