Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.
| Feature | Generative AI | RAG (Retrieval-Augmented Generation) |
|---|---|---|
| Level | All Levels | Advanced |
| Duration | 6 Months | 2 Months |
| Who can join | A laptop with stable internet and basic English reading skills; prior coding is helpful but not mandatory | Open to any stream; no machine learning background needed. Python basics are taught from scratch |
| Key tools | ChatGPT, Claude, Gemini, Microsoft Copilot, Hugging Face, Python | Python, Jupyter, VS Code, Git and GitHub, OpenAI, Anthropic Claude |
| What you’ll learn | Module 1: AI, Machine Learning and Generative AI Foundations · Module 2: Large Language Models (LLMs) · Module 3: Prompt Engineering · Module 4: Python Basics for AI | Module 1: Foundations of LLMs and RAG · Module 2: Python for AI Applications · Module 3: Document Processing and Chunking · Module 4: Embeddings and Vector Databases |
| Portfolio projects | — | — |
| Career roles | Prompt engineer, AI content specialist, AI automation executive | RAG developer, LLM application developer, AI engineer |
Learn to build with, and work alongside, AI tools that create text, images, code, audio and video: large language models, prompt engineering, RAG, AI agents and responsible AI use.
Build AI assistants that answer accurately from your own documents, websites and databases.
A counsellor can map either course to your degree, schedule and career goal — one call is usually enough.
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