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ChatGPT & AI Tools vs RAG (Retrieval-Augmented Generation)

Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.

Side by side

The differences at a glance

FeatureChatGPT & AI ToolsRAG (Retrieval-Augmented Generation)
LevelBeginnerAdvanced
Duration4 Weeks2 Months
Who can joinBasic computer or smartphone skills and a stable internet connection; no coding knowledge requiredOpen to any stream; no machine learning background needed. Python basics are taught from scratch
Key toolsChatGPT, Google Gemini, Claude, Microsoft Copilot, Perplexity, NotebookLMPython, Jupyter, VS Code, Git and GitHub, OpenAI, Anthropic Claude
What you’ll learnModule 1: AI Foundations · Module 2: ChatGPT Essentials and Prompt Writing · Module 3: AI for Writing and Communication · Module 4: AI for Research and LearningModule 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 rolesAI-assisted content writer or social media executive, Digital marketing executive, Prompt writer or AI operations assistantRAG developer, LLM application developer, AI engineer
Which to pick

Choose the one that fits your goal

Pick ChatGPT & AI Tools if…

Learn to use ChatGPT and other leading AI tools to work faster, write better, analyse information and automate everyday tasks, with no coding background needed.

  • Write clear, structured prompts that give reliable results
  • Choose the right AI tool for writing, research, design, data or automation
  • Cut repetitive work time and improve the quality of your output
Explore ChatGPT & AI Tools

Pick RAG (Retrieval-Augmented Generation) if…

Build AI assistants that answer accurately from your own documents, websites and databases.

  • Explain how RAG works and when to use it instead of fine-tuning
  • Process messy real-world documents and choose sensible chunking and embedding settings
  • Build and tune a retrieval pipeline with hybrid search and reranking
Explore RAG (Retrieval-Augmented Generation)

Still deciding between the two?

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