Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.
| Feature | RAG (Retrieval-Augmented Generation) | Tableau |
|---|---|---|
| Level | Advanced | Beginner |
| Duration | 2 Months | 1–2 Months |
| Who can join | Open to any stream; no machine learning background needed. Python basics are taught from scratch | Basic computer skills; no coding background needed |
| Key tools | Python, Jupyter, VS Code, Git and GitHub, OpenAI, Anthropic Claude | Tableau Desktop, Tableau Prep Builder, Tableau Public, Tableau Cloud, Tableau Server, Microsoft Excel |
| What you’ll learn | 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 | Module 1: Introduction to Data and Business Intelligence · Module 2: Connecting and Preparing Data · Module 3: Building Charts and Visual Analysis · Module 4: Calculations and Analytics |
| Portfolio projects | — | — |
| Career roles | RAG developer, LLM application developer, AI engineer | Data Analyst, Business Analyst, BI Analyst |
Build AI assistants that answer accurately from your own documents, websites and databases.
Learn to connect data sources, clean and prepare data, build charts, write calculated fields, design interactive dashboards and present data stories with Tableau.
A counsellor can map either course to your degree, schedule and career goal — one call is usually enough.
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