Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.
| Feature | Generative AI | Data Analytics |
|---|---|---|
| Level | All Levels | Beginner |
| Duration | 6 Months | 3–4 Months |
| Who can join | A laptop with stable internet and basic English reading skills; prior coding is helpful but not mandatory | Basic computer use; no programming or technical background required |
| Key tools | ChatGPT, Claude, Gemini, Microsoft Copilot, Hugging Face, Python | Microsoft Excel, Google Sheets, SQL, MySQL, PostgreSQL, Python |
| 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: Data Analytics Foundations · Module 2: Advanced Excel for Analysis · Module 3: SQL for Data Analysis · Module 4: Statistics for Analysts |
| Portfolio projects | — | — |
| Career roles | Prompt engineer, AI content specialist, AI automation executive | Data Analyst, Business Analyst, MIS Executive |
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.
Learn to collect, clean, analyse and present data using the tools employers actually ask for, such as Excel, SQL, Power BI, Tableau and Python, through real datasets and hands-on projects.
A counsellor can map either course to your degree, schedule and career goal — one call is usually enough.
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