Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.
| Feature | Agentic AI | Data Analytics |
|---|---|---|
| Level | Intermediate | Beginner |
| Duration | 4 Months | 3–4 Months |
| Who can join | Open to any stream; no computer science degree needed. Python basics are taught from scratch | Basic computer use; no programming or technical background required |
| Key tools | Python, Jupyter, VS Code, Git and GitHub, OpenAI, Anthropic Claude | Microsoft Excel, Google Sheets, SQL, MySQL, PostgreSQL, Python |
| What you’ll learn | Module 1: Foundations of AI, LLMs and Agentic AI · Module 2: Python for AI Agents · Module 3: Prompt and Context Engineering · Module 4: Tool Calling and Function Execution | 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 | AI agent developer, AI automation engineer, LLM application developer | Data Analyst, Business Analyst, MIS Executive |
Design and deploy AI agents that plan, use tools and complete multi-step tasks on their own.
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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