Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.
| Feature | Generative AI | Machine Learning |
|---|---|---|
| Level | All Levels | Intermediate |
| Duration | 6 Months | 4–6 Months |
| Who can join | A laptop with stable internet and basic English reading skills; prior coding is helpful but not mandatory | Basic computer skills and school-level maths; no prior programming experience required |
| Key tools | ChatGPT, Claude, Gemini, Microsoft Copilot, Hugging Face, Python | Python, Jupyter Notebook, Google Colab, NumPy, Pandas, SQL |
| 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: Python for Machine Learning · Module 2: Maths and Statistics Essentials · Module 3: Data Handling and Visualisation · Module 4: Supervised Learning |
| Portfolio projects | — | — |
| Career roles | Prompt engineer, AI content specialist, AI automation executive | Machine Learning Engineer (junior), Data Analyst, Junior Data Scientist |
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.
Start with Python, statistics and data handling, then move on to supervised and unsupervised learning, model evaluation and deploying simple models into real applications.
A counsellor can map either course to your degree, schedule and career goal — one call is usually enough.
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