Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.
| Feature | Generative AI | Deep Learning |
|---|---|---|
| Level | All Levels | Advanced |
| 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 skills and school-level maths; Python or machine learning knowledge is useful but not compulsory |
| Key tools | ChatGPT, Claude, Gemini, Microsoft Copilot, Hugging Face, Python | Python, Jupyter Notebook, Google Colab, NumPy, Pandas, Matplotlib |
| 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 and Maths for Deep Learning · Module 2: Machine Learning Foundations · Module 3: Neural Network Fundamentals · Module 4: Building and Tuning Models with TensorFlow, Keras and PyTorch |
| Portfolio projects | — | — |
| Career roles | Prompt engineer, AI content specialist, AI automation executive | Deep Learning Engineer, Machine Learning Engineer, Computer Vision Engineer |
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 how artificial neural networks, CNNs, RNNs, LSTMs and transformers learn from data, working in Python with TensorFlow, Keras and PyTorch on real datasets.
A counsellor can map either course to your degree, schedule and career goal — one call is usually enough.
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