Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.
| Feature | Prompt Engineering | Deep Learning |
|---|---|---|
| Level | Beginner | Advanced |
| Duration | 6 Weeks | 3–4 Months |
| Who can join | Open to any stream; no technical degree or programming background needed | Basic computer skills and school-level maths; Python or machine learning knowledge is useful but not compulsory |
| Key tools | ChatGPT, Claude, Google Gemini, Microsoft Copilot, Perplexity, NotebookLM | Python, Jupyter Notebook, Google Colab, NumPy, Pandas, Matplotlib |
| What you’ll learn | Module 1: Foundations of Generative AI · Module 2: Core Prompting Principles · Module 3: Advanced Prompting Techniques · Module 4: Prompting for Business and Content | 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 | AI content specialist, Prompt designer, AI operations executive | Deep Learning Engineer, Machine Learning Engineer, Computer Vision Engineer |
Get reliable, high-quality results from ChatGPT, Claude and Gemini, and turn prompting into a job skill.
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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