Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.
| Feature | Deep Learning | Power BI |
|---|---|---|
| Level | Advanced | Beginner |
| Duration | 3–4 Months | 1–2 Months |
| Who can join | Basic computer skills and school-level maths; Python or machine learning knowledge is useful but not compulsory | Comfort with Excel; no coding background required |
| Key tools | Python, Jupyter Notebook, Google Colab, NumPy, Pandas, Matplotlib | Power BI Desktop, Power BI Service, Power Query Editor, DAX, Microsoft Excel, SQL basics |
| What you’ll learn | 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 | Module 1: Business Intelligence and Power BI Basics · Module 2: Connecting to Data · Module 3: Data Cleaning with Power Query · Module 4: Data Modelling |
| Portfolio projects | — | — |
| Career roles | Deep Learning Engineer, Machine Learning Engineer, Computer Vision Engineer | Power BI Developer, Data Analyst, Business Analyst |
Learn how artificial neural networks, CNNs, RNNs, LSTMs and transformers learn from data, working in Python with TensorFlow, Keras and PyTorch on real datasets.
Turn raw business data into clear dashboards and reports with Microsoft Power BI: data connection and cleaning, modelling, DAX calculations and interactive dashboards.
A counsellor can map either course to your degree, schedule and career goal — one call is usually enough.
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