Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.
| Feature | Machine Learning | Power BI |
|---|---|---|
| Level | Intermediate | Beginner |
| Duration | 4–6 Months | 1–2 Months |
| Who can join | Basic computer skills and school-level maths; no prior programming experience required | Comfort with Excel; no coding background required |
| Key tools | Python, Jupyter Notebook, Google Colab, NumPy, Pandas, SQL | Power BI Desktop, Power BI Service, Power Query Editor, DAX, Microsoft Excel, SQL basics |
| What you’ll learn | Module 1: Python for Machine Learning · Module 2: Maths and Statistics Essentials · Module 3: Data Handling and Visualisation · Module 4: Supervised Learning | 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 | Machine Learning Engineer (junior), Data Analyst, Junior Data Scientist | Power BI Developer, Data Analyst, Business Analyst |
Start with Python, statistics and data handling, then move on to supervised and unsupervised learning, model evaluation and deploying simple models into real applications.
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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