Both are taught at techcadd. Here is how they differ on level, tools, projects and where each one can take you.
| Feature | Data Science | Power BI |
|---|---|---|
| Level | Intermediate | Beginner |
| Duration | 5–6 Months | 1–2 Months |
| Who can join | Basic school-level maths; no prior coding experience needed | Comfort with Excel; no coding background required |
| Key tools | Python, Jupyter Notebook, NumPy, Pandas, Matplotlib, Seaborn | Power BI Desktop, Power BI Service, Power Query Editor, DAX, Microsoft Excel, SQL basics |
| What you’ll learn | Module 1: Foundations of Data Science · Module 2: Python Programming for Data Science · Module 3: Statistics and Probability · Module 4: SQL and Databases | 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 | Data analyst, Business analyst, Junior data scientist | Power BI Developer, Data Analyst, Business Analyst |
Learn to collect, clean, analyse and visualise data, then build predictive models that solve real business problems, using Python, SQL, statistics, machine learning and modern visualisation tools.
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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