SQL for Data Analysis
Joins, grouping, subqueries, CASE, CTEs and window functions with PostgreSQL — answering business questions throughout.
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Learning area 01
Data & Analytics training
Most of the work in analytics happens before the chart: finding the data, cleaning it, joining it and checking it. These courses teach that work properly — with SQL, Python or R — and the statistics to back up what you conclude.
After this area you can…
- Pull exactly the data you need from a database
- Clean and combine messy files without doing it by hand
- Summarise, cross-tabulate and test differences properly
- Chart results and hand over report-ready output
Courses
Choose your tool
SQL gets the data out. Python and R analyse it. Many analysts learn SQL plus one of the two.
Data Analysis Using Python
Python basics, then Pandas for cleaning and reshaping, EDA and Matplotlib — ending in a full practical exercise.
View courseData Analysis Using R
Excel, CSV and SPSS data through cleaning, recoding, t-tests, ANOVA, chi-square and regression.
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Python or R?
Both are good. Pick by the work you do.
What comes next
From analysis to dashboards
Once your data is clean and your analysis is sound, the next step is putting it in front of the people who decide — that’s business intelligence.
Explore Business IntelligenceData & Analytics questions
Which data analytics course should a complete beginner take first?
SQL for Data Analysis. It’s the most widely used data skill, it reads close to plain English, and it makes every other tool easier.
Do these courses include statistics?
Yes. Python covers descriptive statistics and exploratory analysis; R goes further into hypothesis testing, t-tests, ANOVA, chi-square, correlation and regression.
Can my team take these as a private batch?
Yes — and we can build the exercises around your own data. See corporate training.
Start with the data skill you’ll use most
Register and we’ll confirm the next batch, schedule and fee with you directly.