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Berkeley Global
Learn how to analyze and mine data with the Structured Query Language (SQL). Once you’ve gained the fundamentals of SQL, you advance into the uses of SQL data analysis and data mining with real applications. You use Microsoft Excel to further analyze, manipulate and present your data exploration and data mining findings in tabular and graphical formats. This course is ideal if you want to analyze data with SQL queries and learn statistical methods to test the results. Learn more by e-mailing the instructor at mkremer@berkeley.edu or by visiting the instructor's website.
Prerequisites:
Recommended
Fundamental knowledge/experience of SQL or the following courses:
- Introduction to SQL COMPSCI X451.1
- Managing Data(bases) using SQL EL ENG X401.9
Course Outline
Expand or collapse section
Course Objectives
- Construct SQL queries for data exploration, analysis, mining and statistical testing of results
- Develop advanced queries and calculations using SQL, as well as further analyze and present these results using Excel
- Learn how to perform data analysis using SQL and test the statistical significance of the resulting measurements using different statistical methods
- Learn and practice statistical methods such as null hypothesis, confidence intervals, normal distribution, calculation of probabilities from sample data, difference of proportion
What You Learn
- SQL queries
- SELECT commands UNION, INTERSECT and EXCEPT
- Nested queries
- Aggregate operators
- Null values
- Advanced SQL features
- Data analysis using dataflows
- SQL queries and subqueries
- Data exploration
- Charting with Excel String values
- Data mining models in SQL
- Directed data mining
- Statistical concepts
- Chi-square
How You Learn
- Lectures
- Group discussions
- Review of homework problems
- Assigned textbook chapters
- Homework assignments
Is This Course Right for You?
If you want to explore, analyze and mine data with SQL queries, as well as learn statistical testing of data analysis results, this course is ideal. It is geared to heavy data users, scientists, data modelers, business intelligence professionals, business analysis professionals, dashboard designers, DBAs, quantitative/computational financial engineers and system administrators.
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Spring enrollment opens on October 16!