SQL is a dominant data analysis language, since data are usually available in a structured, database format. Most analyses involve a lot of filtering, grouping, sorting, and aggregation, for which SQL is quite handy to use. Python, on the other hand, has well-known libraries, specially designed for data analysis and statistical modeling. This course teaches how to perform descriptive, diagnostic, and predictive analytics using functions, procedures, and best practices in both SQL and Python. Combining the use of SQL to retrieve and process the essential data for analysis, together with the use specialized Python libraries for more complex data manipulation, analysis, and modeling is also discussed.
What You Will Learn
Upon completion of this course, the learners are expected to:
- leverage the powerful combination of SQL and Python to efficiently perform analysis and modeling; and
- apply the appropriate analytics and modeling techniques in solving business problems.
You will need a computer or laptop with Microsoft Excel installed. Computer or laptop requirements are:
- For Windows: Core i3 or better, 4GB RAM or better, MS Excel 2007 or better
- For MacBook: ideally MS Excel 2013 or newer should be installed (some functions require this version on the Mac). If the version of MS Excel is 2011, download and install StatPlus.