This course deals with Python and SQL in the context of data-driven decision making. Part 1 introduces frameworks for accessing web data and doing textual analysis with Python 3. The course introduces the basics of the Python syntax. After the basics, the focus is on data use and access. Data (pandas) and textual analyses are reviewed. Networked programs are reviewed including web scraping (BeautifulSoup). Web services are reviewed including API contracts. Interactive webpage development is introduced.
Part 2 deals with Structured Query Language (SQL) for accessing and modifying data held in databases. We will review commands for interfacing with databases. After the basics, predictions from tables in databases are dealt with. The integration of SQL with back-end and front-end languages is discussed.
Students apply the frameworks in various data projects. Examples used are relevant for corporate and financial analysts.
Part 2 deals with Structured Query Language (SQL) for accessing and modifying data held in databases. We will review commands for interfacing with databases. After the basics, predictions from tables in databases are dealt with. The integration of SQL with back-end and front-end languages is discussed.
Students apply the frameworks in various data projects. Examples used are relevant for corporate and financial analysts.
- Teacher: Gustav Finne
- Teacher: Marco Lambrecht
- Teacher: Thoi Mai
- Teacher: Benjamin Maury
- Teacher: Elyas Saif
- Teacher: Joosua Virtanen
- Teacher: Xiaogeng Xu