LSE DS105M (2022/23)
Data for Data Science
π Course Brief
Focus: learn how to collect and handle so-called βreal dataβ
How: hands-on coding exercises and a group project
π― Learning Objectives
- Understand the basic structure of data types and common data formats
- Show familiarity with international standards for common data types
- Manage a typical data acquisition, cleaning, structuring, and analysis workflow using practical examples
- Clean data, and diagnose common problems involved in data corruption and how to fix them
- Understand the concept and fundamentals of databases
- Link data from different sources
- Use the collaboration and version control system GitHub, based on the git version control system.
- Markup Language (XML), and the Markdown format for formatting documents and web pages.
- Create and maintain simple websites using HTML and CSS
- Use APIs to send and retrieve data from Internet sources
π§π»βπ« Our Team
Dr. Jonathan Cardoso-Silva
Assistant Professorial Lecturer
LSE Data Science Institute
π§
Office Hours:
- 15-min slots, on Wednesdays 13:00 β 15:00 during Term Time
- Room: PEL 9.01c (check out the πΊοΈ campus map)
- Book via Student Hub up to 12 hours in advance
Anton Boichenko
Guest Teacher at the LSE Data Science Institute
Product Developer at Decoded
MSc in Applied Social Data Science (LSE)
Amara Otero Salgado
BSc in Politics Data Science
Course Representative for DS105M
Nathaniel Ocquaye
Teaching Support and Events Officer
Office: PEL 9.01
Email:
Jill Beattie
Institute Coordinator
Office: PEL 9.01E
Tel: +44 (0) 20 7955 7759
Email:
π Lecture
Tuesdays 4pm-6pm at PAR.LG.03 (πΊοΈ campus map), except Week 06 (Reading Week)
Class Groups
Group 01
- π Fridays
- β 9:00 - 10:30am
- π 32L.G.06
- π§βπ« Anton
Group 02
- π Fridays
- β 12:00 - 1:30pm
- π NAB.LG.03
- π§βπ« Anton
Group 03
- π Fridays
- β 16:00 - 17:30
- π KSW.1.02
- π§βπ« Anton