LSE DS202 (2022/2023)
Data Science for Social Scientists
π Course Brief
Focus: learn and understand the most fundamental machine learning algorithms
How: practical use of machine learning techniques and its metrics, applied to relevant data sets
π― Learning Objectives
- Understand the fundamentals of the data science approach, with an emphasis on social scientific analysis and the study of the social, political, and economic worlds;
- Understand how classical methods such as regression analysis or principal components analysis can be treated as machine learning approaches for prediction or for data mining.
- Know how to fit and apply supervised machine learning models for classification and prediction.
- Know how to evaluate and compare fitted models, and to improve model performance.
- Use applied computer programming, including the hands-on use of programming through course exercises.
- Apply the methods learned to real data through hands-on exercises.
- Integrate the insights from data analytics into knowledge generation and decision-making.
- Understand an introductory framework for working with natural language (text) data using techniques of machine learning.
- Learn how data science methods have been applied to a particular domain of study (applications).
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
Dr. Stuart Bramwell
ESRC Postdoctoral Fellow
Department of Methodology
PhD in Politics (Oxford)
π§
Yijun Wang
Guest Teacher at the LSE Data Science Institute
PhD candidate in Health Informatics (KCL)
MSc in Data Science (KCL)
π§
Mustafa Can Ozkan
Guest Teacher at the LSE Data Science Institute
PhD candidate in the Spacetime Lab (UCL)
MSc in Transport (Imperial/UCL)
π§
Xiaowei Gao
Guest Teacher at the LSE Data Science Institute
PhD candidate in the Spacetime Lab (UCL)
MSc in Data Science (KCL)
π§
Anton Boichenko
Guest Teacher at the LSE Data Science Institute
Product Developer at Decoded
MSc in Applied Social Data Science (LSE)
π§
Zhang Ruishan (Yoyo)
1st Year BSc Economics Student
Course Representative for DS202
Rachitha Raghuram
2nd Year BSc Economics Student
Course Representative for DS202
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:
Class Groups
Group 01
- π Mondays
- β 09:00 β 10:30
- π PAN.1.03
- π§βπ« Xiaowei
Group 02
- π Mondays
- β 10:30 β 12:00
- π PAN.1.03
- π§βπ« Xiaowei
Group 03
- π Mondays
- β 13:00 β 14:30
- π MAR.1.09
- π§βπ« Stuart
Group 04
- π Fridays
- β 16:00 β 17:30
- π NAB.1.04
- π§βπ« Stuart
Group 05
- π Mondays
- β 09:00 β 10:30
- π 32L.LG.11
- π§βπ« Mustafa
Group 06
- π Mondays
- β 10:30 β 12:00
- π 32L.LG.11
- π§βπ« Mustafa
Group 07
- π Fridays
- β 09:30 β 11:00
- π CBG.2.06
- π§βπ« Yijun