LSE DS202 – Data Science for Social Scientists

Author

Dr Jon Cardoso-Silva

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📑 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

🎯 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).

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