Data Science | Harvard University CS109 Course

Comprehensive introduction to data science, covering data wrangling, analysis, and machine learning. Prepares students for real-world data science challenges.

Introduction

Learning from data in order to gain useful predictions and insights. This course introduces methods for five key facets of an investigation: data wrangling, cleaning, and sampling to get a suitable data set; data management to be able to access big data quickly and reliably; exploratory data analysis to generate hypotheses and intuition; prediction based on statistical methods such as regression and classification; and communication of results through visualization, stories, and interpretable summaries.

Highlights

• Covers a broad range of topics in data science, including data cleaning, visualization, analysis, and machine learning
• Teaches students to use tools such as Python to work with data and build statistical models
• Includes a significant group project component where students apply their skills to a real-world data science problem
• Provides a solid foundation in data science and prepares students for further study in the field

Recommendation

This course is well-suited for students with some prior programming experience who are interested in learning the fundamentals of data science. It offers a comprehensive introduction to the field and equips students with the necessary skills to tackle real-world data science problems.