Curriculum

Students joining our Masters in Data Science at UC San Diego can expect to gain a deep understanding of curating and storing data, analyzing data using statistical and machine learning techniques, presenting their findings, and understanding the ethical implications of their work in data science.

Specifically, by the end of this degree program, students will be able to:

  1. Collect raw data from various sources and extract and transform them into a curated form amenable to algorithmic analysis;
  2. Employ appropriate methods and tools to query, store, manage, and analyze large datasets;
  3. Apply the appropriate statistical, machine learning, deep learning, and/or data visualization techniques to obtain insights from the data and facilitate data-driven decision making;
  4. Create presentations or reports to convey insights from data analysis to audiences at various levels of technical expertise;
  5. Recognize and respond to ethical and societal concerns with data collection, data analysis, and reporting of results.

To achieve these learning objectives, students will take a combination of ten courses.  Seven of these ten courses are required and provide the core of being a data scientist. The remaining three courses are electives, allowing students to specialize in different topics of their interest.  More details on the course can be found below:
 

Foundations (take all 3 courses)

The foundation courses provide the basic background needed in the remainder of the program.
 

Core (take all 3 courses)

The core courses cover the central topics of the program.
 

Electives (Pick any 3 courses)

Students will be able to customize their experience in the program by taking 3 electives. We list here several electives that the program will offer. At launch we plan to have at least 3 electives; within one year after launch, we plan to have at least the 5 electives listed below. Over time, we will add additional electives to provide students with more options.
 

Capstone (1 course)

MDS 298R: Capstone Project in Data Science. This course consists of a quarter-long project. Students will pick one project out of several available options, each project from a different domain. At launch we expect to have projects in: Music, Oceanography, and Computer Vision. Over time, we expect to add additional capstone projects from various disciplines, for example Engineering, Health & Life Sciences, Social Sciences, Physical Sciences, and Arts & Humanities.