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The curriculum includes research design and applications for data and analysis, storing and retrieving data, exploring and analyzing data, identifying patterns in data, and effectively visualizing and communicating data. Like all programs offered by the I School, MIDS features a project-based approach to learning and encourages the pragmatic application of a variety of different tools and methods to solve complex problems.

Graduates of the program will be able to:

  • Imagine new and valuable uses for large datasets;
  • Retrieve, organize, combine, clean, and store data from multiple sources;
  • Apply appropriate data mining, statistical analysis, and machine learning techniques to detect patterns and make predictions;
  • Design visualizations and effectively communicate findings; and
  • Understand the ethical and legal requirements of data privacy and security.

Program Requirements

The MIDS program is 27 units. The program can be completed in 20 months (two to three courses per semester). Students can also choose a more accelerated path and complete the degree in 12 months (three courses per semester). While all course work is delivered online, you are required to attend at least one, 4-5 day immersion on the UC Berkeley campus. You will also be required to complete a synthetic capstone course.

See the full curriculum.

Request more information about [email protected], or speak with an admissions counselor at 855-678-MIDS.

For our launch cohort of students entering in January 2014, only two courses — or 6 units of coursework — will be offered during the Spring 2014 term.


The Master of Information and Data Science is a 12-20 month degree program, but other options are available to complete the program on an accelerated basis.1 You will complete 27 units of course work over three to five terms.2 Courses are divided into foundation courses (15 units), advanced courses (9 units), and a synthetic capstone (3 units). You will also complete an immersion at the UC Berkeley campus.


  • Research Design and Application for Data and Analysis
  • Exploring and Analyzing Data
  • Storing and Retrieving Data
  • Introduction to Machine Learning
  • Visualizing and Communicating Data


  • Really Big Data: Scaling up and Parallelism
  • Experiments and Experimentation with Data
  • Privacy, Security, and Ethics of Data


  • Synthetic Capstone Course

Request more information about [email protected], or speak with an admissions counselor at 855-678-MIDS.

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