Spring Data Science Global Internships Program London

Summary

Gain first-hand knowledge, connections, and international work experience through an academic internship in London. On this program, you will:

• Undertake a professional internship opportunity to build transferable skills in the field of Data Science
• Earn academic credit for the internship via an online course, Data 197
• Make progress towards your degree via an online offering of Data 100
• Learn about British culture and history through an on-site course
• Live with other program participants in central London
   

About London

The birthplace of Shakespeare and the Beatles, England boasts a rich history and heritage. London is the center of British politics and business and is a world power in media and advertising. London is also deeply multicultural, with one in three Londoners born in another country. Outside of your internship, share a traditional English breakfast with mates, ride to new heights on the London Eye, or whisk around the city on the underground.

Program Details

Dates:

• London: January 20 - May 9, 2026
• Online Courses: January 19 - May 7, 2026

Dates are subject to change.
 

Units: 13 units
 

Language of Instruction: English
 

Three Required Courses:

On-site course:

• TBD (3 units)

And two online Data Science courses:

• Data 100: Principles and Techniques of Data Science (4 units)

• Data 197: Internship in Data Science (6 units)

   

Housing 

Students will live in fully-furnished apartment-style accommodations in central London.

• Students will have access to a shared bathroom and communal kitchen to prepare meals.
• Students will be randomly assigned to shared rooms. Gender-inclusive housing options are available on this program. If you have clarifying questions, please feel free to reach out to the program staff.

Eligibility

• Currently enrolled in a degree program or have graduated within the last 12 months
• At least one year of college coursework completed by the start of the program
• 2.0 GPA or higher
• At least 18 years old at the time of application
• Not on term/academic notice or under censure for student misconduct at any point from application review to the end of your program
• Competed the prerequisites for Data100, including:
  • Foundations of Data Science: Data 8 covers much of the material in Data 100 but at an introductory level. Data 8 provides basic exposure to python programming and working with tabular data as well as visualization, statistics, and machine learning.
  • Computing: The Structure and Interpretation of Computer Programs, CS61A, Computational Structures in Data Science, CS88, or Introduction to Computer Programming for Scientists and Engineers, ENGIN 7. These courses provide additional background in programming (e.g., for-loops, lambdas, debugging, and complexity) that will enable Data 100 to focus more on the concepts in Data Science and less on the details of programming in python.
  • Math: Linear Algebra (MATH 54, STAT 89A, or EE 16A): We will need some basic concepts like linear operators, eigenvectors, derivatives, and integrals to enable statistical inference and derive new prediction algorithms. This may be satisfied concurrently to Data 100, though course staff highly recommend completing linear algebra prior to enrolling in Data 100.
  • Students who are interested in additional data science classes after Data 8 but don’t yet meet the Data 100 requirements should take the prerequisites in the fall semester to be eligible for this program.

Application

• Application opens August 1, 2025 at 9 am PST
• Space is limited and applications are accepted on a first-come, first-served basis
• Deadline to apply is September 24, 2025 at 11:59 pm PST

Internship

The Global Internships team works one-on-one with you to find an internship based on your academic background, experience, interests, as well as employer needs and availability. Data science internships in London are available in a wide variety of fields and internship placement is guaranteed. However, some roles are more competitive than others, and may require prior experience. Internships will be three days a week, with the other two days of the week consisting of program-related coursework and activities.

Examples of past internships:

• Data Science: Interning with a business insight consultancy, students can expect to get involved with data collection, visualisation and evaluation, as well as updating questionnaires producing charts. 
• Business & Data Science: Based within a finance firm, previous students have been involved with data (in lots of forms including research, organization, clearing and modelling), to then use machine learning to power a predictive algorithm. 
• Computer Science: Interning for a start-up computer software company, interns have previously worked on creating web pages, updating websites and data analysis, as well as assisting clients with any issues they have. 

Opportunities can vary year-to-year by such factors as market trends, time of year, and the economy. Common industry sectors/roles for internships include, but are not limited to:

• Artificial Intelligence
• Business Analyst
• Business Intelligence
• Data Analyst (visualisation, cleaning and preparation etc.) 
• Data Scientist/Engineer
• Machine Learning
• Machine Learning Engineering
• Software Engineer/Developer
• Research

Costs

More information to come!

Timeline

More information to come!

Instructors

More information to come!