Nearly one in four job postings in the US alone require some data science skills and employers are paying up to 14% more for those skills. (Report : ExcelinEd & the Burning Glass Institute).
This powerful specialisation from the University of London and IBM gives you the perfect academic and industry-informed practical introduction to data science. You get:
- Progress transfer for the University of London’s BSc in Computer Science
- The foundational skills and knowledge you need to get a job in a data-rich environment.
During this specialisation, you’ll be introduced to data science, statistics, programming, computational thinking, machine learning, and more. You’ll discover the role of data science in today’s data-driven world. Plus, you’ll get hands-on using IBM’s data science tools, giving you practical experience to talk about in interviews.
Half the teaching is provided by Goldsmiths, University of London, giving you a strong academic foundation. The other half, designed by IBM, provides real-world professional insight supported by practical projects and a capstone project for your resume.
The “Problems and Algorithms in Data Science” course is a great preview of the BSc Computer Science degree with the opportunity to roll your progress into the degree, if you successfully apply and register.
If you’re looking for a solid, practical understanding of data science that unlocks academic and career opportunities, ENROLL today!
Übungsprojekt
There are two Capstone projects that draw together the material across the Data Science Foundations specialization to enable you to apply what you have learned. In one project, students will tackle a prediction problem: forecasting the number of bicycles that will be rented on a given day. Using historical data, students will consider factors such as weather, the day of the week, and other relevant variables to accurately predict daily bicycle rentals. This will help ensure that the bicycle rental service is prepared with the appropriate number of bicycles each day. Students will learn specifically about data acquisition, linear regression, and correlation. In the other project, students will predict if the Falcon 9 rocket's first stage will land successfully and determine the cost of a launch. In doing so, students will apply skills to perform data collection, data wrangling, exploratory data analysis, data visualization model development, and model evaluation.
