Across both units in the module, students gain a comprehensive introduction to scientific computing, Python, and the related tools data scientists use to succeed in their work. Students will develop machine learning and statistical analysis skills through hands-on practice with open-ended investigations of real-world data.
All students receive complimentary access to a ready-to-use Python environment for the entire module. This allows students to gain first-hand experience with Python, pandas, and Jupyter Notebooks, and allows for immediate immersion into novel data science problems.
The Introduction to Data Science module is built by Worldquant University’s partner, The Data Incubator, a fellowship program that trains data scientists. Graduates earn a certificate upon completion of each unit.
The Introduction to Data Science module is delivered entirely online so students can earn their certificate without disrupting their lives.
Students who successfully complete Unit I earn a certificate and an invitation to enroll in Unit II. Those who successfully complete Unit II earn an overall certificate. Students have the opportunity to complete either unit of the module with honors.
Across two units and sixteen weeks, students learn to source data relevant to a business problem or task, to summarize data in aggregate statistics and visualizations, and to model trends to showcase insights and make practical business decisions.
In Unit I, students gain a comprehensive introduction to scientific computing, Python, and the related tools data scientists use to succeed in their work. Successful completion of Unit I is a required prerequisite for enrollment in Unit II.
In Unit II, students develop machine learning and statistical analysis skills through hands-on practice with open-ended investigations of real-world data. Students can expect to work with authentic public data sets from organizations like the NHS, or anonymized data on credit card defaults. This unit has a heavy emphasis on creative use of the tools of data science to solve problems from multiple perspectives.
This is a true introduction to data science and can accomodate beginners with the right amount of foundational knowledge. It does not require you to have any prior degrees.
To qualify for the course you must have experience with algebraic concepts such as functions and variables, which are frequently used in programming.
Preference is given to applicants with familiarity in programming fundamentals, basic statistics, linear algebra, and calculus.
Students should expect to commit roughly 8 to 10 hours per week between lecture videos, assignments and individual study.
The module runs four times each calendar year. We strongly encourage all qualified candidates to apply soon, as space in each class is limited and initial interest is high.