Data Science Foundational Materials (DATA 601/602)
Introduction
The Data Science and Analytics Professional Master's Program is a rigorous, fast-paced, and highly intensive graduate program designed for motivated learners who are prepared to engage with challenging quantitative and analytical material from the very beginning.
Your first term includes two foundational core courses: DATA 601 – Working with Data and Visualization and DATA 602 – Statistical Data Analysis. Success in these courses requires a strong command of prerequisite knowledge, particularly in mathematics, probability, statistics, and introductory programming (preferably Python).
Your admission to this program was based, in part, on your academic record demonstrating competency in these prerequisite areas. As such, we expect all incoming students to begin the program with these foundational skills already in place.
To support your preparation, we have developed the resources on this website as a refresher of the key concepts that underpin the first-term curriculum. We strongly encourage you to work through all modules during the month leading up to the start of the program and use this time to strengthen any areas where your knowledge may have become rusty.
We encourage you to view this preparation period as an investment in your success. Arrive ready to build upon your existing knowledge, take full advantage of these resources, and begin your journey with confidence.
We look forward to welcoming you to the program and supporting your success.
DATA 601 Foundational Materials
DATA 601 introduces the fundamental concepts and tools that form the foundation of modern data science. The course covers data organization, data collection, data cleaning, programming in Python, algorithmic problem solving, and data visualization. While the course includes a review of basic programming concepts, students are expected to enter the program with prior exposure to programming and computational thinking.
The modules provided here are designed to refresh the prerequisite programming knowledge expected of all incoming students and help prepare you for the pace and rigor of the course.
DATA 602 Foundational Materials
DATA 602 assumes a working knowledge of probability and probability distributions and builds rapidly into statistical inference, including estimation, hypothesis testing, simulation-based inference, and statistical modeling in R. The three modules provided here are designed to refresh these prerequisite concepts and help ensure you are ready for the pace and rigor of the course.