What can you expect from BSDS prerequistes DS 1001 and DS 1002?
All students interested in the B.S. in Data Science will need two prerequisite courses: DS 1001 Foundations of Data Science and DS 1002 Programming for Data Science (or an equivalent). But what do these classes actually cover, and how do they prepare you for the major? Here’s a quick overview.
DS 1001 - Foundations of Data Science
In this hands-on course, students don’t just learn about data science, they practice it. From day one, you’ll work on a semester-long project that applies core skills in real-world contexts. Along the way, you’ll explore topics like computing environments, visualization, modeling, and bias analysis.
Class sessions combine interactive lectures, small group discussions, lab-based activities, and guest talks from industry professionals. These experiences build confidence and show how data science connects to research, technology, and problem-solving across fields.
By the end of the semester, students design and execute their own independent project, applying what they’ve learned to a question of their choice.
First-year student Audrey Stelle says the course sparked her interest in data science and gave her a strong foundation for the major. She described DS 1001 as “a web of opportunities in many directions” that introduced her to the School’s four domains—design, analytics, systems, and value—without overwhelming detail too soon. The mix of homework, projects, case studies, and guest speakers helped her see the scope of the field and discover what interested her most.
Her biggest takeaway: data is everywhere, and data science makes it useful. Whether in hospitals, stadiums, or beyond, the ability to turn information into insight is what drives the discipline.
DS 1002 Programming for Data Science
This course builds practical programming skills with a focus on Python. Students learn to write, debug, and structure code, while exploring powerful tools like pandas and NumPy for data analysis.
You’ll gain experience through lectures, live coding demos, in-class exercises, and homework. Core concepts include loops, functions, data structures, and object-oriented programming. In the final weeks, you’ll also practice translating Python skills into R, expanding your versatility.
First-year student Rudra Dave found the class approachable and immediately useful. He especially valued working with Jupyter Notebook, which he described as intuitive and a smooth transition from other coding environments. The focus on labs over exams, he noted, made the course feel practical and applicable to future classes.
If DS 1002 is unavailable, you can complete the prerequisite with CS 1110/1111/1112 Introduction to Programming or PHYS 1655/CS 1113 Introduction to Python for Scientists and Engineers. Students may also meet the requirement with test credit: AP Computer Science A (score of 4 or 5) or IB HL Computer Science (score of 5, 6, or 7).
Next Steps
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