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Data science is not just about gaining a technical skill –
it’s about empowerment.

– Md Kamrul Hasan, Ph.D.

is an Assistant Professor of the Practice of Computer Science at ��һ��ݶ�. His research focuses on smartphone-based diagnostic techniques, particularly non-invasive, point-of-care tools. Dr. Hasan’s work explores how smartphone-captured images can be transformed into meaningful signals, with applications such as estimating blood constituent levels.

He earned his Ph.D. from Marquette University. Dr. Hasan was the recipient of the Northwestern Mutual Postdoctoral Fellowship in the Department of Computer Science at Marquette University. After completing a postdoctoral fellowship at ��һ��ݶ� Medical Center, he joined Vanderbilt.

He has received several prestigious awards, including the Arthur J. SchmittLeadership Fellowship (2018) at Marquette University, the Japanese Government Monbukagakusho (MEXT) Scholarship (2014) at Kyushu University, Japan, and the Opera Universitaria Scholarship (2007–2009) from the University of Trento, Italy.

What brought a computer science professor to teaching in the field of Data Science?

“My background spans computer science, data science, and biomedical informatics. Through my research and professional experience, I have learned that data-driven thinking is central to nearly every discipline—from healthcare and finance to sports, education, and public policy. This realization motivated me to continue teaching Data Science, as it allows me to blend the strengths of computer science—problem-solving, algorithms, and programming—with the creativity and real-world impact of interpreting data.

“When I joined the Computer Science department at Vanderbilt, I was invited to design and develop the Data Science course DS/CS 1100 – Applied Programming and Problem Solving with Python in 2021. That opportunity allowed me to integrate all of my previous experience—analyzing data, identifying patterns, and making informed decisions—into building the course syllabus and content. Later, I also developed an online version of DS/CS 1100.

“Since launching this course at Vanderbilt in 2021, I have taught students from diverse academic backgrounds and with varying levels of programming experience. I truly enjoy helping them build meaningful connections between code and the world around them. It is incredibly fulfilling to guide students from writing their first lines of Python to uncovering insights from real datasets.”

Why should a student take DS/CS 1100?

“DS 1100 is designed for Data Science minors who want to learn not only how to write code, but how to use it to answer real questions in their own fields—such as Economics, Electrical Engineering, or Mechanical Engineering. In my class:

• Students learn Python through practical, hands-on exercises rather than by memorizing syntax.
• Students work directly with the instructor during class using Jupyter Notebook. I upload a structured worksheet with datasets to Brightspace—often related to health, sports, or online shopping—so students can learn to explore, visualize, and analyze real data.
• The class is welcoming to beginners. No prior coding experience is required.
• Students leave the course with skills that are directly useful in internships, research projects, and upper-level courses. My goal is for them to say, ‘I can actually do data science,’ not just understand the definitions.”

Why do YOU think Data Science is important?

“Data Science is one of the most powerful tools of our time. We live in a world where decisions—both small and large—are increasingly guided by data. Whether it’s predicting stock market trends, assessing disease risk, improving transportation routes, or even recommending your next movie, data shapes our daily lives.

“If we can collect the right data, interpret it responsibly, and turn numbers into meaningful insights, we can make truly data-driven decisions. Data Science equips students with the ability to understand the world more deeply and to make informed, ethical choices.

“No matter what career path a student pursues—business, medicine, engineering, the social sciences, or the arts—data literacy is now essential. I believe that learning data science is not just about gaining a technical skill; it’s about empowerment.”