The Master of Science in Data Science program is designed as a STEM offering to prepare students for careers in big data. It covers essential skills like machine learning, modeling, and the analysis of large datasets, with an emphasis on applying these technologies for strategic decision-making. Students learn how to gather and manage massive amounts of data efficiently and implement solutions to real-world big data problems using algorithmic techniques and software tools. The program combines core courses with elective options that include data analytics, biostatistics, bioinformatics, business intelligence, and cyber security, giving students a well-rounded education in the field.
Why this course is highly recommended
The course provides a comprehensive curriculum aligned with industry needs, focusing on practical skills in handling big data and advanced analytical techniques. Its flexible study options, including online and evening courses, support working students, making it accessible for a diverse range of backgrounds.
The program offers a variety of electives related to data analytics, biostatistics, bioinformatics, business intelligence, and cyber security, allowing students to tailor their learning experience to their interests and career goals.
Application fees
20.63L
1st year tuition fees
20.63L
Living cost
To complete the program, students need to earn 30 credit hours, which include four breadth-requirement courses. There is a thesis option involving 24 coursework credits plus 6 thesis research credits, and a non-thesis option with 30 coursework credits. Students can typically finish within 12 to 24 months, depending on their course load.

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Want to learn more about the admission process, eligibility criteria,
and acceptance rates for international students? Visit the University of Alabama at Birmingham admission page
for complete details.
Graduates of the MSDS program are equipped to pursue careers in data science, big data analytics, biostatistics, bioinformatics, business intelligence, and cybersecurity, leveraging their skills in machine learning, data management, and software development.