MS in Data Science and Analytics - STEM, University of Oklahoma

Norman, Oklahoma

24 Months

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About this course

The Master’s in Data Science and Analytics offers students a comprehensive curriculum focused on core areas like computing structures, database management, algorithm analysis, and statistical analysis, along with advanced analytics and data-driven decision-making. The program comprises either a thesis or non-thesis path, with coursework designed to develop practical skills in intelligent data analytics and metaheuristics. Students also engage in professional practice through an internship or practicum, providing real-world experience. The program aims to prepare students for careers in data science, analytics, and related fields, emphasizing both theoretical foundations and applied skills.

Why this course is highly recommended

This master’s program is designed for students looking to gain both theoretical knowledge and practical experience in data science. With a curriculum that balances core technical courses and hands-on internships, students are well-prepared for the evolving demands of the data industry. The inclusion of electives allows customization of learning pathways, and the STEM focus makes it a compelling choice for those interested in advanced analytics and AI applications. The option to choose between thesis and non-thesis paths provides flexibility depending on academic and career aspirations.

Specialisation

This program offers a focused study in data science and analytics, covering essential technical domains such as database management, algorithm analysis, and statistical analysis. The coursework also emphasizes advanced analytics techniques and metaheuristics, enabling students to develop expertise in intelligent data analysis and data-driven strategies. Students have the flexibility to select electives within CS, ISE, or DSA to tailor their specialization according to their interests and career goals.

Course fees

Application fees

1st year tuition fees

17.79L

Living cost

Degree requirements

For the master’s degree, students must complete a total of at least 30 or 33 credit hours depending on whether they opt for the thesis or non-thesis path. All coursework must be graduate-level credit, and students need an overall GPA of 3.0 or higher to qualify for graduation. The thesis option requires research completing 6 hours of thesis work, while the non-thesis route includes additional elective hours. Both paths demand satisfactory graduate work over at least two semesters.

English language test

IELTS

6.5

TOEFL

PTE

DUOLINGO

Career prospects

Graduates of this program can expect to find opportunities in data analysis, data science, machine learning, and analytics roles across diverse industries such as technology, finance, healthcare, and consulting. The program’s focus on practical skills and internship experience enhances employability, preparing students to tackle real-world data challenges and advance their careers in analytics-driven fields.

FAQs

What are the minimum credit hours required for the thesis and non-thesis options?

The thesis option requires at least 30 credit hours, while the non-thesis option requires a minimum of 33 credit hours.

Can core courses be substituted?

Yes, core courses may be replaced with additional graduate electives at the discretion of the Graduate Liaison.