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PROGRAM OVERVIEW

Students pursuing a degree in Data Science and Analytics receive a Bachelor of Science (B.S.). The program offers a range of elective courses that allow students to specialize within their field, including:

• Machine Learning
• Statistical Modeling
• Big Data Technologies
• Predictive Analytics
• Data Visualization

A minor is also available.

WHY STUDY DATA SCIENCE AND ANALYTICS AT GRAND VALLEY?

Computing professionals who want to take their expertise or career to the next level can take advantage of Grand Valley's highly-credentialed and well-connected faculty.

• Accredited by the Computing Accreditation Commission of ABET, abet.org.
• The program offers a variety of electives and minors, so students can tailor their education to their interests.
• The curriculum is a combination of theoretical foundation and applied computing, giving students a competitive edge in the job market.
• Students gain practical experience through extensive internship opportunities available through the School of Computing.
• Dedicated computer labs with state-of-the-art equipment ensure relevant, hands-on experience.

COURSEWORK

The Data Science and Analytics program blends core classes in data science with specialized applications. Key courses in the curriculum include:

• Data Structures and Algorithms
• Information Visualization
• Statistical and Predictive Analysis
• Machine Learning 
• Database
• Artificial Intelligence
• Big Data Technologies

  Advising Plans  Course Descriptions

ADMISSION REQUIREMENTS

Admission to major standing in data science and analytics is competitive and requires a secondary application. Applicants must meet the following criteria:

• Overall GPA of 2.5 or above in all Grand Valley State University coursework
• Completion of each course in data science and analytics foundation with a grade of C or above (C- is not sufficient)
• GPA of 2.5 or above in the data science and analytics foundation.
• A minimum of 9 credits of foundation must be taken at GVSU.
• The data science and analytics foundation include: 
  • CIS 161-Computing for Data & Science I
  • CIS 164-Computing for Data & Science II
  • MTH 204 
  • STA 215 
  • STA 216
  • DSA 220

Completing the data science and analytics course requires a programming, mathematical, statistical, analytical reasoning, and communication skills.

The data science and analytics foundation GPA is calculated on more than one repeat per course. Achievement of the minimum requirements does not guarantee admission to the major.

Students are encouraged to apply for admission during the semester when enrolled in the last required foundation classes.

COMBINED DEGREE PROGRAMS

This undergraduate degree can be combined with a master's degree to save you time and money, and get you into the workforce sooner. On average, students save $8,500 in our combined degree programs and take up to four fewer classes than if earning the degrees separately.

You can even build your own combined degree from programs in different disciplines to further personalize your education and meet specific career goals.

CAREER OPTIONS

Job opportunities in the data science and analytics industry are growing rapidly, particularly in occupations such as:

• Data Scientist
• Data Analyst
• Machine Learning Engineer
• Business Intelligence Analyst
• Data Engineer
• Quantitative Analyst

REAL-WORLD EXPERIENCE

Hands-on learning and other fieldwork not only deepen your mastery of your discipline but also give you the edge employers seek. Visit our experience matters page to see the work GVSU students are doing in their co-ops and internships.

SKILLS EMPLOYERS WANT

The B.S. in Data Science and Analytics at GVSU is designed to develop the essential skills required in the fast-evolving data-driven marketplace. From specialized technical abilities to broad analytical expertise, you will acquire a robust portfolio of qualifications that will appeal to a wide range of employers. Skills cultivated in this program, drawn from actual job postings in data science and analytics, include:

• Programming Languages: Python (especially with libraries like Pandas, NumPy, Scikit-learn), R, SQL
• Data Visualization: Tableau, Power BI, Matplotlib
• Statistics and Machine Learning: Statistical methods, Machine learning algorithms
• Cloud Computing: AWS, Azure, Google Cloud Platform
• Critical Thinking and Problem-Solving
• Communication (written and verbal)
• Collaboration
• Business Acumen

Source: EMSI, 2024

LOCATION & FORMAT

Undergraduate students in this major study at Grand Valley's Allendale Campus.

Format:

• Face To Face

HELPFUL LINKS

• Scholarships
• Financial Aid
• Tuition & Fees
• Study Abroad
• General Education Handbook
• Computer Science Programs