In the Information Age, enormous amounts of data are generated every day in a range of areas, including social media, search engines, insurance companies, healthcare organizations, hospitals, defense, and retail. Data science is now a rapidly growing, high-paying field.   

As a student in the IU Online B.S. in Data Science, you collect, organize, and analyze data to make meaningful conclusions. You write programs to perform data analysis on large, complex datasets. You evaluate the social, legal, and ethical issues that arise from the mass collection of data.   

Specific areas of focus include:  

• Data acquisition and storage 
• Data exploration and curation 
• Data modeling and analysis 
• Data visualization and presentation 
• Data ethics and governance  

Your IU Online BS in Data Science prepares you for such careers as:   

• Business intelligence analyst  
• Data mining engineer, data architect, data scientist  
• Analytics manager  
• Research analyst   
• Information officer   

This 100 percent online, consortial program is taught by IU East, IUPUI, IU Kokomo, IU Northwest, IU South Bend, and IU Southeast. This consortial model allows you to take coursework from several campuses and learn from a wide range of faculty.  

Services and Resources

Students admitted to IU Online receive a full range of personalized services including:

• Onboarding
• Advising
• Success Coaching
• Math and Writing Support
• Career Services
• Peer Mentorship
• Tutoring

Degree Requirements   

Students must complete general education and college/school requirements as directed by the campus of residence, as well as the following Data Science requirements, to total at least 120 credit hours.  

Major Requirements

Professional Communication (6 cr.)

Select one from the following:

• CMCL-C 122 Interpersonal Communication (3 cr.)
• COMM-C 180 Introduction to Interpersonal Communication (3 cr.)
• COMM-C 223 Business and Professional Communication (3 cr.) 
• SPCH-S 122 Interpersonal Communication (3 cr.)
• SPCH-S 223 Business and Professional Communication (3 cr.)

Select one from the following:

• ENG-W 230 Science Writing (3 cr.)
• ENG-W 231 Professional Writing Skills (3 cr.)
• ENG-W 233 Intermediate Expository Writing (3 cr.)
• ENG-W 234 Technical Report Writing (3 cr.)
• ENG-W 270 Argumentative Writing (3 cr.)

Computer Science (11 cr.)

• CSCI-A 204 Introduction to Programming I (4 cr.) Taught using Python 
• CSCI-A 205 Introduction to Programming II (4 cr.) Taught using Python 
• CSCI-A 310 Data Structures (3 cr.) Taught using Python 

Mathematics (9 cr.)

• MATH-M 220 Calculus for Data Science I (3 cr.)
• MATH-M 230 Calculus for Data Science II (3 cr.)
• MATH-M 301 Linear Algebra and Applications; (3 cr.) OR 
  • MATH-M 303 Linear Algebra for Undergraduates (3 cr.)

Statistics (9 cr.)

• PBHL-B 275 Probability Without Tears and Without Calculus (3 cr.) Taught using Python 
• Biostatistics – Choose one of the following:  
  
  • CSCI-C 337 Introduction to Biostatistics (R-based) (3 cr.); OR 
  • PBHL-B 304 Biostatistics for Health Data Scientists a Computational Approach (3 cr.)
• PBHL-B 384 Classical Biostatistical Regression Methods (R-based) (3 cr.)

Data Science Core (30 cr.)

• Capstone Experience – Choose one of the following: 
  • INFO-I 491 Capstone Project Internship; OR  
  • INFO-I 492 Senior Thesis 
• CSCI-C 442 Database Systems  
• CSCI-N 317 Computation for Scientific Applications 
• INFO-I 308 Information Representation 
• INFO-I 416 Applied Cloud Computing for Data Intensive Sciences 
• INFO-I 421 Applications of Data Mining 
• INFO-I 453 Computer and Information Ethics 
• NEWM-N 328 Visualizing Information 
• PBHL-B 352 Fundamentals of Data Management  
• Statistical Learning – Choose one of the following: 
  • INFO-I 415 Introduction to Statistical Learning; OR 
  • PBHL-B 420 Introduction to Statistical Learning 

You can transfer up to 64 credit hours from a regionally accredited community college, or 90 credit hours from an accredited four-year university or college.