Bachelor of Science in Data Science

Collaborative Online Degree

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

This program is authorized, exempt, or not subject to state regulatory compliance and may enroll students from all 50 states.

Many online support services are available to assist you as you progress through the program.

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 BS 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.

• 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

Admissions

Admissions requirements vary by campus.

Degree Requirements (120 cr.)

Students receiving the B.S. in Data Science must complete 120 total credit hours including:

• IU South Bend Campuswide General Education Curriculum (33 cr.)

• Major Requirements (65 cr.)

• Data science core courses, including capstone course (30 cr.)
• Professional Communication courses (6 cr.)
• Computer Science courses (11 cr.)
• Mathematics courses (9 cr.)
• Statistics courses (9 cr.)

• World Languages (6 cr.)
• Physical and Life Sciences (10 cr.)
• Free Electives (balance of credits needed to equal 120 credit requirement)

• A minimum of 33 credit hours at the 300– or 400–level.
• Major requirements must be completed with a grade of C or higher
• A minimum CGPA of 2.0 is required
• All courses are 3 credits, unless otherwise noted.

Major Requirements

Data Science Core (30 cr.)

• CSCI-N 211 Introduction to Database; OR
  CSCI-A 213 Database Applications
• CSCI-N 311 Database Programming, Oracle; OR
  CSCI-B 461 Database Concepts; OR
  CSCI-C 442 Database Systems; OR
  INFO-I 308 Information Representation
• CSCI-N 317 Computation for Scientific Applications
• INFO-I 223 Data Fluency
• INFO-I 416 Applied Cloud Computing for Data Intensive Sciences
• INFO-I 421 Applications of Data Mining
• INFO-I 453 Computer and Information Ethics
• INFO-I 490 Professional Practicum; OR
  INFO-I 491 Capstone
• NEWM-N 328 Visualizing Information
• PBHL-B 452 Fundamentals of Data Management

Professional Communication (6 cr.)

Select one from the following:

• CMCL-C 122 Interpersonal Communication
• COMM-C 180 Introduction to Interpersonal Communication
• COMM-C 223 Business and Profesional Communication
• SPCH-S 122 Interpersonal Communication
• SPCH-S 223 Business and Professional Communication

Select one from the following:

• ENG-W 230 Science Writing
• ENG-W 231 Professional Writing Skills
• ENG-W 233 Intermediate Expository Writing
• ENG-W 234 Technical Report Writing
• ENG-W 270 Argumentative Writing

Computer Science (11 cr.)

• CSCI-A 201 Introduction to Programming I (4 cr.)
  Taught using Python
• CSCI-A 202 Introduction to Programming II (4 cr.)
  Taught using Python
• CSCI-A 343 Data Structures
  Taught using Python

Mathematics (9 cr.)

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

Statistics (9 cr.)

• PBHL-B 275 Probability Without Tears and Without Calculus
  Taught using Python
• PBHL-B 285 Classical Biostatistical Regression Methods; OR
  PBHL-B 302 Biostatistics in Informatics
• PBHL-B 420 Introduction to Biostatistical Learning; OR
  INFO-I 415 Introduction to Statistical Learning

World Languages (6 cr.)

• Successful completion of a second-semester language class, or formal training, as evidenced by secondary or university diplomas, in a language other than English. The Department of World Language Studies (W.L.S.) offers a placement examination to determine into which semester a student should enroll and/or to qualify students for credit by examination.
• Students who have completed at least three years (six semesters) of high school courses in a single world language and have received a grade of C or better would be able to waive this requirement. Consult with your Data Science Advisor.

Physical and Life Sciences (10 cr.)

• Courses in at least two different sciences must be taken (select from Astronomy, Biology, Chemistry, Geology, or Physics)