University of Illinois Urbana-Champaign School of Information Sciences 51 courses 36 total credits
for the degree of Master of Science in Bioinformatics, Information Sciences Concentration A typical student will take 6 required courses (24 hours) 1 Biology, 1 Computer Science, 1 Fundamental Bioinformatics, and 3 Information Sciences. The student must then choose 3 courses (12 hours) of electives to complete the degree. It is strongly encouraged that up to 2 courses of these electives (8 hours) are thesis. Our expectation is that each student will arrange a custom program of study, suitable for the information management of their particular biological informatics application. Currently, this program requires students to be in residence in Champaign-Urbana. The School of Information Sciences (iSchool) offers programs of study leading to the Master of Science (M.S.), the Certificate of Advanced Study (C.A.S), and the Doctor of Philosophy degrees. Three Master of Science (M.S.) degrees are available. The M.S. in Library and Information Science (L.I.S.) prepares students for professional careers in all types of information organizations, including libraries. The M.S. in Information Management (I.M.) will prepare the students for information-intensive professional roles in a broad range of sectors. The Information Sciences concentration of the campus-wide M.S. in bioinformatics program emphasizes multidisciplinary skills that are required for a career developing and managing information systems for the biological sciences community. The C.A.S. program provides the opportunity
| Total Hours | 36 credits |
Thesis or Non Thesis Option
Computer Science and Informatics (choose one) (4 hours) CPSC 565. Fundamental Bioinformatics (choose one) (4 hours) ANSC 545. Biology (choose one) (4 hours)
Data Stewardship
Data Analytics
| Code | Course Title | Credits |
|---|---|---|
| IS 407 | Introduction to Data Science | 4 |
| IS 445 | Data Visualization | 3-4 |
| IS 507 | Data, Statistical Models and Information | 4 |
| IS 527 | Network Analysis | 4 |
| IS 557 | Applied Machine Learning: Team Projects | 4 |
| IS 567 | Text Mining | 4 |
| IS 577 | Data Mining | 2-4 |
System Policy & Design
Electives
For Thesis Option up to 8 hours:
| Code | Course Title | Credits |
|---|---|---|
| IS 424 | Social Computing | 3-4 |
| IS 464 | Information Assurance | 3-4 |
| IS 517 | Methods of Data Science | 4 |
| IS 571 | Advanced Topics in Use and Users of Information | 2-4 |
| INFO 591 | Grad Bioinformatics Seminar | 0-2 |
| IS 599 | Thesis Research | 0-16 |
| Total Electives | 12 credits | |
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