Degree Pathway for the Data Science Option
For students who entered fall 2025 and beyond.
Freshman Year
Fall Semester
| Course Number | Course Name | Credits |
|---|---|---|
| ENGL.1010 /
HONR.1100 | College Writing I /
First Year Seminar in Honors: Text in the City (CW) | 3 |
| DATA.1010 DATA.1010L OR COMP.1010 COMP.1030L | Data Structures in Python I
Programming Lab I OR Computing I Computing I Lab | 4 |
| MATH.1310 | Calculus I (MATH) | 4 |
| xxxx.xxxx | Social Sciences Perspective (SS)1 | 3 |
| Total | 14 | |
Spring Semester
| Course Number | Course Name | Credits |
|---|---|---|
| ENGL.1020 | College Writing II (CW) | 3 |
| DATA.1020 DATA.1020L OR COMP.1020 COMP.1040L | Data Structures in Python II
Programming Lab II OR Computing II Computing II Lab | 4 |
| MATH.1320 | Calculus II | 4 |
| xxxx.xxxx | Arts and Humanities Perspective (AH)1 | 3 |
| Total | 14 | |
Sophomore Year
Junior Year
Senior Year
Fall Semester
| Course Number | Course Name | Credits |
|---|---|---|
| DATA.3221 | Deep Learning | 3 |
| xxxx.xxxx | Project Pair Course 16 | 3 |
| xxxx.xxxx | Domain Application Elective5 | 3 |
| xxxx.xxxx | Natural Science Elective2 | 4 |
| xxxx.xxxx | Free Elective3 | 3 |
| Total | 16 | |
Spring Semester
| Course Number | Course Name | Credits |
|---|---|---|
| DATA.4900 | Capstone Project (AIL), (WOC) | 6 |
| xxxx.xxxx | Project Pair Course 26 | 3 |
| xxxx.xxxx | Technical Elective4 | 3 |
| Total | 12 | |
Total Minimum Credits = 120
Minimum [major] Credits: 49 (DATA and COMP prefixes)
Maximum [major] credits that can be counted toward graduation: 60
1Core Curriculum:
- No more than two Breadth of Knowledge (BOK) courses can be taken with the same prefix. The Core Curriculum courses may be taken in any sequence. Refer to the Core Curriculum policy for further details. You should meet with your faculty advisor to determine how you will meet the Core Curriculum requirements.
- The Core Curriculum Essential Learning Outcomes for Diversity and Cultural Awareness (DCA) and Social Responsibility and Ethics (SRE) are fulfilled outside the Data Science major. See the DCA course listing and the SRE course listing for a full list of classes that fulfill these requirements.
2Natural Electives:
- Natural Science Electives are courses offered by one of the four natural science departments in the College of Sciences: Biological Sciences, Chemistry, Environmental, Earth, and Atmospheric Sciences, Physics and Applied Physics.
- Each course must include a 3-credit lecture accompanied by a 1-credit lab.
- Courses that fulfill this requirement must be classified as required or elective courses for the majors in those departments.
3Free Electives:
- Free Elective courses must not be below the level of any course specifically required by the Data Science major and cannot simultaneously be used to satisfy any other major or elective requirements.
- A maximum of 60 credits of DATA and COMP courses can be counted towards the minimum 120 credits required to graduate.
4Technical Electives:
- Technical Electives are courses offered by departments in the College of Sciences or the College of Engineering, provided they are not used to satisfy any other requirements and are not INFO courses.
- Courses that fulfill this requirement must be classified as required or elective courses for the majors in those departments.
- To use a DATA course as a Technical Elective, it must be at the 3000 or 4000-level.
- To use COMP course as a Technical Elective, it must be at the 2000, 3000,4000, or 5000-level.
- However, no more than 60 credits of DATA and COMP courses can be counted towards the minimum 120 credits required to graduate.
5Domain Application Electives:
- Domain Application Electives are data-driven courses offered by other departments for their majors, involving the analysis, processing, and management of data.
- Students must select two courses (6 credits) from one of the approved domain areas.
- There are two Domain Application areas:
- Economics (select 2 courses)
- Environmental Sciences (select 2 courses)
Note: Other Domain Application areas may be approved by the department.
6Project Pair Courses:
- A Project Pair consists of two courses, which deepen a student’s knowledge in a specific area in Data/Computer Science.
- The Project Pair is selected from the following list:
- DATA.4701 / DATA.4702 Digital Health I AND Digital Health II
- DATA.4430 / DATA.4701 Text Retrieval and Analytics AND Digital Health I
- DATA.3410 / DATA.4430 Introduction to Natural Language Processing AND Text Retrieval and Analytics
- DATA.4701 / DATA.4501 Digital Health I AND Internet of Things
- DATA.4430 / DATA.4201 Text Retrieval and Analytics AND Image Processing
- DATA.4201 / DATA.4501 Image Processing AND Internet of Things
- COMP.4270 / COMP.4280 Computer Graphics I AND Computer Graphics II
- COMP.4270 / COMP.4230 Computer Graphics I AND Computer Vision I
Note: Other combinations of courses from the pairs listed above may also be used to form a different project pair, subject to the approval of the Program Coordinator.
Current UMass Lowell students should use their Advisement Report in the Student Information System (SiS). If you need assistance, please contact your adviser.
Restriction on off-campus study:
Be advised that any course taken at another institution must be formally approved prior to enrollment. See the catalog policy for details.