Data Science and Analytics Track
Using DIDA as a data science minor is a very popular choice. Data science is a broad field focused on modeling and analyzing data, using statistics, machine learning and other methods. Data analysts use many of the same tools and methods as data scientists, with the goal of finding insights and translating results into recommendations for action.
Students from any field may find this track helpful for their career goals. This track offers students in STEM and the social sciences an opportunity to complement the theoretical skills from their fields with applied programming and data skills. Students in the humanities and arts may wish to add these skills to their portfolio and work in careers such as data journalism or marketing research.
We recommend that all students interested in data science get an introduction to working with data and data management in several languages, including Python, R and SQL. This should be combined with advanced courses in statistics, machine learning or programming.
Careers
Internships and job titles of recent graduates include:
- Sports Analyst (FanDuel)
- Sales Analyst (Bloomberg)
- Decision Science Analyst (Axtria)
- Data Analyst (Toshi Stay)
- Data Analyst (Syracuse University)
- Software Engineer (Optum)
Track Requirements
One course in data management:
- DIDA 110: Database Fundamentals (SQL)
One course in advanced statistics, machine learning or programming (any of the following):
- DIDA 340: Intro to Deep Learning (Python)
- DIDA 380B: Advanced Data Models (R)
- DIDA 380I: Algorithms for Bioinformatics
- Economics majors can take ECON 466 or 467, 502 or 504 for this requirement
- Math majors can take MATH 455 or 457 for this requirement
One additional course, either another of the above or:
- DIDA 260: Data Visualization
- DIDA 310: Text Mining (Python)
- DIDA 370: Spatial Fundamentals (R)
- DIDA 380J: Data Journalism (R)
- GEOG 360: Intro to GIS
Language Breadth:
- Students should gain proficiency working with data in both Python and R. The electives above can fulfill this requirement, as can some statistics courses and the methods class.
- Taking DIDA 130, ANTH 200 or MATH 448 for your statistics requirement covers R skills.
- The core methods course, DIDA 325, is offered both in R and Python.
BA and BS in Data Science & Statistics
Students interested in a major should consider Data Science & Statistics in the Mathematics major. A DIDA minor supplements that major with courses in data science that can be taken starting in freshman year with a focus on applications to real-world data and projects.
Students in that program need only three (3) courses on top of their major to complete the minor, no matter which electives are chosen. A suggested track is shown below; courses in bold satisfy requirements for both programs.
Sample Courses
| DIDA Requirement | Data Science | Data Analytics |
Mathematics |
| Programming | HARP 150 | HARP 150 | HARP 150 or CS 110 |
| Statistics | MATH 147 | DIDA 130 (R) |
MATH 448 (R) |
| Intro Elective | DIDA 110 (SQL) | DIDA 110 (SQL) | DIDA 110 (SQL) |
| Free Elective | DIDA 340 (Python) | DIDA 260 | DIDA 260, 370, or 380I |
| Upper-level Elective | DIDA 380B (R) | DIDA 380B (R) | MATH 455 or 457 |
| Methods | DIDA 325 (R or Python) | DIDA 325 (Python) |
DIDA 325 (Python) |
| Capstone | DIDA 425 or 426 | DIDA 426 |
DIDA 425 or 426 |