The focus of the specialization in Computational (Data) Analytics is to allow students to further explore and specialize in the areas of large-scale data analytics and architectures from theory to practice with more of a computational focus. This ranges from Machine Learning, Text and Linguistic Analytics, Graph Analytics, Visual Analytics to Map Reduce, noSQL Databases, Analytics in Cybersecurity, High Performance Computing and Cloud Computing.
Specialization Educational Objectives
In addition to the core objectives, a student graduating with a Bachelor of Science degree with a major in Data Analytics with a specialization in Computational Analytics will demonstrate:
- an understanding of the principles governing an advanced computational focus area (Cyber-security, Machine Intelligence, Systems/Theory, Linguistics and Text analytics).
- an advanced understanding of and the ability to use analytic techniques in one or more focus areas.
Degree Planning Resources
These documents outline the prerequisite structure within the core curriculum and demonstrate how students flow through the required courses for the Data Analytics major with a specialization in Computational Analytics. They should be used as guides only. Semester course offerings are subject to change.
Since AU 2022 with NEW GE (GEN)
Before AU 2022 with LEGACY GE (GEL)
Specialization Requirements
Students in the Computational Analytics specialization must take 10 credit hours of coursework from the electives listed below and also complete a 4 credit hour capstone course. Courses are grouped to show possible focus areas but students may select any combination of courses (having met appropriate pre-requisites) to meet the 14 credit hours requirement.
- LING 2000*: Introduction to Linguistics (3 cr hrs)
*As noted on the GE advising page, students choosing the Linguistics and Text Analytics focus should take Linguistics 2000. This course is a pre-req for the Ling 4x00 courses and may also be used to satisfy the Cultures & Ideas GE.
Electives: Cyber-security Focus
- CSE 3461: Computer Networking and Internet Technologies (3 cr hrs)
- CSE 4471: Information Security (3 cr hrs)
- Choose one of the following:
- CSE 591x/STAT 4911**: Capstone in Data Analytics (4 cr hrs)
Electives: Machine Intelligence Focus
- CSE 2331: Foundations II: Data Structures and Algorithms (3 cr hrs)
- CSE 3521: Survey of Artificial Intelligence I: Basic Techniques (3 cr hrs)
- Choose two of the following courses:
- CSE 591x/STAT 4911**: Capstone in Data Analytics (4 cr hrs)
Electives: Core (Systems or Theory) Focus
- Choose one of the following:
- CSE 3901, 3902, 3903: CSE Junior Project Choice (4 cr hrs)
- Choose one of the following courses:
- CSE 591x**: CSE Capstone Course (4 cr hrs)
Electives: Linguistics and Text Analytics Focus
- LING 5801: Computational Linguistics I (3 cr hrs)
- LING 5802: Computational Linguistics II (3 cr hrs)
- CSE 5525: Foundations of Speech and Language Processing (3 cr hrs)
- Choose one of the following:
- CSE 591x/STAT 4911: Capstone in Data Analytics (4 cr hrs)
***The Department of Computer Science and Engineering offers numerous capstone courses that vary by topic. Data Analytics majors may choose any course numbered 591x for which they meet the prerequisites (CSE 2501 prereq is not enforced). CSE 5914, 5915, and 5916 are preferred. The Department of Statistics also offers a capstone course numbered STAT 4911 that can be taken in place of the CSE capstone options.
[pdf] - Some links on this page are to .pdf files. If you need these files in a more accessible format, please contact data-analytics@osu.edu.