BSIT Data Science Concentration
The Department of Information Technology offers a Bachelor of Science degree in Information Technology with a concentration in Data Science.
As an aspiring data scientist, you are the force driving our ability to use big data. As an IT student with a concentration in data science you will:
- Analyze big data sets to gain actionable insights to help businesses work smarter and make better decisions.
- Gain a solid understanding of the life cycle approach to data analytics.
- Use the tools and techniques necessary to solve problems in big data and data analytics.
Read more about big data and the emerging data science scene at Georgia Southern.
View the BSIT Data Science concentration in the university catalog.
What’s Different About the Data Science Concentration?
In addition to common IT core courses, the data science degree also requires courses that focus on the skills needed to manage big data:
IT 3230 Data Visualization – This course introduces students to the field of data visualization. The course covers basic design and evaluation principles to prepare and analyze large datasets, and standard visualization techniques for different types of data. The course prepares students to communicate clearly, efficiently, and in a visually compelling manner to a variety of audiences.
IT 4136 Knowledge Discovery and Data Mining – The course covers the process of automatically extracting valid, useful, and previously unknown information from data sources and using the information to make decisions. This course is designed to provide students with a solid understanding of the knowledge discovery process and the use of data mining concepts and tools as part of that process.
IT 5135 Data Analytics – This course covers the basic issues involved in building and populating a data mart to support the planning, designing and building of business intelligence applications and data analytics. Core concepts related to business intelligence and analytics are covered. For graduate students a significant research project will be assigned as a culminating experience.
CISM 4237 Business Intelligence – This course is an introduction to business intelligence and business analytics. Students will be exposed to recent technological developments in these areas, as well as best practices.
CISM 4239 Advanced Business Analytics with SAP HANA – This course covers advanced practices and concepts in the areas of business intelligence and business analytics. The course will emphasize more the data foundation required to support business intelligence and business analytics, rather than associated applications. Special emphasis will be given to the SAP HANA big data platform.
IT 2430 Data Programming 1 – The course provides students with an introduction to the main concepts in programming including variables, expressions, statements, conditional execution, functions, iteration, strings, and files.
IT 2431 Data Programming 2 – The course provides students with an introduction to the main concepts in programming related to data. The course focuses on data storage, using regular expressions to search data, interaction with a database, and visualization of data.
IT 3432 Advanced Analytics Programming – The course provides students with the necessary tools and techniques to manipulate, process, clean and analyze data at an advanced level using Python. Specifically, students will use IPython, NumbPy, and pandas to load, clean, transform, visualize and analyze data.
Big Data Capstone
IT 4137 Data Science and Big Data Analytics Capstone Project – This course covers the process of analyzing big data sets to potentially gain actionable insights for an organization. This course provides students with a solid understanding of the life cycle approach to data analytics and the tools and techniques necessary to solve problems in big data and data analytics.
Curriculum & Program Requirements
Curriculum Flow Chart
Students starting fall of 2015 who are interested in the Data Science Concentration can use this flow chart to select courses appropriate to the program.
Area A1 – Communication Skills (6 Hours)
Area A2 – Quantitative Skills (3 Hours)
- MATH 1441 – Calculus 1 (4)
Area B – Global Engagement (4 Hours)
Area C – Humanities, Fine Arts, and Ethics (6 Hours)
- COMM 1110 – Principles of Public Speaking (3)
Area D – Natural Sciences, Mathematics, and Technology (11 Hours)
- STAT 2231 – Introduction to Statistics I (3)
Area E – Social Sciences (12 Hours)
Area F – Courses Appropriate to Major (18 Hours)
- IT 1130 – Introduction to Information Technology (3)
- IT 1430 – Web Page Development (3)
- IT 2333 – IT Infrastructure (3)
- IT 2430 – Data Programming I (3)
- MATH 2130 – Discrete Mathematics (3)
- WRIT- 2130 Technical Communications (3)
Health and Physical Education Activities (4 Hours)
- HLTH 1520 – Healthful Living (2)
- Physical Educational Activities (2)
Orientation (2 Hours)
Specific Requirements Beyond Area A1-F (9 Hours)
- BUSA 3132 – Applied Statistics and Optimization (3)
- MGNT 3430 – Operations Management (3)
- STAT 2232 – Introduction to Statistics II (3)
Major Requirements (39 Hours)
- CISM 3134 – Data Communications (3)
- CISM 4237 – Business Intelligence (3)
- CISM 4239 – Advanced Business Analytics with SAP HANA (3)
- IT 2431 – Data Programming II (3)
- IT 3230 – Data Visualization (3)
- IT 3233 – Database Design and Implementation (3)
- IT 3234 – Systems Acquisition Integration and Implementation (3)
- IT 3432 – Advanced Analytics Programming (3)
- IT 4130 – Information Technology Issues and Management (3)
- IT 4136 – Knowledge Discovery and Data Mining (3)
- IT 4790 – Internship in Information Technology (3)
- IT 5135 – Data Analytics (3)
- IT 4137 – Data Science and Big Data Analytics (3)
Electives (12 Hours)
- No more than 3 hours of electives in IT, CSCI, and CISM courses
ADVISEMENT: College of Information Technology Office of Student Services, Room 1208, College of Information Technology, Telephone: (912) 478-4877.
OTHER PROGRAM REQUIREMENTS: A minimum grade of “C” is required in all Major Requirements.
Last updated: 4/26/2017