Build the skills to succeed in a world driven by data and artificial intelligence.
From business and healthcare to sports and technology, every industry is being transformed by data and AI. At Lander, our Data Science program prepares you to be part of that transformation—equipping you with the skills to analyze data, build intelligent systems and make informed decisions that matter.
You won’t just learn theory, you’ll gain hands-on experience solving real-world problems using modern tools and technologies.
Data science and artificial intelligence are deeply connected fields. Data science focuses on collecting, managing, analyzing and interpreting data to support decision-making. Artificial intelligence builds on those data science foundations by enabling systems to learn from data, make predictions, automate tasks and support intelligent decision-making. At Lander, you’ll learn how data science and AI work together across the full problem-solving pipeline – from data collection and analysis to modeling, prediction and action.
You will also explore the ethical and responsible use of data and AI, preparing you to apply these technologies thoughtfully in real-world settings.
Skills That Set You Apart
Develop the in-demand skills needed to succeed in today’s data-driven, AI-powered world:
Apply what you learn in a capstone experience where you solve real-world problems using data science and artificial intelligence.
Program Goals
Graduates of Lander’s Data Science program will demonstrate:
Real-World Learning Experience
Data science and AI are most powerful when applied to real problems. That is why Lander’s program emphasizes hands-on, practical learning. Students work with real datasets, modern software tools and AI methods that reflect today’s workplace expectations.
Examples of real-world applications may include:
Students also have opportunities to engage in research with faculty, expanding their experience beyond the classroom.
Concentrations
Choose a concentration that aligns with your interests and career goals:
Launch Your Career in Data and AI
Data science is one of the fastest-growing and highest-paying career fields in the U.S., with strong demand across industries.
With your degree from Lander, you’ll be prepared for roles such as:
Opportunities span industries including healthcare, finance, technology, education, retail, sports and more.
Turn data into insight. Use AI to make an impact.
Start your journey in Data Science at Lander University today.
The B.S. in Data Science, Computer Information Systems Concentration is a program in the Department of Applied Computing at Lander University. Click here to learn more about the department.
The Department of Applied Computing is housed in Lander University’s College of Business and Technology. For more information on the college, click here.
Note: The information below provides convenient links to some of the courses required for this degree; however, it should not be used as a course registration guide. Please refer to the official Lander University Academic Catalog for the most accurate and up-to-date program requirements.
| GENERAL EDUCATION REQUIREMENTS1 | CREDIT HOURS |
||
|---|---|---|---|
| A. Core Skills |
|
||
| ENGL 101 | Writing and Inquiry I | 3 | |
| ENGL 102 | Writing and Inquiry II | 3 | |
| MATH 123 |
Calculus and its Applications |
3 | |
|
B. Humanities and Fine Arts |
6 | ||
| C. Behavioral and Social Perspectives (6 hours selected from 2 different disciplines) |
6 | ||
| D. Scientific and Mathematical Reasoning | |||
| MATH 211 | Statistical Methods I | 3 | |
| Approved Lab Science | 4 | ||
| E. Founding Documents of the United States | |||
| HIST 111R2 | United States History to 1877 OR HIST 112R2 United States History since 1877 OR POLS 101R2 American National Government |
3 | |
| F. World Cultures | 3 | ||
| G. LINK 101 | 1 | ||
| Total General Education Requirements | 35 | ||
1 For approved courses see the General Education section
2 If you already have credit for HIST 111, do not take HIST 111R; if you already have credit for HIST 112, do not take HIST 112R; if you already have credit for POLS 101, do not take POLS 101R
| MAJOR PROGRAM CORE REQUIREMENTS | CREDIT HOURS |
|
|---|---|---|
| CIS 120 | Fundamentals of Information Systems & Information Technology | 3 |
| CIS 130 | Problem Solving and Programming Methods | 4 |
| CIS 230 | Computer Programming Principles I | 4 |
| CIS 234 | Introduction to C/C++ Programming | 1 |
| CIS 360 | Database Design | 3 |
| DSCI 130 | Introduction to Data Science | 3 |
| DSCI 230 | Introduction to Data Science Programming | 3 |
| DSCI 231 | Data Visualization | 3 |
| DSCI 330 | Big Data Analysis | 3 |
| DSCI 340 | Applied Machine Learning | 3 |
| DSCI 440 | Applied Deep Learning | 3 |
| DSCI 499 | Data Science Capstone | 3 |
| MATH 125 | Introduction to Discrete Mathematics | 3 |
| MATH 208 | Applied Linear Algebra | 3 |
| MATH 213 | Supervised Machine Learning | 3 |
| MATH 214 | Unsupervised Machine Learning | 3 |
| MAJOR PROGRAM CONCENTRATION REQUIREMENTS | CREDIT HOURS |
|---|---|
| Select 15 hours CIS 231: Computer Programming Principles CIS 240: Introduction to Data Communication CIS 250: Introduction to E-Commerce CIS 320: Information Systems and Practice CIS 321: Analysis and Design CIS 498: Design and Implementation in Emerging Environments CYBR 140: Networking Lab |
15 |
| Total Major Program Requirements | 64 |
| Additional Electives (3-9 hours must be 300- or 400-level) |
21 |
| TOTAL FOR B.S. DEGREE | 120 |