Data Science
In today’s data-driven world, data science and AI are revolutionizing industries. This major will give you in-demand data science skills.
Through hands-on projects, you’ll master dataset creation, find insights and learn effective communication to tackle challenges in healthcare, finance and beyond. Emphasizing ethical data use to ensure privacy and combat bias, you’ll graduate ready for a range of data science roles.
Thrive in a dynamic world of data
As a data science major, you will be prepared for success through:
- Early exposure to data — dive into data science in our first-year student courses with no prerequisites.
- Theory and practice — experience a holistic blend of mathematics, statistics and computer science. Engage with discrete mathematics and machine learning, connecting abstract concepts and practical computer models.
- Personal schedule — choose electives and an optional minor to tailor your degree to your interests and goals.
Gain industry-ready skills
You’ll gain comprehensive skills in data analysis — ranging from data collection and management to deriving actionable insights using cutting-edge analytics and visualization techniques. Our coursework, embedded with real-world applications, will empower you to navigate and analyze extensive, complex datasets across a variety of industries.
Our curriculum stays current with emerging methodologies and contemporary data challenges. Through class projects, you won’t just learn to identify patterns — you’ll also hone your ability to communicate results in ways that drive informed and strategic decisions.
Develop ethical data practices
At the heart of our program is a strong commitment to ethical data practices. We prepare you to be not just an analyst, but a principled steward of data, emphasizing the importance of privacy and responsible data use.
At a Glance
Degree Type
Bachelor of Science
Department
School/College
College of Arts and Sciences
Next Steps
Interested in this major? Here's what you can do next:
With challenging and relevant courses, outstanding faculty, small class sizes, and an emphasis on hands-on learning, the data science program will position you to succeed in your chosen career.
Degree requirements
Find out what it takes to earn a degree in data science and explore the courses.
Highlighted Courses
Get familiar with some of the courses you might take in this major.
DATA 215: Introduction to Data Science
Data science relies on the ethical use of data, algorithmic thinking, and statistical inference. In this course the learner will survey these areas in the course of exploring real-world data sets. Learners will use technology and write code to analyze data sets and to create visualizations that effectively communicate their findings.
See descriptionDATA 340: Mathematics for Machine Learning
This course focuses on key areas of mathematics at the foundation of machine learning algorithms. After surveying matrix algebra, vector calculus, numerical optimization, and probability, the course culminates with random walks on graphs and vector space embeddings, tasks vital to the preparation of data for neural networks. Throughout the course, learners will approach topics theoretically and experimentally, augmenting traditional paper-and-pencil analysis by writing code.
See descriptionDATA 350: Technology, Ethics and Applications
This seminar course focuses on contemporary issues at the intersection of emerging data technology and applications viewed through a lens of ethics in data science. The course develops habits for life long learning and responsibility for the state of one's own knowledge, critical features of any data scientist.
See descriptionDATA 360: Advanced Visualization
The first and last mile in any data analysis project is data visualization. This course focuses on the design of data visualizations to discover patterns, form hypotheses, support conclusions, and drive decision making. Visualization is not an end goal, and this course presents visualization design in the context of producing clear, impactful, evidence-based narratives.
See descriptionDATA 440: Machine Learning
This course offers a practical approach to harnessing the power of data using machine learning, with a strong emphasis on programming and implementation. The course covers a comprehensive range of supervised techniques, including regression, k-nearest neighbor, naïve Bayes, decision trees, tree ensembles, neural networks, and support vector machines.
See descriptionDATA 450: Machine Learning in Practice
This hands-on course focuses on the application of machine learning techniques to solve real-world problems. While reading contemporary case studies, students will develop, code, analyze, and optimize machine learning models. This course is structured as an interactive seminar emphasizing active learning and encouraging students to engage in projects demonstrating their mastery of machine-learning solutions.
See description4+1 Option: Fast Track Your Graduate Degree
Add further value to your degree by choosing the 4+1 Option, which gives you a head start on earning a related graduate degree. With 4+1, you’ll be able to take graduate-level courses as part of your undergraduate curriculum. After graduation, you’ll only need one additional year to complete your degree at Cal Lutheran — saving you both time and money.
Recommended Minors
Want to add even more value to your degree? Consider one of these minors to gain a unique combination of skills and perspectives.
- Computer Science
- Mathematics
- Public Health
- Applied Scientific Computing
- Business Administration
- Economics
We offer hands-on opportunities that give you the freedom to explore your passion through real-world work and prepare for a fulfilling career.
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Learning in Action
You’ll gain practical knowledge and skills through course projects using real-world datasets from various industries. These experiences will lead to a capstone project where you will independently tackle a substantive data analytics challenge, demonstrating your ability to apply what you’ve learned to address practical business and societal challenges.
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Real-world Applications
Our coursework, embedded with real-world applications, empowers you to proficiently navigate and analyze extensive, complex datasets across a variety of industries such as healthcare, finance, and beyond.
The rise of data science, machine learning, and AI has given birth to an array of rewarding and sought-after career paths. Data scientists, data engineers, machine learning engineers and AI specialists are in high demand across industries.
Potential Careers
Bioinformatics Scientists
Conduct research using bioinformatics theory and methods in areas such as pharmaceuticals, medical technology, biotechnology, computational biology, proteomics, computer information science, biology and medical informatics. May design databases and develop algorithms for processing and analyzing genomic information, or other biological information.
See descriptionStatisticians
Develop or apply mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data to provide usable information. May specialize in fields such as biostatistics, agricultural statistics, business statistics, or economic statistics. Includes mathematical and survey statisticians.
See descriptionData Scientists
Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.
See descriptionComputer Systems Engineers/Architects
Design and develop solutions to complex applications problems, system administration issues, or network concerns. Perform systems management and integration functions.
See descriptionHealth Informatics Specialists
Apply knowledge of nursing and informatics to assist in the design, development, and ongoing modification of computerized health care systems. May educate staff and assist in problem solving to promote the implementation of the health care system.
See descriptionDatabase Architects
Design strategies for enterprise databases, data warehouse systems, and multidimensional networks. Set standards for database operations, programming, query processes, and security. Model, design, and construct large relational databases or data warehouses. Create and optimize data models for warehouse infrastructure and workflow. Integrate new systems with existing warehouse structure and refine system performance and functionality.
See descriptionData Warehousing Specialists
Design, model, or implement corporate data warehousing activities. Program and configure warehouses of database information and provide support to warehouse users.
See descriptionMarket Research Analysts and Marketing Specialists
Research conditions in local, regional, national, or online markets. Gather information to determine potential sales of a product or service, or plan a marketing or advertising campaign. May gather information on competitors, prices, sales, and methods of marketing and distribution. May employ search marketing tactics, analyze web metrics, and develop recommendations to increase search engine ranking and visibility to target markets.
See descriptionLooking for more career paths? Search these related areas to discover more options.
This page includes information from O*NET OnLine by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. Some occupations listed above may require a related graduate degree.
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