Applied Computer Science, BS Post-Baccalaureate Courses
Find a path that meets your educational and career goals.
CU Boulder’s online Computer Science courses can help you level up your skills and gain the knowledge and expertise to meet your individual goals. Whether you want to test out online learning through individual courses or find a path toward your specific goal through combined classwork, our experienced faculty and dedicated program staff will support you on your journey.
Online computer science courses can help you:
- Complete prerequisite courses for a graduate program
- Prepare for an internship
- Gain specialized knowledge in AI or data science
- Explore the full degree program without the commitment
Choose from any of the classes offered in our program provided that you are able to meet course prerequisites. This is a non-degree option, which means you can enroll in computer science courses for credit without being a degree-seeking student.
If you choose to enroll in the degree program at a later date, the standalone or pathway courses may transfer and be applied to your degree. Learn more about transferring credits.
Career-relevant coursework for professional advancement
Flexible courses to fit your schedule
Complete your courses in 13 weeks year-round
Personalized Student Support
What makes our program unique is the excellent student support you receive from the moment you express interest until you graduate with your degree. Our admissions specialist can answer questions about everything from course selection to meet your personal goals, financial aid and admissions requirements, so you can feel confident in your decision to learn at CU Boulder. Once you’re enrolled in courses, our academic advisor can help you stay on track with your classes and connect you to academic and career resources to make sure you enjoy your journey along the way.
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Individual Courses
Our student-centered format allows you to engage with the coursework you need to achieve your specific goals. Find in-demand classes that help prepare you for graduate school in Computer Science or fill a gap in your professional skills, including:
Natural Language Processing
Linear Algebra
Discrete Structures
Algorithms
Machine Learning
Non-degree students can enroll in fall, spring and summer semesters.
Full List of Available Courses
Course Considerations
Subject to availability, non-degree students may enroll in section 750 after they meet with the Applied Computer Science Post-Baccalaureate program academic advisor and receive permission.
Courses are also available to on-campus undergraduate students pursuing a Computer Science degree. Computer Science degree-seeking students may enroll in summer in section 751.
Course Pathways
Our program offers different course pathways that allow you to gain specialized knowledge and skills to achieve specific learning or career goals whether you are on the path to completing your degree or are a non-degree student with discrete educational objectives.
Full course descriptions are provided above.
Pathway to an Introduction to Computer Science
This introductory pathway is ideal if you seek a comprehensive foundation in both computational thinking and key interdisciplinary areas.
Courses
Computer Science 1: Starting Computing
Get an introduction to fundamental programming concepts and problem-solving strategies, offering a solid entry point into the field of computer science.
Discrete Structures
Deepen your understanding of essential mathematical principles, such as logic and combinatorics, which underpin many areas of computer science.
Cognitive Science
Explore the intersection of computing and human cognition, which will give you insight into how computers can simulate thought processes.
Information Visualization
Gain skills to visually represent complex data, a critical skill for communicating technical information effectively.
Pathway to Internship
This pathway gives you foundational skills and practical knowledge necessary to be competitive for internships in the technology industry.
Courses
Computer Science 1: Starting Computing
Focus on building a strong computational foundation by learning the basics of programming and problem-solving.
Computer Science 2: Data Structures
Deepens your knowledge with essential data structures, enabling efficient algorithmic thinking.
Computer Systems
Get an introduction to the underlying hardware and low-level processes that support software applications, providing a comprehensive understanding of system-level design.
Software Development Methods and Tools
Learn best practices in software engineering, including version control, testing, and project management, preparing students for collaborative, real-world development environments.
Pathway to Graduate School in Computer Science
This pathway will prepare you to pursue advanced academic studies in computer science by providing the theoretical and practical foundation needed for success in graduate programs.
Courses:
Discrete Structures
Get an introduction to the mathematical principles underpinning computer science, such as logic, set theory, and combinatorics, which are crucial for understanding advanced concepts.
Computer Science 2: Data Structures
Build on knowledge gained in Discrete Structures course by learning how to efficiently manage and manipulate data, a core skill for graduate-level research.
Computer Systems
Gain an understanding of how hardware and software interact, bridging the gap between low-level systems and high-level computing processes.
Design & Analysis of Algorithms
Learn advanced algorithmic techniques and problem-solving strategies, which will prepare you for the rigorous analytical and research demands of graduate school.
Pathway to Data Science Skills
This pathway gives you foundational knowledge in data science and provides analytical and computational challenges in case you are interested in advanced studies in data science.
Courses
Discrete Structures
Gain foundational knowledge by working with fundamental mathematical concepts like logic and combinatorics, essential for algorithm design and data analysis.
Linear Algebra
Learn the mathematical tools necessary to work with large datasets, vectors, and matrices, which are critical for machine learning and statistical modeling.
Introduction to Data Science with Probability and Statistics
Learn core statistical methods and probability theory, which form the basis for data-driven decision-making and predictive analytics.
Data Mining
Learn how to extract valuable insights from large datasets using sophisticated techniques, setting them up for success in the research-heavy environment of data science graduate programs.
Pathway to Artificial Intelligence Skills
This pathway gives you foundational knowledge and specialized skills necessary for research, development and practical applications or further study in Artificial Intelligence.
Courses
Introduction to Artificial Intelligence
Gain a broad overview of AI concepts, from problem-solving techniques to knowledge representation and search algorithms.
Natural Language Processing
Explore the groundbreaking technologies that have revolutionized how computers understand and generate human language, providing you with the knowledge to build cutting-edge applications in areas like translation, text generation, and question answering.
Machine Learning
Study how machines can learn from data, which will give you tools and methods for building models and making predictions.
Cognitive Science
Learn how AI bridges with human cognition, offering insights into how humans think and learn, which can inform the design of more intuitive and human-like AI systems.
These sample pathways illustrate just some of the ways our Computer Science classes can help you meet your goals. We encourage you to talk with an academic advisor about your specific goals so that they can recommend the coursework that can help you along your educational journey. Pathways can be customized to meet individual student needs.
Getting Started
You can start your application and finish anytime. Learn more about the application requirements and process below. If you’ve missed the application deadline, please contact us at cspbonline@colorado.edu to discuss your options.
How to Enroll
Check Prerequisites and Transfer Credits
CSPB prerequisites listed in the CU Course Catalog must be met prior to enrollment in a given course. Non-degree seeking Continuing Education students should always defer to the prerequisite requirements for CSPB courses.
Students who have taken classes outside of CU may be eligible to transfer their credits to satisfy prerequisites. Eligibility can be verified by using Transferology to check course equivalencies.
Complete the Application
Complete the free, online application as a new non-degree student.
Schedule an Appointment With an Advisor
After completing your application, non-degree students must set up an appointment to meet with the Applied Computer Science Post-Baccalaureate program academic advisor. This advisor will support you in enrolling in classes and answer any questions you have about the program.
Non-degree Dates and Deadlines
For a complete list of academic dates and deadlines, visit the university's Academic Calendar. Dates are subject to change.
For more information about dates, please contact the Applied Computer Science Post-Baccalaureate academic advisor.
* Drop by 11:59 p.m. online using Buff Portal.
** Withdraw by 11:59 p.m. online using Buff Portal or by email to ceregistration@colorado.edu. A grade of W will appear on your transcript.
Program Offerings Related to these Courses
Students with a prior bachelor’s degree who are looking to make a career pivot, move ahead in their current career path or deepen their knowledge of computer science can earn a second undergraduate degree.
Post-Baccalaureate Bachelor's Degree
Our online Bachelor of Science in Applied Computer Science Post-Baccalaureate degree is designed for working professionals with a prior bachelor’s degree who are looking to enhance or change their career. The program is on an accelerated timeline which means you can earn a second bachelor's degree in just 45 credit hours.
The program aims to produce students who are able to:
- learn the strong foundational material that distinguishes professionals and lets them keep up with emerging technologies,
- develop software engineering skills using modern tools and a variety of programming languages,
- learn the tools and methods needed to work in groups,
- learn the algorithms and mathematics that underlie Computer Science, Data Science, Artificial Intelligence and Machine Learning, analyze and visualize data while understanding the cognitive processes of decision making, and analyze and create databases and automate analysis using data mining and data science algorithms.