Inside Boston University’s Online MS in Computer Science & Artificial Intelligence
No longer is artificial intelligence (AI) a “niche” area of computer science. In many ways, AI now serves as a foundational capability that’s actively reshaping how entire computer systems and networks are built.
If you’ve been considering a career in computer science, having strong foundations in both computer science and artificial intelligence is more important than ever. Fortunately, Boston University’s online Master of Science in Computer Science & Artificial Intelligence has been specifically designed to integrate CS fundamentals with applied AI.
Why Computer Science and Artificial Intelligence Are Now Taught Together
With AI becoming ingrained in every aspect of computing, many schools are now including AI coursework in their computer science curricula — and for good reason.
The Evolution of Computer Science in an AI-Driven World
Since AI has become inextricably linked with computer science, it is increasingly being used to automate routine tasks. As a result, computer science professionals can free up more of their valuable time to focus on high-level problem-solving and system design.
Likewise, as AI continues to be used in more applications across industries, the need for specialized skills in machine learning, data science, and AI ethics is becoming apparent.
Moving Beyond Standalone AI Courses
AI technology began to take off several years ago, prompting many computer science programs to add standalone AI courses to cover the basics. However, even in such a short period of time, AI technology has evolved and advanced significantly. Today, standalone AI courses aren’t enough to prepare computer science students for the realities of the field. Instead, programs need to integrate advanced AI coursework into existing curricula to keep up with AI and computer science workforce demands.
BU’s AI & Computer Science Program Structure
At Boston University, our online Master’s Degree in Computer Science & AI consists of 30 credit hours that are delivered across 10 dedicated modules — with most students completing the program in four semesters of part-time study.
Our MS in Computer Science & AI curriculum is also broken up into an AI curriculum and a systems curriculum, with respective coursework in career-ready topics such as:
- Applied machine learning
- Generative models
- Systems deployment
- Responsible innovation
- Cloud computing
- Scalable data analytics systems
- GPU computing for data and cloud applications
Preparing Students Through Required Bootcamps
Before beginning either the AI or systems curriculum, students in our MS in Computer Science & AI program are required to complete two preparatory, no-credit bootcamps. These bootcamps prepare students for rigorous coursework while ensuring all students are on the same page as they enter the program.
Machine Learning Preparation Bootcamp
In our Machine Learning Preparation Bootcamp, students will:
- Refresh Python skills
- Revisit basic skills in working with data using Pandas
- Rehash math concepts, including linear algebra, probability, and optimization
- Explore the AI/ML pipeline at a high level
Programming and Systems Preparation Bootcamp
As part of the Programming and Systems Preparation Bootcamp, students will:
- Learn how to package and run a script in Docker
- Learn how to make simple HTTP requests with Python
- Develop basic skills in debugging and testing
- Explore small-scale programming projects
- Prepare for concurrency, networking, and systems thinking
Parallel Tracks That Build Complementary Expertise
At Boston University, the way we teach AI and computer science in parallel tracks is what sets our program apart. By teaching these concepts side by side rather than sequentially, students can better understand the interplay between AI and computer systems in modern practice.
The Artificial Intelligence Track
In the AI track of our program, students explore:
- Applied machine learning
- Machine learning foundations
- Generative models
- Responsible deployment
These concepts are reinforced not just through theory and lectures but also through hands-on implementation, practice, and evaluation.
The Systems Track
The systems track of our MS in Computer Science & AI program focuses on concepts such as:
- Programming
- Cloud computing
- Scalable analytics
- GPU-enabled systems
Through assigned readings, discussions, and hands-on learning experiences, students develop critical performance, reliability, and production-readiness skills that translate into their future work in the field.
Why Parallel Learning Matters
When students proactively apply AI concepts within system constraints (rather than learning concepts independently of one another), they can better understand the real interplay that’s required to build intelligent systems that run at scale.
Applied Learning Through Industry Context
In BU’s Master of Computer Science & AI program, we strongly believe that students learn best when they’re able to view course concepts through an industry-specific lens. That’s why we incorporate guidance from real industry leaders and experiential learning that prepares students for real workplace environments.
AI in Industry Speaker Series
Our program regularly brings in industry leaders to speak to students in our MS in Computer Science & AI program. These speakers provide students with the important real-world context needed to understand current and future challenges in deploying AI at scale within the industry.
Collaborative and Project-Based Coursework
Another important component of BU’s Computer Science & AI program is ample collaborative and project-based coursework for students. Specifically, group projects and discussion-based coursework are intentionally incorporated to help students develop valuable collaboration and teamwork skills needed in real computing/engineering environments.
The Capstone Experience: Building a Production-Ready AI System
In addition to completing two parallel tracks in AI and systems, students in BU’s online Computer Science & AI program complete a two-semester capstone project as a synthesis of what they’ve learned in the program.
A Two-Semester, End-to-End Project
During the capstone, students are tasked with designing and building a full language model pipeline. Development of this pipeline occurs not solely in the final semester, but with progressive development across semesters as an end-to-end project.
Integrating AI, Systems, and Responsible Deployment
As part of the capstone project, students gain practical experience evaluating, optimizing, and deploying systems responsibly — all with special attention to scalability, ethics, and long-term reliability.
Learning Designed for Working Professionals
Considering a return to school while working full-time? Boston University’s Master of Science in Computer Science & AI is specifically designed with the needs of working professionals in mind, supporting depth and flexibility without sacrificing rigor.
High-Touch Online Instruction
Our online coursework offers the ideal blend of versatility and structure that working professionals need, with a combination of both weekly live sessions with faculty and asynchronous modules that students can complete on their own time.
Cohort-Based Experience and Support
Our Computer Science & AI program is cohort-based, meaning students move through the program with the same group of peers. This cohort experience encourages peer learning and professional networking. At the same time, students enjoy personalized instruction and feedback from expert faculty and learning facilitators.
For each module of the program, students are assigned a dedicated learning facilitator (LF) who serves as a direct subject-matter expert. These LFs are available to assist with all course-related materials and will communicate with students on a regular basis to help them stay on track.
Each student is also assigned a Student Success Specialist, who is available at every step of the program to assist with schedule planning, utilizing university resources, and exploring ways to engage in the program community. You can learn more about these services in the “Student Services” section of our program FAQ.
Academic Rigor and Faculty Expertise
All of our courses in BU’s MS in Computer Science & AI program are intentionally designed for online delivery and taught exclusively by knowledgeable, experienced faculty from our Department of Computer Science. Even with its 100% online format, students experience the same academic rigor and high standards as our residential learners.
Plus, with plenty of opportunities for applied research and hands-on experience with real-world systems, online students can enter or advance in the field with the real skills today’s employers are looking for in a fast-changing technical landscape.
What This Program Is Designed to Deliver
Ultimately, what sets BU’s Computer Science & AI program apart from other programs is the fact that our coursework truly integrates AI concepts, tools, and implications into core computer science areas — effectively preparing students to meet and exceed dynamic workforce demands while emphasizing responsible, ethical, and human-centered AI.
With deep computer science foundations, applied AI knowledge, and plenty of hands-on experience building scalable systems, graduates of our MS in Computer Science & AI program are ready for advanced technical work in today’s AI-driven environments.
Ready to Take the Next Step?
Boston University’s online MS in Computer Science & AI integrates rigorous computer science foundations with modern artificial intelligence — ultimately preparing graduates to take on the unique challenges and opportunities of computing in the modern world.
Learn more about this program by requesting information, or consider attending one of our upcoming webinars. If you’re eager to get started, you can also learn more about our admissions requirements or start your online application.