Artificial Intelligence & Machine Learning

Major: Artificial Intelligence & Machine Learning
Degree Awarded: Bachelor of Science (BS)
Calendar Type: Quarter
Minimum Required Credits: 180.0
Co-op Options: Three Co-op (Five years); One Co-op (Four years)
Classification of Instructional Programs (CIP) code: 11.0701
Standard Occupational Classification 15-0000

About the Program

Note: Students will be accepted into this program beginning Fall 2025 for a Fall 2026 admittance. For more information or to apply, please go to Undergraduate Application Instructions.

The School of Computer and Information Sciences' Bachelor of Science in Artificial Intelligence & Machine Learning (AIML) provides a strong foundation in these areas, combining conceptual and theoretical knowledge with hands-on practice and applications. The program is designed for maximum flexibility, allowing students to tailor their study of AI and machine learning along specific focus areas (e.g., theory, data analytics, hardware, and/or practical applications). Through coursework and possibly double majors, students can also blend their study with a wide variety of other fields, including computing, physical or social sciences, engineering, and arts and humanities. The hands-on curriculum combined with co-op provides real-world experience that culminates in a full-year team capstone project involving in-depth study and application of computing and informatics. Graduates of the BS AIML program are in high demand in a vast array of industries where knowledge of AI and machine learning is critical for success.

Additional Information

For more information about this program, please visit the Undergraduate Programs page on the School of Computer and Information Sciences website.

Degree Requirements

*

Only one of the two High Performance Computing sequences may be selected.

**

Instead of MATH 200, students may substitute CS 270, ECE 232, ENGR 232, or any other MATH course not used to fulfill another requirement.

Writing-Intensive Course Requirements

In order to graduate, all students must pass three writing-intensive courses after their freshman year. Two writing-intensive courses must be in a student's major. The third can be in any discipline. Students are advised to take one writing-intensive class each year, beginning with the sophomore year, and to avoid “clustering” these courses near the end of their matriculation. Transfer students need to meet with an academic advisor to review the number of writing-intensive courses required to graduate.

A "WI" next to a course in this catalog may indicate that this course can fulfill a writing-intensive requirement. For the most up-to-date list of writing-intensive courses being offered, students should check the Writing Intensive Course List at the University Writing Program. Students scheduling their courses can also conduct a search for courses with the attribute "WI" to bring up a list of all writing-intensive courses available that term.

Sample Plan of Study

5-year, 3 co-op

4-year, 1 co-op

Co-op/Career Opportunities

Co-Op Options

Two co-op options are available for this program:

• five-year/three co-op
• four-year/one co-op

Career Opportunities

The demand for computing skills is tremendous and growing with highly paid jobs. Most professionals in the field focus on the design and development of artificial intelligence- and machine learning-centered applications. Typical jobs include software engineer, programmer, data scientist, systems analyst or consultant, and manager of technical staff. Most positions require at least a bachelor’s degree. Relevant work experience, such as that provided by co-operative education, is also very important, as cited by the Occupational Outlook Handbook published by the US Bureau of Labor Statistics.

Additional Information

Visit the Drexel Steinbright Career Development Center page for more detailed information on co-op and post-graduate opportunities.

3675 Market Street

The School of Computer and Information Sciences (SCIS) is located at 3675 Market. Occupying three floors in the modern uCity Square building, SCIS's home offers state-of-the-art technology in our classrooms, research labs, offices, meeting areas, and collaboration spaces. 3675 Market offers Class A laboratory, office, coworking, and convening spaces. Located at the intersection of 37th and Market Streets, 3675 Market acts as a physical nexus for our school, bridging academic campuses and medical centers to the east and south, the commercial corridors along Market Street and nearby Chestnut Street, and the residential communities to the north and west.

The uCity Square building offers:

• Speculative lab/office space
• World-class facilities operated by CIC
• Café/restaurant on-site
• Quorum, a two-story, 15K SF convening space and conference center
• Adjacency to future public square
• Access to Science Center’s nationally renowned business acceleration and technology commercialization programs

Drexel University Libraries

The Drexel University Libraries is a one-stop resource for all members of the Drexel community, providing access to millions of print and online books, journals, databases and other media, as well as hundreds of online course and research guides, workshops, and tutorials. Expert librarians offer a variety of consultation services virtually or in person, including help with course-related projects, strategies for finding and evaluating authoritative information, and approaches to utilizing, organizing, and presenting scholarship.

Students in SCIS also have access to the W. W. Hagerty Library where they can take advantage of the Libraries’ various learning environments, including group study rooms, collaborative and silent study areas, and 24/7 study space in the Dragons’ Learning Den. The Libraries also offers a wellness room, printing and scanning services, and laptops, portable power chargers, and other equipment you can borrow for use in the Library.

SCIS Commons

Located on the 10th floor of 3675 Market Street, the SCIS Commons is an open lab and collaborative work environment for students. It features desktop computers, a wireless/laptop area, free black-and-white printing, and more collaborative space for our students. Community members have access to 3675 Market's fully equipped conference room with 42” displays and videoconferencing capabilities. The SCIS Commons provides technical support to students, faculty, and professional staff. In addition, the staff provides audio-visual support for all presentation classrooms within 3675 Market. Use of the SCIS Commons is reserved for all students taking SCIS courses.

The computers for general use are Microsoft Windows and Apple macOS machines with appropriate applications which include the Microsoft Office suite, various database management systems, modeling tools, and statistical analysis software. Library-related resources may be accessed at the SCIS Commons and through the W.W. Hagerty Library. SCIS is a member of the "Azure Dev Tools for Teaching” platform that allows students free access to a wide array of Microsoft software titles and operating systems.

The SCIS Commons, student labs, and classrooms have access to networked databases, print and file resources, and the Internet via the University’s network. Email accounts, Internet and BannerWeb access are available through Drexel's Office of Information Resources and Technology.

Computer Support for Teaching

The SCIS server room houses a multitude of servers to support faculty research, staff operations, and student learning. Services provided include a Linux compute cluster which is open to all faculty, staff, and students, multiple virtualization environments to meet different needs of faculty, staff, and students, and other single-purpose servers to support various operations throughout the school. The compute cluster provides a common environment for students to develop software, which makes testing easier for the TAs and faculty. Our virtualization environments allow community members the flexibility of a cloud environment with local support and direct cost recovery options. For those who need dedicated hardware, we also support dedicated research systems.

Classrooms are outfitted with laser projectors, 4K displays, class capture hardware, and the Wolfvision Cynap. The Cynap controls the AV distribution throughout the room and can display up to 4 streams simultaneously. These include the local PC, a laptop connected directly to the podium, or up to 4 streaming devices. Windows, macOS, iOS, and Android devices can all connect wirelessly to the presentation system, allowing collaboration and freedom to roam the classroom for better interactivity. Wireless networking and outlets are also available for students throughout the classrooms. Laptops are available for checkout from the SCIS Commons desk.

Additionally, SCIS hosts and supports multiple Virtual Computing Lab environments for students to use that mimics our physical computer labs. This technology allows both online and face to face students to have the same experience when using computing facilities.

SCIS Virtual Environments

SCIS hosts a variety of virtual environments, which support all levels of research, academics, and administration. These include OpenStack, Proxmox VE, VMWare, and Xen architectures, backed by storage in CEPH. Multiple environments allow SCIS IT to provide researchers with the level of control appropriate for the project at hand and make efficient use of project funding. External cloud vendors such as AWS and Google Cloud Platform are also used when appropriate.

SCIS continues to invest in these virtual environments, and explores emerging environments, to continue to best support research and teaching. CPU cores, storage, and memory are added at every opportunity to these flexible, scalable environments. The current capacity of the system includes:

• 1760 CPU Cores
• 6 TB of Memory
• Over 556 TB of HDD-backed storage
• 122 TB of high-performance SSD-backed storage
• 12 GPUs with room for expansion through funded research for high-performance computing needs

Cyber Learning Center

The Cyber Learning Center (CLC), located in 3675 Market Street's SCIS Commons student computer lab, provides consulting and other learning resources for students taking courses offered by the Computer Science Department. The CLC is staffed by graduate and undergraduate computer science students from across SCIS.

The CLC and SCIS Commons serve as a central hub for small group work, student meetings, and TA assistance. 

Research Laboratories

SCIS houses multiple research labs, led by SCIS faculty, in 3675 Market Street including: the Metadata Research Center (MRC), Interactive Systems for Healthcare (IS4H) Research, Economics and Computation (EconCS), The TeX-Base Lab, SPiking And Recurrent SoftwarE (SPARSE) Coding, Human-System Evaluation and Analysis Lab (H-SEAL), Applied Symbolic Computation Laboratory (ASYM), Security and Privacy Analytics Lab (SePAL), Software Engineering and Analytics Research (SOAR), Software Engineering Research Group (SERG), Social Computing Research Group, Vision and Cognition Laboratory (VisCog). For more information on these laboratories, please visit the our research web page.

Program Level Outcomes

The College of Computing & Informatics works continually to improve its degree programs. As part of this effort, the Artificial Intelligence & Machine Learning degree is evaluated relative to the following Objectives and Outcomes:

Artificial Intelligence & Machine Learning Program Educational Objectives

Drexel Artificial Intelligence & Machine Learning alumni will:

• Be valued employees in a wide variety of occupations in industry, government and academia, in particular as artificial intelligence and machine learning scientists and engineers
• Succeed in graduate and professional studies, such as engineering, science, law, medicine, and business
• Pursue life-long learning and professional development to remain current in an ever-changing technological world
• Provide leadership in their profession, in their communities, and society
• Function as responsible members of society with an awareness of the social and ethical ramifications of their work

Artificial Intelligence & Machine Learning Student Outcomes

The Drexel Artificial Intelligence & Machine Learning program enables students to attain by the time of graduation:

• An ability to analyze a problem and identify and define the use of artificial intelligence and/or machine learning (AI/ML) as appropriate to its solution
• An ability to interpret and communicate the output of statistical and algorithmic methods
• An ability to function effectively on a team to design and implement a computer-based AI/ML system
• An ability to understand the implementation and use of AI/ML tools and systems
• An ability to apply mathematical foundations, algorithmic principles, and computational knowledge in the modeling and design of AI/ML systems in a way that demonstrates comprehension of the tradeoffs involved in design choices
• An ability to design, implement, and evaluate a computer-based AI/ML system, process, component, or program to meet desired needs
• An ability to apply sound software engineering principles in the construction of computer-based AI/ML systems of varying complexity
• An ability to understand and communicate the ethical aspects of AI/ML, and to communicate these aspects as part of result interpretation
• An ability to understand and communicate the legal and ethical aspects of using AI/ML in societal contexts