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 College of Computing & Informatics' 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 College of Computing & Informatics website.

Degree Requirements

Core Requirements
CS 171Computer Programming I3.0
or ENGR 131 Introductory Programming for Engineers
or ENGR 132 Programming for Engineers
CS 172Computer Programming II3.0
or ECE 105 Programming for Engineers II
CS 180Introduction to Artificial Intelligence & Machine Learning3.0
CS 260Data Structures4.0
CS 265Advanced Programming Tools and Techniques3.0
CS 380Artificial Intelligence3.0
CS 383Machine Learning3.0
or INFO 213 Data Science Programming II
or ECE 310 Machine Learning Engineering Practicum
INFO 212Data Science Programming I3.0
INFO 215Social Aspects of Information Systems3.0
SE 201Introduction to Software Engineering and Development3.0
SE 310Software Design3.0
Elective Requirements
Select 8 courses from the list below. For sequences, each course may count separately toward this total provided that it is not already used to satisfy another degree requirement.24.0
Systems Architecture
and Systems Programming
and High Performance Computing *
Evolutionary Computing
Game AI Development
Reinforcement Learning
Reinforcement Learning
Computational Photography
Computational Network Neuroscience
Advanced Artificial Intelligence
Robust Machine Learning
Topics in Artificial Intelligence
Digital Logic Design
and Introduction to Computer Organization
and Neuromorphic Computing
Introduction to Computer Organization
and High Performance Computing *
Introduction to Computer Organization
and Discrete Mathematics
and Intelligent System Architectures
Introduction to Multimedia Forensics and Security
Cell and Tissue Image Analysis
Pattern Recognition
Bioinformatics
Statistical Analysis of Metagenomics
Recommender Systems
Applied Deep Learning
Database Management Systems
and Cloud Computing and Big Data
Information Retrieval Systems
Human-Centered Design Process & Methods
Exploratory Data Analytics
Data Mining Applications
Advanced Data Analytics
Social Media Data Analysis
Project Requirements
Select one of the following sequences:6.0
Computing and Informatics Design I
and Computing and Informatics Design II
and Computing and Informatics Design III
Introduction to Engineering Design & Data Analysis
and First-Year Engineering Design
Choose one of the following sequences:9.0
Senior Project I
and Senior Project II
and Senior Project III
Senior Design Project I
and Senior Design Project II
and Senior Design Project III
Mathematics Requirements
Select one of the following sequences:11.0-14.0
Algebra, Functions, and Trigonometry
and Calculus I
and Calculus II
Calculus and Functions I
and Calculus and Functions II
and Calculus II
Calculus I
and Calculus II
and Multivariate Calculus **
MATH 201Linear Algebra3.0-4.0
or ECE 231 Linear Algebra and Matrix Computations
or ENGR 231 Linear Engineering Systems
MATH 311Probability and Statistics I4.0
or ECE 361 Probability and Data Analytics for Engineers
Science Requirements
Select from the following 100-400 level courses:20.0
Any BMES (Biomedical Engineering & Science)
Any BIO (Bioscience & Biotechnology)
Any CHEM (Chemistry)
Any ENVS (Environmental Science)
Any GEO (Geoscience)
Any PHEV (Physics-Environmental Science)
Any PHYS (Physics)
Arts & Humanities Requirements
COM 230Techniques of Speaking3.0
or COM 310 Technical Communication
ENGL 101Composition and Rhetoric I: Inquiry and Exploratory Research3.0
or ENGL 111 English Composition I
ENGL 102Composition and Rhetoric II: Advanced Research and Evidence-Based Writing3.0
or ENGL 112 English Composition II
ENGL 103Composition and Rhetoric III: Themes and Genres3.0
or ENGL 113 English Composition III
PHIL 311Ethics and Information Technology3.0
University Requirements
UNIV CI101The Drexel Experience2.0
or CI 120 CCI Transfer Student Seminar
CIVC 101Introduction to Civic Engagement1.0
COOP 101Career Management and Professional Development1.0
Free Electives
Select any unrestricted 099-499 courses46.0-50.0
Total Credits180.0
*

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

First Year
FallCreditsWinterCreditsSpringCreditsSummerCredits
CI 1012.0CI 1022.0CI 1032.0Vacation
CS 1803.0CIVC 1011.0COOP 1011.0 
ENGL 101 or 1113.0CS 1713.0CS 1723.0 
MATH 1214.0ENGL 102 or 1123.0ENGL 103 or 1133.0 
UNIV CI1011.0MATH 1224.0MATH 2004.0 
Free Elective3.0Science Elective4.0UNIV CI1011.0 
  Science Elective4.0 
 16 17 18 0
Second Year
FallCreditsWinterCreditsSpringCreditsSummerCredits
CS 2653.0CS 2604.0Co-op ExperienceCo-op Experience
INFO 2123.0INFO 2153.0  
MATH 2014.0MATH 3114.0  
SE 2013.0Science Elective4.0  
Science Elective4.0Free Elective3.0  
 17 18 0 0
Third Year
FallCreditsWinterCreditsSpringCreditsSummerCredits
COM 2303.0CS 3833.0Co-op ExperienceCo-op Experience
CS 3803.0AI/ML Elective3.0  
SE 3103.0Science Elective4.0  
AI/ML Elective3.0Free Electives6.0  
Free Elective3.0   
 15 16 0 0
Fourth Year
FallCreditsWinterCreditsSpringCreditsSummerCredits
PHIL 3113.0AI/ML Electives6.0Co-op ExperienceCo-op Experience
AI/ML Electives6.0Free Electives6.0  
Free Electives6.0   
 15 12 0 0
Fifth Year
FallCreditsWinterCreditsSpringCredits 
CI 4913.0CI 4923.0CI 4933.0 
AI/ML Elective3.0AI/ML Elective3.0Free Electives9.0 
Free Electives6.0Free Electives6.0  
 12 12 12 
Total Credits 180

4-year, 1 co-op

First Year
FallCreditsWinterCreditsSpringCreditsSummerCredits
CI 1012.0CI 1022.0CI 1032.0Vacation
CS 1803.0CIVC 1011.0CS 1723.0 
ENGL 101 or 1113.0CS 1713.0ENGL 103 or 1133.0 
MATH 1214.0ENGL 102 or 1123.0MATH 2004.0 
UNIV CI1011.0MATH 1224.0UNIV CI1011.0 
Free Elective3.0Science Elective4.0Science Elective4.0 
 16 17 17 0
Second Year
FallCreditsWinterCreditsSpringCreditsSummerCredits
CS 2653.0CS 2604.0COM 2303.0COOP 1011.0
INFO 2123.0INFO 2153.0CS 3803.0CS 3833.0
MATH 2014.0MATH 3114.0SE 3103.0AI/ML Elective3.0
SE 2013.0Science Elective4.0AI/ML Elective3.0Science Elective4.0
Science Elective4.0Free Elective3.0Free Elective3.0Free Electives6.0
 17 18 15 17
Third Year
FallCreditsWinterCreditsSpringCreditsSummerCredits
PHIL 3113.0AI/ML Electives6.0Co-op ExperienceCo-op Experience
AI/ML Electives6.0Free Electives6.0  
Free Electives6.0   
 15 12 0 0
Fourth Year
FallCreditsWinterCreditsSpringCredits 
CI 4913.0CI 4923.0CI 4933.0 
AI/ML Elective3.0AI/ML Elective3.0Free Electives9.0 
Free Electives6.0Free Electives6.0  
 12 12 12 
Total Credits 180

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 College of Computing & Informatics is located at 3675 Market. Occupying three floors in the modern uCity Square building, CCI'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 Market Street and 37th Street, 3675 Market acts as a physical nexus, bridging academic campuses and medical centers to the east and south, the commercial corridors along Market Street and 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
  • Adjacent 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 the College of Computing & Informatics 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.

CCI Commons

Located on the 10th floor of 3675 Market Street, the CCI 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 its students. Students have access to 3675 Market's fully equipped conference room with 42” displays and videoconferencing capabilities. The CCI 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 CCI Commons is reserved for all students taking CCI courses.

The computers for general use are Microsoft Windows and Macintosh OSX 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 CCI Commons and through the W.W. Hagerty Library. The College 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 CCI Commons, student labs, and classrooms have access to networked databases, print and file resources within the College, and the Internet via the University’s network. Email accounts, Internet and BannerWeb access are available through the Office of Information Resources and Technology.

Computer Support for Teaching

The CCI 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 college. 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 college 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 CCI Commons desk.

Additionally, CCI is hosting and supporting multiple Virtual Computing Lab environments for students to use that mimics the physical computer labs in CCI. This technology allows both online and face to face students to have the same experience when using computing facilities.

CCI Virtual Environments

CCI hosts a variety of virtual environments, which support all levels of research, academics, and administration at CCI. These include OpenStack, Proxmox VE, VMWare, and Xen architectures, backed by storage in CEPH. Multiple environments allow CCI 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.

CCI continues to invest in these virtual environments, and explores emerging environments, to continue to best support CCI 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

CCI Learning Center

The CCI Learning Center (CLC), located in 3675 Market Street's CCI 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 the College of Computing & Informatics.

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

Research Laboratories

The College houses multiple research labs, led by CCI 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 College’s 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