Artificial Intelligence and Machine Learning

Major: Artificial Intelligence and Machine Learning
Degree Awarded: Master of Science in Artificial Intelligence and Machine Learning
Calendar Type: Quarter
Minimum Required Credits: 45.0
Co-op Option: Available for full-time, on-campus master's-level students
Classification of Instructional Programs (CIP) code: 11.0701
Standard Occupational Classification (SOC) code: 15-0000

About the Program

The Master of Science in Artificial Intelligence and Machine Learning provides a strong foundation in the artificial intelligence and machine learning fields with foci on mathematical foundations, algorithms, tools, and applications as they pertain to artificial intelligence and machine learning. Students will pursue an applied or computational track and will gain competency in fundamental methods and techniques in artificial intelligence and machine learning. Their fundamental understanding will be applied to real data sets and data analysis tasks with the help of state-of-the-art technologies, tools, and platforms. The Master of Science in Artificial Intelligence and Machine Learning program culminates with a two-term capstone experience where students work on a real world or research problem using the knowledge they have gained throughout the program.

Admission Requirements

The Master of Science in Artificial Intelligence and Machine Learning accepts applicants who hold a four-year bachelor's degree or master’s degree from a regionally accredited institution in computer science, software engineering, or related STEM degree, plus work experience equal to Drexel's Post-Baccalaureate Certificate in Computer Science. Please visit the College of Computing & Informatics website for more information on admission requirements.

Additional Information

For more information about this program, visit the College of Computing & Informatics MS in Artificial Intelligence and Machine Learning webpage.

Degree Requirements

Core Courses
CS 591Artificial Intelligence and Machine Learning Capstone I3.0
CS 592Artificial Intelligence and Machine Learning Capstone II3.0
Choose appropriate core courses for concentration:9.0
Introduction to Programming
Programming Foundations
Applications of Machine Learning
Applied Artificial Intelligence
Introduction to Artificial Intelligence
Machine Learning
Deep Learning
Breadth Requirements9.0
One course must be selected from each group for the appropriate concentration
Data Science Foundations
Quantitative Foundations of Data Science
Data Acquisition and Pre-Processing
Data Analysis and Interpretation
Applied Machine Learning for Data Science
Applied Cloud Computing
Data Analytics for Community-Based Data and Service
Social Network Analytics
Data Mining
Introduction to Data Analytics
AI Foundations
Data Structures and Algorithms
Systems Basics
Introduction to Artificial Intelligence
Machine Learning
Knowledge-based Systems
Explainable Artificial Intelligence
Human-Centered Computing
Responsible Data Analysis
Security, Policy and Governance
Information Innovation through Design Thinking
Foundations of Data and Information
Human-Computer Interaction
Designing with Data
Social and Collaborative Computing
Understanding Users: User Experience Research Methods
Prototyping the User Experience
Human–Artificial Intelligence Interaction
Information Policy and Ethics
Data Science and Analytics
Data Analysis at Scale
Responsible Data Analysis
Data Acquisition and Pre-Processing
Data Analysis and Interpretation
Applied Machine Learning for Data Science
Applied Cloud Computing
Data Analytics for Community-Based Data and Service
Social Network Analytics
Data Mining
Introduction to Data Analytics
Algorithmic Foundations
Data Structures and Algorithms I
Data Structures and Algorithms II
Theory of Computation
Applied Symbolic Computation
Algorithmic Game Theory
Advanced Data Structure and Algorithms
Approximation Algorithms
Program Generation and Optimization
Quantitative Foundations of Data Science
Probability & Random Variables
Detection & Estimation Theory
Linear Algebra & Matrix Analysis
Applied Probability and Statistics I
Applications of AI/ML
Applications of Machine Learning
Introduction to Computer Vision
Advanced Artificial Intelligence
Game Artificial Intelligence
Knowledge-based Agents
Algorithmic Game Theory
Cognitive Systems
Advanced Computer Vision
Topics in Artificial Intelligence
Natural Language Processing with Deep Learning
Applied Artificial Intelligence
Human–Artificial Intelligence Interaction
Machine Learning in Biomedical Applications
Applied Machine Learning Engineering
Neuromorphic Computing
The remaining 7 courses may be selected from any focal area listed above or any graduate course in CCI (CI, CS, CT, SE, DSCI, INFO). For the ComputationalAIML concentration, at least two (2) of these must be within the CS department.
Up to two (2) of these may be approved independent studies.
Total Credits45.0

Sample Plan of Study

Part time, No co-op

First Year
Core Courses6.0Core Course3.0Breadth Courses6.0Electives6.0
 Breadth Course3.0  
 6 6 6 6
Second Year
Electives6.0CS 5913.0CS 5923.0 
 6 9 6 
Total Credits 45

Full time, With Co-op

First Year
Core Courses6.0Core Course3.0Breadth Course3.0COOP EXPERIENCE
Breadth Course3.0Breadth Course3.0Electives6.0 
 9 9 9 0
Second Year
 0 9 9 
Total Credits 45

3675 Market Street

In March 2019, the College of Computing & Informatics relocated to 3675 Market. For the first time in the College's history, all CCI faculty, students and professional staff are housed under one roof. Occupying two floors in the brand new uCity Square building, CCI's new home offers state-of-the-art technology in our classrooms, labs, meeting areas and collaboration spaces. 3675 Market offers Class A laboratory, office, coworking, and convening spaces. In fall 2019, the College opened a third floor which will include additional offices, classrooms, innovative research labs, and a maker space. Located at the intersection of Market Street and 37th Street, 3675 Market will act 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

Drexel University Libraries is a learning enterprise, advancing the University’s academic mission through serving as educators, supporting education and research, collaborating with researchers, and fostering intentional learning outside of the classroom. Drexel University Libraries engages with Drexel communities through three physical locations, including W. W. Hagerty Library,  Queen Lane Library, and the Library Learning Terrace, as well as a vibrant online presence which sees, on average, over 8,000 visits per day. In the W.W. Hagerty Library location, College of Computing & Informatics students have access to private study rooms and nearly half a million books, periodicals, DVDs, videos and University Archives. All fields of inquiry are covered, including: library and information science, computer science, software engineering, health informatics, information systems, and computing technology. Resources are available online at or in-person at W. W. Hagerty Library.

The Libraries also make available laptop and desktop PC and Mac computers, printers and scanners, spaces for quiet work or group projects and designated 24/7 spaces. Librarians and library staff—including a liaison librarian for computing and informatics—are available for individual research consultations and to answer questions about materials or services.

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 Rational SEED Program which provides cutting-edge software development and project management software for usage in the CCI Commons and CCI classrooms. The College is also a member of the Microsoft Academic Alliance known also as “DreamSpark” 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.

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 computer science classes. 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 Drexel Health and Risk Communication Lab, Interactive Systems for Healthcare, Socio-Technical Studies Group, Intelligent Information & Knowledge Computing Research Lab, Evidence-based Decision Making Lab, Applied Symbolic Computation Laboratory (ASYM), High Performance Computing Laboratory (SPIRAL), Drexel Research on Play (RePlay) Laboratory, Software Engineering Research Group (SERG), Social Computing Research Group, Vision and Cognition Laboratory (VisCog) and the Vision and Graphics Laboratory. For more information on these laboratories, please visit the College’s research web page.

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