Explore the Master of Science in Artificial Intelligence & Machine Learning program at Drexel University. This program is offered in USA and provides an excellent learning opportunity in Masters studies.

Drexel University's online Master of Science in Artificial Intelligence & Machine Learning is designed for professionals seeking to enhance their skills in this rapidly evolving field. The program focuses on three key areas: data science and analytics, theory of computation and algorithms, and practical applications of AI and machine learning. With a total of 45 quarter credits, students engage with real datasets and cutting-edge tools, preparing them for immediate application in their careers. The curriculum includes core courses such as Introduction to Programming, Applications of Machine Learning, and Machine Learning, alongside a selection of electives that allow for specialization. The program can be completed in as little as two years, and students have the flexibility to choose between full-time and part-time study options. Graduates are equipped to tackle complex problems using AI and machine learning, making them valuable assets in various industries.

Required Courses

• CS 501 - Introduction to Programming
• CS 614 - Applications of Machine Learning
• INFO 629 - Applied Artificial Intelligence
• CS 510 - Introduction to Artificial Intelligence
• CS 613 - Machine Learning
• CS 615 - Deep Learning

Elective Courses

• DSCI 501 - Quantitative Foundations of Data Science
• DSCI 511 - Data Acquisition and Pre-Processing
• DSCI 521 - Data Analysis and Interpretation
• DSCI 631 - Applied Machine Learning for Data Science
• DSCI 632 - Applied Cloud Computing
• INFO 623 - Social Network Analytics
• INFO 659 - Introduction to Data Analytics
• CS 502 - Data Structures and Algorithms
• CS 503 - Systems Basics
• DSCI 691 - Natural Language Processing with Deep Learning
• INFO 612 - Knowledge-based Systems
• INFO 692 - Explainable Artificial Intelligence
• CT 620 - Security, Policy and Governance
• INFO 508 - Information Innovation through Design Thinking
• INFO 590 - Foundations of Data and Information
• INFO 608 - Human-Computer Interaction
• INFO 693 - Human-Artificial Intelligence Interaction
• INFO 725 - Information Policy and Ethics
• CS 660 - Data Analysis at Scale
• CS 521 - Data Structures and Algorithms I
• CS 522 - Data Structures and Algorithms II
• CS 525 - Theory of Computation
• CS 540 - High Performance Computing
• CS 567 - Applied Symbolic Computation
• CS 616 - Robust Deep Learning
• CS 770 - Topics in Artificial Intelligence
• ECES 521 - Probability & Random Variables
• MATH 504 - Linear Algebra & Matrix Analysis
• MATH 510 - Applied Probability and Statistics I
• CS 583 - Introduction to Computer Vision
• CS 589 - Responsible Machine Learning
• CS 610 - Advanced Artificial Intelligence
• CS 611 - Game Artificial Intelligence
• CS 614 - Applications of Machine Learning
• CS 618 - Algorithmic Game Theory
• CS 630 - Cognitive Systems
• DSCI 641 - Recommender Systems for Data Science
• DSCI 691 - Natural Language Processing with Deep Learning
• INFO 629 - Applied Artificial Intelligence
• INFO 693 - Human-Artificial Intelligence Interaction
• BMES 547 - Machine Learning in Biomedical Applications
• ECE 612 - Applied Machine Learning Engineering
• ECE 613 - Neuromorphic Computing