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  • Master’s in Artificial Intelligence & Machine Learning Online

    Master of Science in Artificial Intelligence & Machine Learning

    Drexel University’s online MS in Artificial Intelligence & Machine Learning is an interdisciplinary program structured around three focus areas: data science and analytics, theory of computation and algorithms, and applications of artificial intelligence and machine learning. Designed for current practitioners, you’ll work with real datasets and state-of-the-art tools and systems to build knowledge and experience that can be used immediately in the workplace.

    A strong background in computer science is required for this program. For those who do not have a bachelor’s or master’s degree in computer science, Drexel’s Graduate Certificate in Computer Science can serve as the entry point into the program.

    The 45-quarter credit MS in Artificial Intelligence & Machine Learning is housed in Drexel’s College of Computing and Informatics. Faculty have active research experience in machine learning, computer vision, game AI, data science, cognitive science, high performance computing, software engineering, applied machine learning in gaming, and applied machine learning in security.

    The MS in Artificial Intelligence & Machine Learning will prepare you to:

    • Analyze a problem and identify and define the use of artificial intelligence and/or machine learning as appropriate to its solution
    • Understand the implementation and use of existing artificial intelligence and/or machine learning tools and systems
    • Apply mathematical foundations, algorithmic principles, and computational knowledge in the modeling and design of artificial intelligence and machine learning systems
    • Design, implement, and evaluate a computer-based artificial intelligence and machine learning system, process, component, or program to meet a specific need
    • Apply sound software engineering principles in the construction of computer-based artificial intelligence and machine learning systems
    • Understand the ethical aspects of artificial intelligence and machine learning, and communicate these aspects as part of result interpretation
    • Understand and communicate the legal and ethical aspects of using artificial intelligence and machine learning in societal contexts

    What is an MS in Artificial Intelligence?

    The MS in Artificial Intelligence covers theories and principles in artificial intelligence – a branch of computer science that focuses on creating machines that can perform tasks with human-like intelligence.

    Is a Master’s Degree Required For Machine Learning?

    While a master’s degree is not required for machine learning, it can help you stand out in the field, especially if you don’t have previous work experience in machine learning or AI. Drexel’s program focuses specifically on artificial intelligence and machine learning foundations, algorithms, and systems.

    What Can You Do with a Master’s in Artificial Intelligence?

    According to a 2018 LinkedIn report, AI skills were among the fastest-growing skills on the platform, and there was a 190% global increase from 2015-2017.

    Common jobs within the industry include:

    • Data Scientist
    • Software Engineer
    • Deep Learning Engineer
    • Algorithm Developer
    • Computer Vision Engineer

    How Much Can You Earn with an MS in Artificial Intelligence & Machine Learning?

    Artificial Intelligence & Machine Learning Career Opportunities

    Job Title

    Salary*

    Data Scientist

    $129,000

    Computer and Information Research Scientist

    $133,750

    Computer Systems Analyst

    $111,350

    Market Research Analyst

    $87,550

    Operations Research Analyst

    $89,300

    *Data from Wanted Analytics

    How Long Does It Take to Complete an MS in Artificial Intelligence?

    The MS in Artificial Intelligence & Machine Learning can be completed on either a full- or part-time basis. You can complete the degree in as little as two years.

    Unlike many universities, most of Drexel’s programs operate on a quarter system. Each quarter term is 10 weeks long, and there are four quarters in Drexel’s academic year. To learn more about Drexel’s quarter system, check out our online guide.

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    Related Program


    Drexel University offers a variety of Graduate Minors that can be added to any master's degree program.
    State restrictions may apply to some programs.

    Curriculum

    This program is organized into four 10-week quarters per year (as opposed to the traditional two semester system) which means you can take more courses in a shorter time period. One semester credit is equivalent to 1.5 quarter credits.

    Core Courses
    CS 591 Artificial Intelligence and Machine Learning Capstone I 3.0
    CS 592 Artificial Intelligence and Machine Learning Capstone II 3.0
    Choose appropriate core courses for concentration: 9.0
    Applied
    CS 501
    Introduction to Programming
    or CS 570
    Programming Foundations
    CS 614
    Applications of Machine Learning
    INFO 629
    Applied Artificial Intelligence
    Computational
    CS 510
    Introduction to Artificial Intelligence
    CS 613
    Machine Learning
    CS 615
    Deep Learning
    Breadth Requirements 9.0
    One course must be selected from each group for the appropriate concentration
    Applied
    Data Science Foundations
    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 546
    Data Analytics for Community-Based Data and Service
    INFO 623
    Social Network Analytics
    INFO 634
    Data Mining
    INFO 659
    Introduction to Data Analytics
    AI Foundations
    CS 502
    Data Structures and Algorithms
    CS 503
    Systems Basics
    CS 510
    Introduction to Artificial Intelligence
    CS 613
    Machine Learning
    INFO 612
    Knowledge-based Systems
    INFO 692
    Explainable Artificial Intelligence
    Human-Centered Computing
    CS 661
    Responsible Data Analysis
    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 615
    Designing with Data
    INFO 616
    Social and Collaborative Computing
    INFO 690
    Understanding Users: User Experience Research Methods
    INFO 691
    Prototyping the User Experience
    INFO 693
    Human–Artificial Intelligence Interaction
    INFO 725
    Information Policy and Ethics
    Computational
    Data Science and Analytics
    CS 660
    Data Analysis at Scale
    CS 661
    Responsible Data Analysis
    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 546
    Data Analytics for Community-Based Data and Service
    INFO 623
    Social Network Analytics
    INFO 634
    Data Mining
    INFO 659
    Introduction to Data Analytics
    Algorithmic Foundations
    CS 521
    Data Structures and Algorithms I
    CS 522
    Data Structures and Algorithms II
    CS 525
    Theory of Computation
    CS 567
    Applied Symbolic Computation
    CS 618
    Algorithmic Game Theory
    CS 620
    Advanced Data Structure and Algorithms
    CS 621
    Approximation Algorithms
    CS 650
    Program Generation and Optimization
    DSCI 501
    Quantitative Foundations of Data Science
    ECES 521
    Probability & Random Variables
    ECES 523
    Detection & Estimation Theory
    MATH 504
    Linear Algebra & Matrix Analysis
    MATH 510
    Applied Probability and Statistics I
    Applications of AI/ML
    CS 614
    Applications of Machine Learning
    CS 583
    Introduction to Computer Vision
    CS 610
    Advanced Artificial Intelligence
    CS 611
    Game Artificial Intelligence
    CS 612
    Knowledge-based Agents
    CS 618
    Algorithmic Game Theory
    CS 630
    Cognitive Systems
    CS 634
    Advanced Computer Vision
    CS 770
    Topics in Artificial Intelligence
    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
    Electives 21.0
    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 Credits 45.0

    View Course Descriptions

    Admissions Criteria

    • A four-year bachelor's 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 Graduate Certificate in Computer Science
    • GPA of 3.0 or higher, in a completed degree program, bachelor’s degree or above

    Required Documents

    With multiple ways to submit documents, Drexel makes it easy to complete your application. Learn more by visiting our Completing Your Application Guide.

    • A completed application
    • Official transcripts from all universities or colleges and other post-secondary educational institutions attended (including trade schools)
    • One letter of recommendation required, two suggested
    • Essay/Statement of Purpose
    • Resume
    • Graduate Record Examination (GRE) Scores (five years old or less) are recommended, but not required for international students and domestic students with a GPA below 3.0
    • Additional requirements for International Students

    Computer Requirements

    You must have access to a computer that meets or exceeds the minimum configuration outlined in the College of Computing and Informatics's Computer and Technology Requirements Guide.

    Tuition

    The tuition rate for the academic year 2022-2023 is $1396 per credit.

    • This program is eligible for Financial Aid.
    • Special tuition rates available for Drexel University AlumniMilitary members, and members of our Partner Organizations
      • These rates apply only to new online students and students being readmitted.
      • Tuition rates are subject to increase with the start of each academic year in the fall term.
      • All students must contact applyDUonline@drexel.edu within the first two weeks of the term to request tuition savings for which they qualify.
      • Special rates cannot be combined. If you qualify for more than one special rate, you'll be given the one with the largest savings.
      • When receiving special tuition plans with Drexel University Online, you may not combine them with other tuition benefits that may be available from Drexel University.

     

    Academic Calendar

    2022-2023 Academic Year

    Term

    Classes Begin

    Classes End

    Exams Begin

    Exams End

    Fall 2022

    September 19, 2022

    December 3, 2022

    December 5, 2022

    December 10, 2022

    Winter 2023

    January 9, 2023

    March 18, 2023

    March 20, 2023

    March 25, 2023

    Spring 2023

    April 3, 2023

    June 10, 2023

    June 12, 2023

    June 17, 2023

    Summer 2023

    June 26, 2023

    September 2, 2023

    September 4, 2023

    September 9, 2023

     

    2021-2022 Academic Year

    Term

    Classes Begin

    Classes End

    Exams Begin

    Exams End

    Fall 2021

    September 20, 2021

    December 4, 2021

    December 6, 2021

    December 11, 2021

    Winter 2022

    January 3, 2022

    March 12, 2022

    March 14, 2022

    March 19, 2022

    Spring 2022

    March 28, 2022

    June 4, 2022

    June 6, 2022

    June 11, 2022

    Summer 2022

    June 21, 2022

    August 29, 2022

    August 30, 2022

    September 3, 2022

     

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