Protected: Master of Science in Artificial Intelligence (MScAI)

Protected: Master of Science in Artificial Intelligence (MScAI)

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MScAI Program Learning Outcomes

MScAI Program Learning Outcomes

Develop a comprehensive understanding of artificial intelligence theory, algorithms, and applications to address modern challenges and opportunities. Master advanced techniques such as machine learning, deep learning, robotics, and data science to design and implement innovative solutions across diverse industries. Build expertise in analyzing and solving complex AI problems, fostering practical innovations that contribute to the field's evolution. Develop the ability to communicate AI concepts and findings effectively to varied audiences, showcasing proficiency in making complex ideas accessible. Emphasize ethical and responsible AI practices, ensuring sustainable and equitable advancements in AI technologies.

The Master of Science in Artificial Intelligence encourages students to achieve the following educational outcomes:

1
Develop a comprehensive understanding of artificial intelligence theory, algorithms, and applications and analyze current AI-based opportunities and challenges.
2
Analyze the latest AI techniques including machine learning, deep learning, robotics, fuzzy logic, and data science, and apply them in providing solutions in different environments.
3
Identify, analyze, and solve complex AI-related problems, fostering innovation in the field and contributing to practical solutions.
4
Research and evaluate Artificial Intelligence techniques to address complex real-world problems through innovative solutions.
5
Prepare and communicate AI concepts, findings, and solutions to diverse audiences, including professionals, stakeholders, and the general public, demonstrating their proficiency in conveying complex ideas in a clear and accessible manner.
6
Demonstrate a commitment to ethical and responsible AI practices, emphasizing the importance of ethical considerations in the development and deployment of AI technologies.

Program Requirements

  • Admissions Requirements

    For acceptance into the Master of Science in Artificial Intelligence (MScAI) degree program, applicants must hold:

    • Bachelor's degree in the field of information technology, engineering, computer science, or related fields (i.e., Electrical or Electronics Engineering) from a regional and/or national college (or its equivalent from a recognized institution) with a minimum 2.5 cumulative GPA.

    AND

    • Undergraduate degrees obtained outside of the United States will only be accepted if they have been evaluated by a member in good standing of the National Association of Credential Evaluation Services (NACES) or another nationally recognized credentialing service. In this case, the listed U.S. degree equivalency will be used.

    Alternatively, the Department of Computer Science may grant provisional approval to candidates with a B.Sc. in a different area with the requirement that they succeed in B.Sc. level courses of the required prerequisites with a minimum grade of 83% i.e., letter grade B from the first time.

  • Graduation Requirements

    Students must complete forty-two (42) prescribed credit hours with a program GPA (PGPA) of 3.0 or higher to graduate. Students must apply for graduation. Upon graduation and fulfillment of all academic requirements, students receive a Master of Science in Artificial Intelligence degree.

  • Practical Learning Experience Requirements

    Westcliff University has integrated Practical Learning Experience (PLE) as a graduation requirement for the applied version of the Master of Science in Artificial Intelligence program. This graduation requirement is satisfied by completing the six (6) credit-bearing internship courses within the program. These courses are assessed on a Credit/No Credit basis. Westcliff University may require a start date up to 30 days prior to the start of classes to meet the onboarding requirements of the professional workplace where the PLE will be conducted. Students are encouraged to take full advantage of the opportunities afforded to them in practical learning and maximize their potential career placement or advancement upon graduation.

    The primary objective of the internship course is to align the graduate technology program with job experience. The internship course allows students the opportunity to gain practical training and real-life experience pertaining to their current program of study. Engaging in an internship provides students with networking, educational, and career advancement opportunities. The university does not have a direct internship placement service but works with services in the community to alert students of available placements and job openings at outside businesses. There is a close relationship between the graduate program course of study and the internship course. The high expectations of being an intern/employee and a graduate-level student are part of the internship course experience.

Program Information

  • Required Courses

    Master of Science in Artificial Intelligence Program Requirements - 42 Credit Hours Total

    Core Courses - 33 Credit Hours

    MSAI 500 Fundamentals of Artificial Intelligence 3 credit hours
    MIS 505 Advanced Mathematical Methods for AI 3 credit hours
    MSAI 506 Machine Learning 3 credit hours
    MSAI 510 Introduction to Data Science 3 credit hours
    MSAI 530 Advanced AI Programming and Frameworks 3 credit hours
    MSAI 540 Fuzzy Logic Systems 3 credit hours
    MSAI 550 Linear Systems Theory 3 credit hours
    MSAI 560 Natural Language Processing 3 credit hours
    MSAI 565 Information Retrieval 3 credit hours
    MSAI 570 Big Data Analytics 3 credit hours
    MSAI 575 Data Mining 3 credit hours

     
    Practical Learning Internship Courses - 6 Credit Hours

    INT 601 MS Graduate Internship I 1 credit hour
    INT 602 MS Graduate Internship II 1 credit hour
    INT 603 MS Graduate Internship III 1 credit hour
    INT 604 MS Graduate Internship IV 1 credit hour
    INT 605 MS Graduate Internship V 1 credit hour
    INT 606 MS Graduate Internship VI 1 credit hour

     
    Capstone Course - 3 Credit Hours

    MSAI 690 AI Capstone 3 credit hours
  • Program Concentrations

    Big Data Analytics - The Big Data Analytics concentration is designed to provide students with in-depth knowledge of technologies relevant to big data management. Students understand the design and maintenance of the infrastructure store, access, and transfer extremely large amounts of data across wide area networks.

    Data Mining - The Data Mining concentration will help students develop the skills needed to analyze large datasets to discover meaningful trends, identify outcomes and solve real-world business challenges.

    Machine Learning - The Machine Learning concentration provides students with a broad introduction to machine learning topics and core concepts. This concentration is intended for students interested in topics related to theory, design and synthesis of intelligent machines.

  • Course Catalog and Student Handbook
    Student Handbook and Catalog

  • Scholarship Application

    As a Westcliff student, you have access to a powerful network of support from staff, faculty, alumni, and many others who take pride in investing in you. Scholarships are made possible by generous benefactors who are passionate about supporting your success.

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Program Requirements