Lockheed Martin - MS Artificial Intelligence
- Overview
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According to a new report from the World Economic Forum, the demand for artificial intelligence rising is set to create 58 million new jobs by 2022. Even though science fiction often portrays AI as robots with humanoid qualities, the field encompasses a vast amount of products, from Google’s search algorithms to autonomous vehicles like a Tesla. The rapid growth of AI allows creativity to thrive and create endless possibilities for the future.
The artificial intelligence program provides the foundation that will prepare students for future changes in the field. Advanced skills including principles and technologies that underlie AI including logic, regression and machine learning. Students will pursue topics in depth, with hands-on experience built into the courses.
Gain the advanced degree requirements needed to upgrade your salary, earn a promotion or bring your resume to the attention of hiring managers and recruiters by earning your Master of Science in Artificial Intelligence.
Students interested in pursuing their MSAI should have a programming background, experience and ideally an engineering undergraduate degree, and then they can apply the AI technology to their engineering profession.
Prequalify now! A specialist will review your prequalification form and contact you regarding opportunities.
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- PreQualify Now
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Not Accepting Applications
Applications open August 1, 2023
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- Program Schedule and Course Descriptions
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Program Learning Outcomes (PLOs)
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PLO 1. Be able to demonstrate an understanding of advanced knowledge of the practice of artificial intelligence and machine learning, from vision to formulation, analysis, design, validation and deployment.
PLO 2. Be able to tackle complex machine learning and artificial intelligence problems using contemporary principles, algorithms, technologies, methodologies, and tools.
PLO 3. Be able to lead and participate in a team to develop AI and machine learning applications.
PLO 4. Be aware of ethical, economic and environmental implications of their work, as appropriate.
PLO 5. Be able to advance successfully in their profession, and sustain a process of life-long learning in engineering or other professional areas.
PLO 6. Be able to communicate effectively and persuasively with a variety of audiences.
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Student Learning Outcomes (SLOs)
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SLO 1. Understand and apply mathematical principles to formulate and solve problems related to AI systems engineering.
SLO 2. Illustrate the fundamental concepts and building blocks of machine learning and Artificial Intelligence systems.
SLO 3. Identify, formulate, design, and develop AI applications using appropriate machine learning, data engineering, and data mining algorithms, tools, and methodologies.
SLO 4. Demonstrate leadership and ability to participate in a team in a multidisciplinary environment to develop AI and machine learning applications.
SLO 5. Demonstrate awareness of ethical, economic, and environmental implications of their work, as appropriate.
SLO 6. Demonstrate the potential to advance successfully in their profession, and sustain a process of life-long learning in engineering or other related professional areas.
SLO 7. Communicate clearly and persuasively demonstrating technical depth to a variety of audiences.
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- Contact
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Program Specialist
TBA
engineering-extended@sjsu.eduAcademic Program Coordinator
Wencen Wu
wencen.wu@sjsu.edu
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Disclaimer
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Corporate Programs Requirement: You must be a current employee of the host company to enroll.
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Applying for admission to an off-campus cohort at San Jose State University is not a guarantee that the program will occur. Cohorts must meet minimum enrollment standards in order to take place. Please be aware that in the event a cohort does not launch due to low enrollment, any and all associated application fees cannot be refunded.
