{"id":29278,"date":"2023-12-13T12:07:33","date_gmt":"2023-12-13T17:07:33","guid":{"rendered":"https:\/\/marymount.edu\/academics\/?page_id=29278"},"modified":"2024-05-16T09:01:30","modified_gmt":"2024-05-16T13:01:30","slug":"web-content-for-bs-ai-school-of-tech","status":"publish","type":"page","link":"https:\/\/marymount.edu\/academics\/college-of-business-innovation-leadership-and-technology\/school-of-technology-and-innovation\/undergraduate-programs\/artificial-intelligence-bs\/","title":{"rendered":"Artificial Intelligence (B.S.)"},"content":{"rendered":"
Artificial Intelligence (AI) is playing a significant role in government, business, society and also in our personal lives. Marymount University recognizes the important role of AI engineers in all in the today’s world.<\/p>\n
Marymount University works with community colleges in the region to maximize the credits that can be transferred into the program from dual enrollment programs, community colleges, other accredited 4-year schools.<\/p>\n
The faculty in the program, both full-time and part-time, have extensive expertise in the subjects they teach. They employ hands-on activities where appropriate to reinforce learning. Courses seamlessly integrate labs, enabling students to apply tools and techniques relevant to the professional world while mastering foundational concepts. The learning experience is enriched by a diverse array of extracurricular activities, such as competitions and boot camps<\/p>\n
Students are encouraged to engage in artificial intelligence-related research with full-time faculty in areas such as business and financial analysis, cybersecurity, natural language processing (NLP), etc. A variety of paid and volunteer opportunities are available under the direction of our diverse and experienced faculty.<\/p>\n
To make sure students are ready for the workforce; all students must take a for-credit internship in the AI field before graduation. A minimum of 90 credits with a minimum cumulative GPA of 2.0 is required to register for the internship.<\/p>\n
The B.S. in Artificial Intelligence degree requires at least 120 total credits.<\/p>\n
A minimum grade of C is required in all AI courses. A minimum grade of C+ is required for IT 489 Capstone Project.<\/p>\n
RESIDENCY REQUIREMENT \u2013 Artificial Intelligence<\/strong><\/p>\n Students must complete 21 credits of their artificial intelligence major at Marymount.<\/p>\n LIBERAL ARTS CORE REQUIREMENTS<\/strong><\/p>\n SAMPLE DEGREE PLAN<\/b><\/p>\n Year One – Fall<\/b><\/p>\n Year One \u2013 Spring <\/b><\/p>\n Year Two\u2013 Fall<\/b><\/p>\n Year Two\u2013 Spring<\/b><\/p>\n Year Three \u2013 Fall<\/b><\/p>\n Year Three \u2013 Spring<\/b><\/p>\n Year Four \u2013 Fall<\/b><\/p>\n Year Four \u2013 Spring<\/b><\/p>\n Artificial Intelligence (AI) is playing a significant role in government, business, society and also in our personal lives. Marymount University recognizes the important role of AI engineers in all in the today’s world. THE AI PROGRAM PROVIDES THE FOLLOWING: A solid foundation of artificial intelligence concepts Specific skills in advanced software development, machine learning and […]<\/p>\n\n\n
\n IT 112<\/td>\n Introduction to Computer Systems and Computer Architecture<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 129<\/td>\n Python Scripting<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n MA 218<\/td>\n Probability and Statistics – Depth in Sciences Core course<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 150<\/td>\n Concepts in Artificial Intelligence<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 229<\/td>\n Advanced Python Applications<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 212<\/td>\n Software Architecture and Design<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n MA 200<\/td>\n Calculus II – Math and Depth in Sciences Core course<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 250<\/td>\n Robotics and Embedded Systems<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 208<\/td>\n Computer Networking<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 310<\/td>\n Database Technology<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 315<\/td>\n Operating Systems and Virtualization<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 350<\/td>\n AI: Sensor Networks and IOT<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n DATA 325<\/td>\n Data Analytics<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 323<\/td>\n Junior Seminar<\/td>\n 1<\/td>\n<\/tr>\n \n IT 321<\/td>\n Cloud Computing<\/td>\n 3<\/td>\n<\/tr>\n \n IT 210<\/td>\n Software Engineering<\/td>\n 3<\/td>\n<\/tr>\n \n IT 345<\/td>\n Human Computer Interaction<\/td>\n 3<\/td>\n<\/tr>\n \n DATA 370<\/td>\n Machine Learning<\/td>\n 3<\/td>\n<\/tr>\n \n DATA 360<\/td>\n Natural Language Processing (NLP)<\/td>\n 3<\/td>\n<\/tr>\n \n DATA 395<\/td>\n Data Visualization<\/td>\n 3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n IT 112<\/td>\n Introduction to Computer Systems and Computer Architecture<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n PSY101<\/em><\/td>\n Social Science Core – General Psychology<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n EN 101<\/td>\n Composition I<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n MA 181<\/td>\n Calculus I – <\/em>Math Core course<\/td>\n 4<\/td>\n<\/tr>\n \n PH 100<\/td>\n Exploring Philosophy<\/em><\/td>\n 3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n IT 129<\/td>\n Python Scripting<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n MA 218<\/td>\n Probability and Statistics – <\/em>Depth in Sciences Core course<\/td>\n 3<\/td>\n<\/tr>\n \n IT 150<\/td>\n Concepts in Artificial Intelligence<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n EN 102<\/td>\n Composition II<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n TRS 100<\/td>\n Theological Inquiry<\/em><\/td>\n 3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n IT 229<\/td>\n Advanced Python Applications<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n <\/td>\n History Core Course<\/td>\n 3<\/td>\n<\/tr>\n \n <\/td>\n Natural Science with Laboratory Core course<\/td>\n 4<\/td>\n<\/tr>\n \n <\/td>\n Literature Core Course<\/td>\n 3<\/td>\n<\/tr>\n \n PH 313<\/td>\n Cyberethics – <\/em>Depth in Faith and Reasoning Core course<\/td>\n 3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n IT 212<\/td>\n Software Architecture and Design<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n MA 200<\/td>\n Calculus II – <\/em>Math and Depth in Sciences Core course<\/td>\n 3<\/td>\n<\/tr>\n \n IT 250<\/td>\n Robotics and Embedded Systems<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n <\/td>\n Fine and Performing Arts Core Course<\/td>\n 3<\/td>\n<\/tr>\n \n IT 208<\/td>\n Computer Networking<\/em><\/td>\n 3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n IT 310<\/td>\n Database Technology<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 315<\/td>\n Operating Systems and Virtualization<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n MA 260<\/td>\n Discrete Math for IT- <\/em>Math Core Course and Depth in Sciences<\/td>\n 3<\/td>\n<\/tr>\n \n IT 350<\/td>\n AI: Sensor Networks and IOT<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n DATA 325<\/td>\n Data Analytics<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 323<\/td>\n Junior Seminar<\/td>\n 1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n IT 321<\/td>\n Cloud Computing <\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 210<\/td>\n Software Engineering<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 345<\/td>\n Human Computer Interaction<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n DATA 370<\/td>\n Machine Learning<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n <\/td>\n Elective<\/td>\n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n <\/td>\n Depth in Humanities Core course<\/td>\n 3<\/td>\n<\/tr>\n \n IT 352<\/td>\n AI Trust, Bias and Societal Impacts<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 385<\/td>\n Managing Big Data<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n DATA 450<\/td>\n Advanced Machine Learning<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n IT 490<\/td>\n Internship<\/em><\/td>\n 3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n DATA 360<\/td>\n Natural Language Processing (NLP)<\/em><\/td>\n 3<\/td>\n<\/tr>\n \n DATA 395<\/td>\n Data Visualization <\/em><\/td>\n 3<\/td>\n<\/tr>\n \n <\/td>\n Social Science Core Course<\/td>\n 3<\/td>\n<\/tr>\n \n <\/td>\n Elective Course<\/td>\n 3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"