Artificial Intelligence (B.S.)
| Code | Title | Hours |
|---|---|---|
| Major Requirements | ||
| CS 1120 | Computer Science I | 4 |
| CS 1121 | Computer Science II | 3 |
| AIML 1101 | AI Fundamentals: Impacts, Ethics, and Applications (AI Fundamentals) | 3 |
| AIML 2001 | Introduction to Machine Learning (Intro to Machine Learning) | 3 |
| ENGR 2120 | Python Programming Essentials | 3 |
| CYB 2200 | Secure Coding and Analysis | 3 |
| CS 3195 | Analysis of Algorithms | 3 |
| CS 4622 | Applied Data Science with Python | 3 |
| CS 4701 | Artificial Intelligence | 3 |
| CS 4715 | Deep Learning | 3 |
| CS 4741 | Natural Language Processing | 3 |
| CS 4771 | Python for Machine Learning | 3 |
| AIML 4010 | Contemporary Issues in AI (Senior Seminar) | 1 |
| AIML 4800 | AI Senior Capstone Design I (Senior Capstone I ) | 3 |
| AIML 4810 | AI Senior Capstone Design II (Senior Capstone II) | 3 |
| Mathematic | ||
| MATH 1170 | Calculus I | 4 |
| MATH 1750 | Calculus II | 4 |
| MATH 1760 | Discrete Mathematics | 3 |
| MATH 3300 | Linear Algebra | 3 |
| Statistics | ||
| STAT 3010 | Probability and Statistics | 3 |
| or STAT 2510 | Statistical Methods | |
| Technical Writing | ||
| ENGL 2020 | Technical Writing I | 3 |
| or ENGL 3170 | Technical Writing II | |
| In Addition: Students may choose the General AI Studies emphasis or one of the five emphases. The capstone project for students in an emphasis must be directly relevant to their selected emphasis area. | 21 | |
General AI Studies | ||
Emphasis 1: Robotics AI | ||
Emphasis 2: AI Cyber | ||
Emphasis 3: Secure AI | ||
Emphasis 4: AI Infrastructure & Operations | ||
Emphasis 5: AI in Data Science | ||
| Total Hours | 85 | |
A. General AI Studies Emphasis
| Code | Title | Hours |
|---|---|---|
| Select seven elective courses with a CS, CYB, or AIML prefix. At least four of the seven elective courses must be upper division. | 21 | |
| Total Hours | 21 | |
Courses to total 120 credits for this degree
B. Robotics AI Emphasis
| Code | Title | Hours |
|---|---|---|
| CS 1550 | Computer Organization and Architecture | 3 |
| CS 2XXX | Course CS 2XXX Not Found (Introduction to Robotic Systems) | 3 |
| CS 2240 | Computer Operating Systems | 3 |
| Select 4 courses from the list below: | 12 | |
| Real-Time Operating Systems | ||
| Embedded Systems | ||
| Robotic Systems Engineering I | ||
| Robotic Systems Engineering II | ||
| Computational Biology: Sequence Analysis | ||
| AI Data Analysis for Industrial Applications | ||
| Evolutionary Computation | ||
| Machine Vision | ||
| Total Hours | 21 | |
Courses to total 120 credits for this degree
C. AI Cyber Emphasis
| Code | Title | Hours |
|---|---|---|
| CYB 1100 | Cybersecurity and Privacy | 3 |
| CYB 2100 | Cybersecurity Architectures and Management | 3 |
| CYB 3100 | Cybersecurity Technical Foundations | 3 |
| CYB 3300 | Networking Fundamentals | 3 |
| CYB 3400 | Network Defense | 3 |
| CYB 4400 | Software Vulnerability Analysis | 3 |
| CYB 4442 | IoT and CPS Security (IoT and CPS Security) | 3 |
| Total Hours | 21 | |
Courses to total 120 credits for this degree
D. Secure AI Emphasis
| Code | Title | Hours |
|---|---|---|
| CS 1550 | Computer Organization and Architecture | 3 |
| CS 2240 | Computer Operating Systems | 3 |
| CYB 3100 | Cybersecurity Technical Foundations | 3 |
| CYB 3300 | Networking Fundamentals | 3 |
| CYB 3400 | Network Defense | 3 |
| CYB 3500 | Operating System Defense | 3 |
| CS 4727 | Adversarial Machine Learning | 3 |
| Total Hours | 21 | |
Courses to total 120 credits for this degree
E. AI Infrastructure & Operations Emphasis
| Code | Title | Hours |
|---|---|---|
| Emphasis: AI Infrastructure & Operations | ||
| CS 1550 | Computer Organization and Architecture | 3 |
| CS 2240 | Computer Operating Systems | 3 |
| CYB 3300 | Networking Fundamentals | 3 |
| CS 4211 | Parallel Programming | 3 |
| Select 3 courses from the list below: | 9 | |
| Database Systems | ||
| Database Management Systems Design | ||
| Advanced Operating Systems | ||
| Multi-User Games and Virtual Environments | ||
CS 4XXX | Course CS 4XXX Not Found (Digital Twins ) | |
Elective course with CS, CYB, or AIML prefix | ||
| Total Hours | 21 | |
Courses to total 120 credits for this degree
F. AI in Data Science Emphasis
| Code | Title | Hours |
|---|---|---|
| CS 3600 | Database Systems | 4 |
| CS 4621 | Data Science | 3 |
| CS 4625 | Semantic Web and Open Data | 3 |
| Select 4 courses from the list below: | 11 | |
| Database Management Systems Design | ||
| Machine Learning | ||
| Convex Optimization | ||
| Adversarial Machine Learning | ||
| Probability Theory | ||
| Mathematical Statistics | ||
Elective course with CS, CYB, or AIML prefix | ||
| Total Hours | 21 | |
Courses to total 120 credits for this degree.
ourses to total at least 120 credits for this degree, not counting prerequisites that may be required for registration in MATH 1170 or ENGL 1102. Note: students whose standardized test scores allow them to register for ENGL 1102 without first taking ENGL 1101 will automatically receive credit for ENGL 1101 upon successful completion of ENGL 1102.
Students who place directly into MATH 1170 are required to enroll in an additional elective to meet the minimum 120 credits for a baccalaureate degree (J-1-a).
General AI Emphasis
| Fall Term 1 | Hours | |
|---|---|---|
| COMM 1101 | Fundamentals of Oral Communication | 3 |
| CS 1120 | Computer Science I | 4 |
| ENGL 1101 | Writing and Rhetoric I | 3 |
| MATH 1143 | Precalculus I: Algebra | 3 |
| MATH 1144 | Precalculus II: Trigonometry | 1 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Hours | 17 | |
| Spring Term 1 | ||
| AIML 1101 | AI Fundamentals: Impacts, Ethics, and Applications | 3 |
| CS 1121 | Computer Science II | 3 |
| ENGL 1102 | Writing and Rhetoric II | 3 |
| MATH 1170 | Calculus I | 4 |
| MATH 1760 | Discrete Mathematics | 3 |
| Hours | 16 | |
| Fall Term 2 | ||
| ENGR 2120 | Python Programming Essentials | 3 |
| MATH 1750 | Calculus II | 4 |
| Major Elective, Technical Elective Course | 3 | |
| Scientific Ways of Knowing (course with Lab) | 4 | |
| Hours | 14 | |
| Spring Term 2 | ||
| AIML 2001 | Introduction to Machine Learning | 3 |
| CYB 2200 | Secure Coding and Analysis | 3 |
| STAT 3010 or STAT 2510 | Probability and Statistics or Statistical Methods | 3 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Scientific Ways of Knowing Course (CORS recommended) | 3 | |
| Hours | 15 | |
| Fall Term 3 | ||
| CS 3195 | Analysis of Algorithms | 3 |
| MATH 3300 | Linear Algebra | 3 |
| American Experience Course | 3 | |
| International Course | 3 | |
| Major Elective, Technical Elective Course | 3 | |
| Hours | 15 | |
| Spring Term 3 | ||
| CS 4622 | Applied Data Science with Python | 3 |
| CS 4771 | Python for Machine Learning | 3 |
| ENGL 3170 or ENGL 2020 | Technical Writing II or Technical Writing I | 3 |
| Major Elective, Technical Elective Course | 3 | |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Fall Term 4 | ||
| AIML 4800 | AI Senior Capstone Design I | 3 |
| CS 4715 | Deep Learning | 3 |
| Major Elective, Technical Elective Course | 3 | |
| Major Elective, Technical Elective Course | 3 | |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Spring Term 4 | ||
| AIML 4010 | Contemporary Issues in AI | 1 |
| AIML 4810 | AI Senior Capstone Design II | 3 |
| CS 4701 | Artificial Intelligence | 3 |
| CS 4741 | Natural Language Processing | 3 |
| Major Elective, Technical Elective Course | 3 | |
| Major Elective, Technical Elective Course | 3 | |
| Hours | 16 | |
| Total Hours | 123 | |
Robotics AI Emphasis
| Fall Term 1 | Hours | |
|---|---|---|
| COMM 1101 | Fundamentals of Oral Communication | 3 |
| CS 1120 | Computer Science I | 4 |
| ENGL 1101 | Writing and Rhetoric I | 3 |
| MATH 1143 | Precalculus I: Algebra | 3 |
| MATH 1144 | Precalculus II: Trigonometry | 1 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Hours | 17 | |
| Spring Term 1 | ||
| AIML 1101 | AI Fundamentals: Impacts, Ethics, and Applications | 3 |
| CS 1121 | Computer Science II | 3 |
| ENGL 1102 | Writing and Rhetoric II | 3 |
| MATH 1170 | Calculus I | 4 |
| MATH 1760 | Discrete Mathematics | 3 |
| Hours | 16 | |
| Fall Term 2 | ||
| CS 1550 | Computer Organization and Architecture | 3 |
| ENGR 2120 | Python Programming Essentials | 3 |
| MATH 1750 | Calculus II | 4 |
| Scientific Ways of Knowing Course (Course with lab) | 4 | |
| Hours | 14 | |
| Spring Term 2 | ||
| AIML 2001 | Introduction to Machine Learning | 3 |
| CYB 2200 | Secure Coding and Analysis | 3 |
| STAT 3010 or STAT 2510 | Probability and Statistics or Statistical Methods | 3 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Scientific Ways of Knowing Course (CORS recommended) | 3 | |
| Hours | 15 | |
| Fall Term 3 | ||
| CS 3195 | Analysis of Algorithms | 3 |
| CS 2XXX | Course CS 2XXX Not Found | 3 |
| MATH 3300 | Linear Algebra | 3 |
| American Experience Course | 3 | |
| International Course | 3 | |
| Hours | 15 | |
| Spring Term 3 | ||
| CS 4622 | Applied Data Science with Python | 3 |
| CS 4771 | Python for Machine Learning | 3 |
| CS 2240 | Computer Operating Systems | 3 |
| ENGL 3170 or ENGL 2020 | Technical Writing II or Technical Writing I | 3 |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Fall Term 4 | ||
| AIML 4800 | AI Senior Capstone Design I | 3 |
| CS 4715 | Deep Learning | 3 |
| Major Elective, Technical Elective Course | 3 | |
| Major Elective, Technical Elective Course | 3 | |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Spring Term 4 | ||
| AIML 4010 | Contemporary Issues in AI | 1 |
| AIML 4810 | AI Senior Capstone Design II | 3 |
| CS 4701 | Artificial Intelligence | 3 |
| CS 4741 | Natural Language Processing | 3 |
| Major Elective, Technical Elective Course | 3 | |
| Major Elective, Technical Elective Course | 3 | |
| Hours | 16 | |
| Total Hours | 123 | |
AI Cyber Emphasis
| Fall Term 1 | Hours | |
|---|---|---|
| COMM 1101 | Fundamentals of Oral Communication | 3 |
| CS 1120 | Computer Science I | 4 |
| ENGL 1101 | Writing and Rhetoric I | 3 |
| MATH 1143 | Precalculus I: Algebra | 3 |
| MATH 1144 | Precalculus II: Trigonometry | 1 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Hours | 17 | |
| Spring Term 1 | ||
| AIML 1101 | AI Fundamentals: Impacts, Ethics, and Applications | 3 |
| CS 1121 | Computer Science II | 3 |
| ENGL 1102 | Writing and Rhetoric II | 3 |
| MATH 1170 | Calculus I | 4 |
| MATH 1760 | Discrete Mathematics | 3 |
| Hours | 16 | |
| Fall Term 2 | ||
| CYB 1100 | Cybersecurity and Privacy | 3 |
| ENGR 2120 | Python Programming Essentials | 3 |
| MATH 1750 | Calculus II | 4 |
| Scientific Ways of Knowing Course (Course with Lab) | 4 | |
| Hours | 14 | |
| Spring Term 2 | ||
| AIML 2001 | Introduction to Machine Learning | 3 |
| CYB 2200 | Secure Coding and Analysis | 3 |
| STAT 3010 or STAT 2510 | Probability and Statistics or Statistical Methods | 3 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Scientific Ways of Knowing Course (CORS recommended) | 3 | |
| Hours | 15 | |
| Fall Term 3 | ||
| CS 3195 | Analysis of Algorithms | 3 |
| CYB 2100 | Cybersecurity Architectures and Management | 3 |
| MATH 3300 | Linear Algebra | 3 |
| International Course | 3 | |
| American Experience Course | 3 | |
| Hours | 15 | |
| Spring Term 3 | ||
| CS 4622 | Applied Data Science with Python | 3 |
| CS 4771 | Python for Machine Learning | 3 |
| CYB 3100 | Cybersecurity Technical Foundations | 3 |
| ENGL 3170 or ENGL 2020 | Technical Writing II or Technical Writing I | 3 |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Fall Term 4 | ||
| AIML 4800 | AI Senior Capstone Design I | 3 |
| CS 4715 | Deep Learning | 3 |
| CYB 3300 | Networking Fundamentals | 3 |
| CYB 4400 | Software Vulnerability Analysis | 3 |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Spring Term 4 | ||
| AIML 4010 | Contemporary Issues in AI | 1 |
| AIML 4810 | AI Senior Capstone Design II | 3 |
| CS 4701 | Artificial Intelligence | 3 |
| CS 4741 | Natural Language Processing | 3 |
| CYB 3400 | Network Defense | 3 |
| CYB 4442 | IoT and CPS Security | 3 |
| Hours | 16 | |
| Total Hours | 123 | |
Secure AI Emphasis
| Fall Term 1 | Hours | |
|---|---|---|
| COMM 1101 | Fundamentals of Oral Communication | 3 |
| CS 1120 | Computer Science I | 4 |
| ENGL 1101 | Writing and Rhetoric I | 3 |
| MATH 1143 | Precalculus I: Algebra | 3 |
| MATH 1144 | Precalculus II: Trigonometry | 1 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Hours | 17 | |
| Spring Term 1 | ||
| AIML 1101 | AI Fundamentals: Impacts, Ethics, and Applications | 3 |
| CS 1121 | Computer Science II | 3 |
| ENGL 1102 | Writing and Rhetoric II | 3 |
| MATH 1170 | Calculus I | 4 |
| MATH 1760 | Discrete Mathematics | 3 |
| Hours | 16 | |
| Fall Term 2 | ||
| CS 1550 | Computer Organization and Architecture | 3 |
| ENGR 2120 | Python Programming Essentials | 3 |
| MATH 1750 | Calculus II | 4 |
| Scientific Ways of Knowing Course (Course with Lab) | 4 | |
| Hours | 14 | |
| Spring Term 2 | ||
| AIML 2001 | Introduction to Machine Learning | 3 |
| CYB 2200 | Secure Coding and Analysis | 3 |
| STAT 3010 or STAT 2510 | Probability and Statistics or Statistical Methods | 3 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Scientific Ways of Knowing Course (CORS recommended) | 3 | |
| Hours | 15 | |
| Fall Term 3 | ||
| CS 3195 | Analysis of Algorithms | 3 |
| CS 2240 | Computer Operating Systems | 3 |
| MATH 3300 | Linear Algebra | 3 |
| American Experience Course | 3 | |
| International Course | 3 | |
| Hours | 15 | |
| Spring Term 3 | ||
| CS 4622 | Applied Data Science with Python | 3 |
| CS 4771 | Python for Machine Learning | 3 |
| CYB 3100 | Cybersecurity Technical Foundations | 3 |
| ENGL 3170 or ENGL 2020 | Technical Writing II or Technical Writing I | 3 |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Fall Term 4 | ||
| AIML 4800 | AI Senior Capstone Design I | 3 |
| CS 4715 | Deep Learning | 3 |
| CYB 3300 | Networking Fundamentals | 3 |
| CYB 3500 | Operating System Defense | 3 |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Spring Term 4 | ||
| AIML 4010 | Contemporary Issues in AI | 1 |
| AIML 4810 | AI Senior Capstone Design II | 3 |
| CS 4701 | Artificial Intelligence | 3 |
| CS 4741 | Natural Language Processing | 3 |
| CS 4727 | Adversarial Machine Learning | 3 |
| CYB 3400 | Network Defense | 3 |
| Hours | 16 | |
| Total Hours | 123 | |
AI Infrastructure & Operations Emphasis
| Fall Term 1 | Hours | |
|---|---|---|
| COMM 1101 | Fundamentals of Oral Communication | 3 |
| CS 1120 | Computer Science I | 4 |
| ENGL 1101 | Writing and Rhetoric I | 3 |
| MATH 1143 | Precalculus I: Algebra | 3 |
| MATH 1144 | Precalculus II: Trigonometry | 1 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Hours | 17 | |
| Spring Term 1 | ||
| AIML 1101 | AI Fundamentals: Impacts, Ethics, and Applications | 3 |
| CS 1121 | Computer Science II | 3 |
| ENGL 1102 | Writing and Rhetoric II | 3 |
| MATH 1170 | Calculus I | 4 |
| MATH 1760 | Discrete Mathematics | 3 |
| Hours | 16 | |
| Fall Term 2 | ||
| CS 1550 | Computer Organization and Architecture | 3 |
| ENGR 2120 | Python Programming Essentials | 3 |
| MATH 1750 | Calculus II | 4 |
| Scientific Ways of Knowing Course (Course with lab) | 4 | |
| Hours | 14 | |
| Spring Term 2 | ||
| AIML 2001 | Introduction to Machine Learning | 3 |
| CYB 2200 | Secure Coding and Analysis | 3 |
| STAT 3010 or STAT 2510 | Probability and Statistics or Statistical Methods | 3 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Scientific Ways of Knowing Course (CORS recommended) | 3 | |
| Hours | 15 | |
| Fall Term 3 | ||
| CS 3195 | Analysis of Algorithms | 3 |
| CS 2240 | Computer Operating Systems | 3 |
| MATH 3300 | Linear Algebra | 3 |
| American Experience Course | 3 | |
| International Course | 3 | |
| Hours | 15 | |
| Spring Term 3 | ||
| CS 4622 | Applied Data Science with Python | 3 |
| CS 4771 | Python for Machine Learning | 3 |
| CS 4211 | Parallel Programming | 3 |
| ENGL 3170 or ENGL 2020 | Technical Writing II or Technical Writing I | 3 |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Fall Term 4 | ||
| AIML 4800 | AI Senior Capstone Design I | 3 |
| CS 4715 | Deep Learning | 3 |
| CYB 3300 | Networking Fundamentals | 3 |
| Major Elective, Technical Elective Course | 3 | |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Spring Term 4 | ||
| AIML 4010 | Contemporary Issues in AI | 1 |
| AIML 4810 | AI Senior Capstone Design II | 3 |
| CS 4701 | Artificial Intelligence | 3 |
| CS 4741 | Natural Language Processing | 3 |
| Major Elective, Technical Elective Course | 3 | |
| Major Elective, Technical Elective Course | 3 | |
| Hours | 16 | |
| Total Hours | 123 | |
AI in Data Science Emphasis
| Fall Term 1 | Hours | |
|---|---|---|
| COMM 1101 | Fundamentals of Oral Communication | 3 |
| CS 1120 | Computer Science I | 4 |
| ENGL 1101 | Writing and Rhetoric I | 3 |
| MATH 1143 | Precalculus I: Algebra | 3 |
| MATH 1144 | Precalculus II: Trigonometry | 1 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Hours | 17 | |
| Spring Term 1 | ||
| AIML 1101 | AI Fundamentals: Impacts, Ethics, and Applications | 3 |
| CS 1121 | Computer Science II | 3 |
| ENGL 1102 | Writing and Rhetoric II | 3 |
| MATH 1170 | Calculus I | 4 |
| MATH 1760 | Discrete Mathematics | 3 |
| Hours | 16 | |
| Fall Term 2 | ||
| CS 1550 | Computer Organization and Architecture | 3 |
| ENGR 2120 | Python Programming Essentials | 3 |
| MATH 1750 | Calculus II | 4 |
| Scientific Ways of Knowing Course (Course with lab) | 4 | |
| Hours | 14 | |
| Spring Term 2 | ||
| AIML 2001 | Introduction to Machine Learning | 3 |
| CYB 2200 | Secure Coding and Analysis | 3 |
| STAT 3010 or STAT 2510 | Probability and Statistics or Statistical Methods | 3 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Scientific Ways of Knowing Course (CORS recommended) | 3 | |
| Hours | 15 | |
| Fall Term 3 | ||
| CS 3195 | Analysis of Algorithms | 3 |
| CS 3600 | Database Systems | 4 |
| MATH 3300 | Linear Algebra | 3 |
| American Experience Course | 3 | |
| International Course | 3 | |
| Hours | 16 | |
| Spring Term 3 | ||
| CS 4622 | Applied Data Science with Python | 3 |
| CS 4771 | Python for Machine Learning | 3 |
| ENGL 3170 or ENGL 2020 | Technical Writing II or Technical Writing I | 3 |
| Major Elective, Technical Elective Course | 3 | |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Fall Term 4 | ||
| AIML 4800 | AI Senior Capstone Design I | 3 |
| CS 4715 | Deep Learning | 3 |
| CS 4621 | Data Science | 3 |
| Major Elective, Technical Elective Course | 3 | |
| Social & Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Spring Term 4 | ||
| AIML 4010 | Contemporary Issues in AI | 1 |
| AIML 4810 | AI Senior Capstone Design II | 3 |
| CS 4701 | Artificial Intelligence | 3 |
| CS 4741 | Natural Language Processing | 3 |
| CS 4625 | Semantic Web and Open Data | 3 |
| Major Elective, Technical Elective Course | 3 | |
| Hours | 16 | |
| Total Hours | 124 | |
The B.S. in AI program is designed to ensure that graduates achieve six defined student learning outcomes (LOs):
- Analyze a complex computing problem and apply principles of computing and other relevant disciplines to identify solutions.
- Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline.
- Communicate effectively in a variety of professional contexts.
- Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
- Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
- Apply appropriate AI theories, models, techniques, and tools throughout the AI lifecycle to design, implement, and evaluate solutions that meet stakeholders’ needs.