Artificial Intelligence and Cloud Computing - Associate of Applied Science Degree (AAS)
-thumb.png)
Degree Quick Facts
- Instructional School: Science, Technology, and Math
- Department: Computer Science
- Program Code: AICC.AAS
- Program Type: Career and Technical Education
- Available Fully Online: No
- Eligible for Federal Financial Aid: Yes
NOTE: Courses required for this program may have an additional fee; more information can be found on the Special Course Fees web page.
Degree Requirements
| Course | Course Title | Min Credits |
|---|---|---|
| General Education Requirements | ||
| GEM 1 - Written Communication course | 3 | |
| GEM 2 - Oral Communication course | 3 | |
| MATH 143 | Precalculus I: Algebra (GEM 3) 1 | 3 |
| SCIE 102 | Ethics in Science (GEM 6) | 3 |
| MATH 153 | Statistical Reasoning (GE Elective) | 3 |
| Major Requirements | ||
| AICC 110 | Introduction to Artificial Intelligence | 4 |
| AICC 120 | Introduction to Python Programming and the Cloud | 4 |
| AICC 130 | Linux for Artificial Intelligence and Cloud Computing | 4 |
| AICC 150 | Python for Artificial Intelligence | 4 |
| AICC 160 | Math for Artificial Intelligence | 4 |
| AICC 170 | Database, Data Mining, and Big Data | 4 |
| AICC 210 | Machine Learning | 4 |
| AICC 220 | Artificial Intelligence for Business | 4 |
| AICC 230 | Artificial Intelligence and Cloud Computing | 4 |
| AICC 250 | Computer Vision | 4 |
| AICC 260 | Natural Language Processing | 4 |
| AICC 270 | Artificial Intelligence for Cybersecurity and the SOC | 4 |
| Minimum Credit Hours Required | 63 | |
- 1
Students who do not score high enough on the CWI Math Diagnostic exam to place directly into MATH 143 Precalculus I: Algebra have the option of completing MATH 142 Precalculus I: Algebra Plus and MATH 143P Precalculus I: Algebra instead. While this option adds an additional two credits, it will reduce the overall time to degree completion.
Degree Plan
The course sequence listed below is strongly recommended in order to complete your program requirements. Many Career and Technical Education (CTE) courses have prerequisites and/or corequisites that have been accounted for within this course sequence plan. Please register for each semester as shown using the Student Planning tool in myCWI. Consult your advisor for any questions regarding this course sequence plan.
| First Year | ||
|---|---|---|
| Fall | Credit Hours | |
| AICC 110 | Introduction to Artificial Intelligence | 4 |
| AICC 120 | Introduction to Python Programming and the Cloud | 4 |
| AICC 130 | Linux for Artificial Intelligence and Cloud Computing | 4 |
| MATH 153 | Statistical Reasoning (GE Elective) | 3 |
| GEM 1 - Written Communication course | 3 | |
| Total Semester Credit Hours | 18 | |
| Spring | ||
| AICC 150 | Python for Artificial Intelligence | 4 |
| AICC 160 | Math for Artificial Intelligence | 4 |
| AICC 170 | Database, Data Mining, and Big Data | 4 |
| MATH 143 | Precalculus I: Algebra (GEM 3) 1 | 3 |
| Total Semester Credit Hours | 15 | |
| Second Year | ||
| Fall | ||
| AICC 210 | Machine Learning | 4 |
| AICC 220 | Artificial Intelligence for Business | 4 |
| AICC 230 | Artificial Intelligence and Cloud Computing | 4 |
| GEM 2 - Oral Communication course | 3 | |
| Total Semester Credit Hours | 15 | |
| Spring | ||
| AICC 250 | Computer Vision | 4 |
| AICC 260 | Natural Language Processing | 4 |
| AICC 270 | Artificial Intelligence for Cybersecurity and the SOC | 4 |
| SCIE 102 | Ethics in Science (GEM 6) | 3 |
| Total Semester Credit Hours | 15 | |
| Minimum Credit Hours Required | 63 | |
- 1
Students who do not score high enough on the CWI Math Diagnostic exam to place directly into MATH 143 Precalculus I: Algebra have the option of completing MATH 142 Precalculus I: Algebra Plus and MATH 143P Precalculus I: Algebra instead. While this option adds an additional two credits, it will reduce the overall time to degree completion.
Program Learning Outcomes
Upon successful completion of this program, students will be able to:
- Recommend ethical methods of implementing and employing Artificial Intelligence (AI) in cloud, business, and cybersecurity environments.
- Utilize AI-driven tools and industry-standard methods to generate actionable information from large data sets.
- Properly apply statistical analysis to guide Machine Learning (ML).
- Plan effective applications of AI to real business problems.
- Plan effective applications of AI to real cybersecurity problems.
- Integrate AI tools and concepts with cloud computing domains.