Major:
MS in Artificial Intelligence - Data Analytics
AIML-505 Large Language Models and Generative Artificial Intelligence
Instructor:
Dr. Mary Lind
Delivery:
onsite
9
/10
Class was pretty good, but please do not expect like any hard technical stuff. It's mostly like theoretical. The class was mostly talking about machine learning models. When it was time for residency, we were tasked to create an AI agent. That was pretty fun, but most of the time the class taught you theory and not coding stuff.
09/28/2026
10
/10
Major:
Doctorate in Business Administration (DBA) – Information Systems Specialization
BADM-701 Residency 1: The DBA Journey
Instructor:
Marian Carpenter
Delivery:
onsite
10
/10
The quality of class is good the workload was normal and maintaining good discipline and attendance requirements Good and Professor teaching is good communication is very good and great evaluation.
09/25/2026
10
/10
Major:
Master’s in Data Analytics
DTAN-745 Advanced Application of Data Analytics
Instructor:
Jody Ferrell
Delivery:
online
10
/10
very good teacher who gives interesting assignments with generous grading, a good course to take
09/23/2026
10
/10
Major:
MBA in Information Technology Management
FINC-510 Financial Reporting and Analysis
Instructor:
Carlos Slaughter
Delivery:
online
10
/10
Dr. Slaught is a very nice and understanding professor. His class is pretty easy, and I would say it is an easy A as long as you complete the assignments on time. Every week, he offers an optional online meeting, so you can join if you have questions or want extra guidance.
I also had his class during residency, and the overall experience was very relaxed and enjoyable. The workload is manageable, and nothing is overly difficult or stressful. At the end of the course, there is a group presentation, but it is also very manageable.
Overall, I would definitely recommend taking Dr. Slaught’s class if you are looking for a supportive professor and a relatively easy course.
09/15/2026
10
/10
Major:
MS in Artificial Intelligence - Data Analytics
AIML-501 Model Development
Instructor:
Chris Walker
Delivery:
onsite
10
/10
AIML-501 Model Development has been a very valuable and well-structured course in the MS in Artificial Intelligence – Data Analytics program. Professor Chris Walker has done an excellent job presenting the course material in a clear, organized, and practical manner. The class has helped strengthen my understanding of model development, evaluation, and the overall process of building effective artificial intelligence and machine learning solutions.
Professor Walker’s teaching style is engaging and supportive. He explains technical concepts clearly and connects them with practical applications, which makes the material easier to understand. He is approachable when students have questions and encourages participation and critical thinking throughout the course. His explanations help students understand not only how models are developed, but also why certain approaches, techniques, and evaluation methods are used.
The homework load has been manageable and appropriately balanced with the course content. Assignments reinforce the topics discussed in class and provide useful opportunities to apply the concepts in practical situations. The workload requires consistent effort but is reasonable for a graduate-level course. Instructions and expectations have generally been clear, making it easier to organize and complete assignments on time.
Classroom discipline and the overall learning environment have been professional and respectful. The course is organized in a way that encourages students to stay engaged and participate. Attendance expectations are clear and reasonable, and students understand the importance of being present and actively involved in the course.
Overall, I have had a very positive experience in AIML-501. Professor Walker is knowledgeable, professional, and effective in communicating technical material. The course provides a strong foundation in model development and is highly relevant for students pursuing careers in artificial intelligence, machine learning, and data analytics. I would highly recommend this course and Professor Walker to other students in the program.
09/02/2026
10
/10
Major:
M.S. Computer Information Systems - Artificial Intelligence
DTAN-500 Foundations of Data Analytics
Instructor:
McCoy,Robert
Delivery:
onsite
10
/10
Professor Robert McCoy is a great instructor who conducts classes twice a week—one general class session and one discussion session, both of which are optional. His assignments in Data Analytics are very practical and helpful. I especially enjoyed the assignments focused on data cleaning and creating meaningful insights from Kaggle datasets, as they provided valuable hands-on experience with real-world data. Overall, his course is well organized and provides a good balance of learning and practical application.
09/02/2026
10
/10
Major:
Master’s in Data Analytics
DTAN-745 Advanced Application of Data Analytics
Instructor:
Jody Ferrell
Delivery:
online
10
/10
Good professor. Very engaging coursework.
08/31/2026
10
/10
Major:
M.S. Computer Information Systems - Artificial Intelligence
AIML-500 Machine Learning Fundamentals
Instructor:
Asabe Dawudu
Delivery:
onsite
10
/10
Professor Asabe Dawudu is a friendly and supportive instructor. Her assignments are practical and useful, especially the portfolio creation project, which helped me apply what I learned in a meaningful way. I really enjoyed the course and appreciated her teaching approach.
08/31/2026
9
/10
Major:
MS in Artificial Intelligence - Data Analytics
AIML-500 Machine Learning Fundamentals
Instructor:
Nigel Basta
Delivery:
onsite
9
/10
This course did a great job blending technical AI/ML fundamentals with practical leadership application, the mix of discussions, hands-on chatbot coaching sessions, and portfolio. The workload was substantial, but the variety of formats (case studies, quizzes, peer review, reflective writing) kept it engaging rather than repetitive.
08/20/2026
8
/10
Major:
M.S. Computer Information Systems - Artificial Intelligence
AIML-505 Large Language Models and Generative Artificial Intelligence
Instructor:
Dr. Mary Lind
Delivery:
onsite
8
/10
The class was good; all the coursework was still manageable. The onsite class was spent just creating one big project and presenting it in class. She is usually giving high grades. No online meeting ever held, only onsite. This class teaches you the concept of LLM but doesn't go to deep into coding an LLM like RAG or creating an AI agent from scratch, mostly theory
