DSO 522 - Applied Time Series Analysis for Forecasting

This topic can also be covered lightly, in DSO 510, the required elective for the Business Analytics certificate, and in DSO 529, Advanced Regression. The biggest challenge was how Professor organizes Blackboard, and her approachability in general. While available most times, it felt hard to actually approach for out of class questions etc. I also got the vibe that she is more of an academic than an instructor. For example, the recommended text is a book that covers time series for electrical signals: not quite business school. Labs are done in a peculiar fashion in class, with guidance (if you can ask), and due in the evening. Overall, the assignments cadence (and subject matter) are both demanding, but the class is doable. You do have to keep with submissions and self-study. You can take a hit to your GPA if you do bad on some assignments, and/or because the MSBA kids pull the GPA to the higher end. Analysing time series is still a valuable ability, many real life datasets tend to be time series. This course was in R. Beware of the proliferation of tools as one takes many DSO classes (R/Python on Colab/Python on your local machine/JMP/Radiant/Frontline Solver/Excel... etc). The MSBA kids go HARD.

The course has many real world applications, the professor sometimes struggles to explain the application of the code; however, the very hands on ability to code in R is extremely useful in learning the concepts.

Awesome class; however, the professor get's into the weeds fairly often. Don't worry about becoming an expert on the terminology, he grades you based on your execution of your forecasts and your ability to actually do work. I would recommend he get's rid of the final, as it is impossible to finish...but his class was graded extremely fair. Don't freak out in your first three classes, gabrys does a good job making the assignments walk you through the material and get a good grasp of things.

Course material was very useful. Gabrys wasn't the best at lecturing, but if you are going into a Finance or Marketing career, I would highly recommend taking this course to learn several applicable Excel Forecasting methods, as well as learning a little bit of R

The class material is challenging enough, but the professor does not have organized syllabus with due dates or lecture schedule. Also, his pacing of the class is slow in the early lectures but gets extremely rushed towards the end as he is behind. This lack of consistency in pacing results in having heavy homework and group project due back to back. The course material is useful to learn multiple theories on different regression methodologies.

Abbas is a cool professor. He is friendly and even shy. The class is all about R. But we didn't learn R per se. We learned very basic forecasting in R. There were three HW assignments. Each took me a day to complete. It's a good 1.5-unit class to give you a basic knowledge of R.

The topics learned on this class were very helpful and would have helped me greatly during my internship project. It's really relevant and provides an easy-to-apply framework for real-work situations. The downside is that given that it was the first time this course was offered as 1.5 credits the content was condensed. I would recommend taking the full course in order to expand on this subject because of its relevance.

One of the best analytics classes at Marshall. Gabrys is much more in his element here, so his teachings stick significantly better than GSBA 524. Covers times series decomposition, ANOVA, etc...all great stuff that builds significantly on Market Demand/Sales Forecasting. If you're interested in analytics, this is a must. I'd recommend taking DSO 530 beforehand to learn R as well.

The subject matter of this course is extremely interesting and useful in many ways. However, it was taught in a way that made it too confusing and tried to cram too much into half a semester. The midterm and final were basically the same test since he wasn't able to cover any new material between tests. And both exams were way longer than we had time allotted, which resulted in them being half take-home test. I very much recommend the class material, but not in this format taught by Gabrys.

Technical course that teaches how to use R

The discipline is really important and practical for data analytics. However, although the professor intend to teach us well, the way he taught is really need to be improved. The materials and the structure of this elective is really hard to follow, and the way he went to cases is also hard to understand.