great

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The course was very informational. A lot of the concepts were new but very practical, as much as were the typical theories we deal with everyday in our corporate lives.

As much as I appreciate the course content, I had expected more metrics to be discussed, more maths, more problem solving, a session on a set of metrics, formulae, some business cases as a part of evaluation would have been more realistic. I deal with lot of analytics and numbers always. I do a set number of things. I was expecting the professors to guide us on more number crunching techniques with say, an excel of data of say 1000 employees. How do we play around with such data - which is what I do. And a thorough insight on such would have been amazing.

I hope my feedback is taken into consideration in a positive light. I loved your sessions, and would love to join in the future again, and it would be really helpful if you could guide us in some of the ways I tried to explain.

Thank once again.

Best

angana

Pretty good. Cade's analysis of the NFL draft is the highlight of the course and one of my favorite videos in the entire Wharton BA series. Overall the course gets kind of depressing towards the end as you realize how noisy this data is and how tough it is to get access to.

Martine's network analysis module is pretty cool. It would not have been overload to work in some of the calculations of network metrics, though, and they would have made for better quiz items. I'll have to be honest, though. I'm not very hopeful about ever being able to use this kind of analysis in the workspace.

Matthew's module was ok but I thought could have used more hard examples. Maybe some research from law enforcement or some field with lots of pre-tests could be used to illustrate regression and some of those techniques.

It was great learning from such experienced mentors and they got us very deep insights of research. however there were some grey lines as per me, methodologies, and actual working was expected from my side and practical application. Secondly, the language issue, as they were very clear about the language but the frequency and the level they were talking was a bit difficult to catch but watching it twice or thrice can help, that's not much of an issue. well apart from the issues that i have mentioned i more of a positive perspective towards this course, making the concept clear was the brightest side of the course and recommend even others to pursue this course and additional linking course that will be a great help in the analytical world.

Very nice foundation level course. Based on many courses I have taken so far, I have high expectations from the ones offered by Wharton (Univ of Pennsylvania), this one met the expectations. Good content at even at introductory level. At least for weeks 1 to 3. Week 4 was a bit weak, not much substance, can use some modifications for making it better. Thanks to professors for sharing their knowledge and all the people involved in producing it. Some quiz questions weren't good (not clear from Q as well as A perspectives), and I wish the course had more interactions with professors, other students and community TAs. And, of course, a free "Statement of Accomplishment" would have been awesome. In any case, overall good course, worth taking.

Module 1 was particularly difficult to understand because it involved a lot of statistics.Whereas the other modules were relatively easier to grasp.Also some of the examples given were in American context it is difficult for non Americans to understand the examples such as NFL, Baseball etc.If the examples were chosen based on the most popular sports (universally played sports) such as football or tennis it would have been more easier to grasp.Also as a precursor to this course, one can introduce the basics of statistics which will help us understand the statistical examples, tools and algorithms that you are covering in the "People Analytics" Course.Overall I liked the course except for the few things mentioned above.