OPIM 5604 Predictive Modeling
Course Title: OPIM 5604 Predictive Modeling
Type: Required course
Term/Time: Spring 2017 / Mondays 6:00 – 9:00pm
Instructor: Iva Stricevic
Teaching Assistant: No TA
Overall Rating: 1 out of 5 stars
Knowledge/Skills Gained: Teamwork, JMP, Pattern/Cluster Discovery, Performance Evaluation, Regressions (Single/ Multiple/ Stepwise/ Logistic), Neural Nets etc.
Summary: I do NOT recommend this professor at all. Find other professors, such as Shun-Yang Lee (see his OPIM profile) for this required predictive modeling subject.
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To be honest, if there was no time conflict in my spring class schedule, I wouldn't have taken this predictive modeling class taught by Iva Stricevic. She's a nice person. However, she's not a good instructor for this subject. I passed this course thanks to my previous sound knowledge in Statistics, JMP, and my thesis research, which I gained from my previous nutrition master's degree at University of Kentucky. I also greatly appreciated my teammates for this course's group project.
When I took this course, JMP Pro version 12 was used. You may have an advanced version when you take this class in the future. Iva has been using JMP a lot for her daily work (She works at The Hartford now). Therefore, she's familiar with this tool enough to teach us. Unfortunately, she has no solid knowledge in Statistics. For instance, she pronounces "chi-square" as chee-square (if you did take any right statistical subject before, you should know how chi-square is pronounced).
At least she knows how to interpret p-value, R-square, and adjusted R-square, as well as under what circumstances you should use which regression or clustering. ...Basically these are all what she knows. When I was in this class, it happened very often that Iva didn't know answers to students' questions. It was nice she would look for answers and got it back to us, but we could simply Google answers by ourselves to save us time. Therefore, I would recommend that if you have any question, instead of asking Iva, it's be better if you seek help from your classmates or teammates who have strong knowledge or understanding in this subject.
The group project was a fun part for me (take a look at our team project to gain an overall sense for this class). Thankfully that Iva broke down the entire project into small pieces, so students could complete the project step by step after we learned something from each week's topic. It took a lot of time to find an appropriate dataset for this class. It also took plenty of time to clean the data. Hence, I recommend start to look for datasets as soon as you form a group for this project. It happened sometimes that several teams would use the same dataset. Nonetheless, it was fun and educational to see how these teams solved the problem in completely different approach.
If you already have solid knowledge in JMP and statistics like me, taking Iva's predictive modeling would be okay. In contrast, if you desire to develop a sound foundation in the predictive modeling, I definitely suggest you find other professors, such as Shun-Yang Lee. He is highly recommended by many of my friends.
Type: Required course
Term/Time: Spring 2017 / Mondays 6:00 – 9:00pm
Instructor: Iva Stricevic
Teaching Assistant: No TA
Overall Rating: 1 out of 5 stars
Knowledge/Skills Gained: Teamwork, JMP, Pattern/Cluster Discovery, Performance Evaluation, Regressions (Single/ Multiple/ Stepwise/ Logistic), Neural Nets etc.
Summary: I do NOT recommend this professor at all. Find other professors, such as Shun-Yang Lee (see his OPIM profile) for this required predictive modeling subject.
========================================================================
To be honest, if there was no time conflict in my spring class schedule, I wouldn't have taken this predictive modeling class taught by Iva Stricevic. She's a nice person. However, she's not a good instructor for this subject. I passed this course thanks to my previous sound knowledge in Statistics, JMP, and my thesis research, which I gained from my previous nutrition master's degree at University of Kentucky. I also greatly appreciated my teammates for this course's group project.
When I took this course, JMP Pro version 12 was used. You may have an advanced version when you take this class in the future. Iva has been using JMP a lot for her daily work (She works at The Hartford now). Therefore, she's familiar with this tool enough to teach us. Unfortunately, she has no solid knowledge in Statistics. For instance, she pronounces "chi-square" as chee-square (if you did take any right statistical subject before, you should know how chi-square is pronounced).
At least she knows how to interpret p-value, R-square, and adjusted R-square, as well as under what circumstances you should use which regression or clustering. ...Basically these are all what she knows. When I was in this class, it happened very often that Iva didn't know answers to students' questions. It was nice she would look for answers and got it back to us, but we could simply Google answers by ourselves to save us time. Therefore, I would recommend that if you have any question, instead of asking Iva, it's be better if you seek help from your classmates or teammates who have strong knowledge or understanding in this subject.
The group project was a fun part for me (take a look at our team project to gain an overall sense for this class). Thankfully that Iva broke down the entire project into small pieces, so students could complete the project step by step after we learned something from each week's topic. It took a lot of time to find an appropriate dataset for this class. It also took plenty of time to clean the data. Hence, I recommend start to look for datasets as soon as you form a group for this project. It happened sometimes that several teams would use the same dataset. Nonetheless, it was fun and educational to see how these teams solved the problem in completely different approach.
If you already have solid knowledge in JMP and statistics like me, taking Iva's predictive modeling would be okay. In contrast, if you desire to develop a sound foundation in the predictive modeling, I definitely suggest you find other professors, such as Shun-Yang Lee. He is highly recommended by many of my friends.
I can't agree more. I took the same class and it was the most terrible experience for me as a student in the States. Iva's teaching sucks. Apparently, she doesn't know how to teach but can only read slides and demonstrate how to use the software. More tragically, Iva doesn't know the stuff she's supposed to teach. In terms of statistics, she lacks the basic knowledge as a teacher and as a data analyst. I know she has been a professional in a famous insurance company, but based on what her teaching indicates, she might not be that qualified for her current job.
ReplyDeleteIn terms of the software, this course uses JMP which Iva uses in her daily work. Of course she can use it to do some analysis and get some results, and build some models. But if we want to learn the tool, we can learn it by ourselves. It can be more effective.
Predictive modeling is a required course for all other data analytics courses in this program. Why is it so important? Because students need to master the basics so that they can move to the next level. I agree with this article that you can take Iva's class if all others have been taken. Don't expect to learn much about statistics and analytics because Iva herself doesn't know much. If you are a student without basic statistics knowledge, you will suffer a lot as you will find it will be difficult to understand how data analytics works. On the top of that, other teachers like Jose can use this course to walk you through the basic elements of data analytics.