INTA-6450 - Data Analytics & Security
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Reviews
You’ll learn a little from this course if you’re new to the area. You’ll get an opportunity to learn a little R or Python, but there is no deep dive into anything. There are regular graded discussions which may take 30 minutes to think through the question and provide your thoughts on it. No exams, only weekly quizes on the lectures. There is a group project. If you get a good group (I did) then it should be pretty easy. If you don’t, I think its completely possible to do on your own if you have a bad group, you have some analytics programming experience and capable of writing a detailed paper. Makes a good class to pair with a harder one.
I am in OMSCS and I took this course my last semester along with GA. When this class was first added to the list of available courses, I thought “oh this sounds interesting”, but by the time I actually registered, I knew exactly what I was doing…I needed an easy class to pair with GA. I almost didn’t take this, as it required a group project, but luckily I got a good group and we only needed to schedule meetings the last month or so of the class. And my groupmates were great! As this was my last semester, I didn’t learn anything new, but modules open up enough in advance that you can work ahead if desired. The group project was totally open ended so there is potential to make it interesting, but we went for straight forward and easy. Professor is great and really involved, so if you take the initiative, you can learn from and interact with him a lot (so I hear), which is unusual for OMSCS. But after taking this class, I totally understand why we are only allowed 2 non-CS classes to count for the CS degree!
This was a very easy class. I had it paired with AIES and didn’t even need to put any effort except for the ENRON final project.
The class discussions were easy write ups. The quizzes were easy Ctrl + F from the lecture materials. The coding assignments were pretty easy, just changing some parameters and inputs to demonstrate the understanding of the code. I wish the lectures had done a better job of explaining the regression models. This was never explained in detail, but it appeared to be significant in data analysis.
The TAs and professor held weekly office hours which was very helpful in getting the direction while working on the ENRON project. This semester there was a new project introduced for extra credit. I didn’t need to do that because i was easily sitting in 90+ range.
This class was OK. No disrespect to the professor but the lectures need to be reworked. They are all over the place and make no sense sometimes. The project is also ok, but watch out for students who have no coding experience in your team as there seem to be alot here.
Class overall was light and is good to pair with another higher workload class. It consists of weekly lectures, quizzes, and sometimes simple programming assignments (R / Python). The crux of the class was the final project, which has you conduct an investigation on a large email corpus. This final project is a group project, and your experience may heavily vary depending on who you group up with. The grading of your project deliverables in this class highly depends on your TA, and is a total hit or miss - I’ve observed a few that were extremely low quality and I question how they got hired in the first place, and this is what ultimately swayed my rating of this class.
All that said, I recommend taking this class if you need a lighter workload semester. For purely educational value, the material felt superficial, and I suggest looking elsewhere if you’re seeking a class that is more technically deep.
I actually liked this class and the lectures. The professor was great and the pace of the class is reasonable. I learned a lot and it is rare for the prof to be involved.
TAs did a decent job; however, It does depend on the TA you get though, i wish there was a way to reduce TA bias and that TAs should be aware of their grading. Other than that keep it up
I’m an OMSCS student (for context). I’m about to finish this course and the best way I can sum it up is that I’m not really sure what this course focuses on as its main element and what I’ve learned. It touches on a lot of data related topics but doesn’t go into much detail on any of them. I took it as a second course this semester, but wish I had taken Digital Marketing or another non-CS course. It’s easy to get a good grade, but a waste of the tuition money tbh.
Pros:
- Jeff (the professor) is great. He’s involved on Piazza, runs office hours regularly and is very active.
- I have never looked at R before so this course provided me with a (very) light introduction
- The team project - while easy - could be tackled in a number of different ways. You could try out some cool stuff around NLP and suchlike there. Also you could do it by yourself if you had to.
Cons:
- Course quiz’s and assignments are very easy for individuals with basic programming skills
- The course did not go into much detail on anything - I didn’t really learn anything
- The security element is very small IMO, please don’t take this if you want to dive deep into infosec side of data analytics
- My team for the team project was great, but as always it’s who you end up with
Horseshit class full of only lazy trash students who look for the easiest way out of everything - myself included.
Easy course but lots of pointless busy work and your grades largely depend on what TA you get assigned. You learn a little bit about some interesting topics but the lecture quality is pretty low
The course was pretty easy. The professor was awesome! He was very active in the discussion boards, and he really knows his stuff. He was available every week for live office hours. I don’t know any professor in the OMSCS program who commits that sort of time. The only downside is that there’s a bit of luck on who grades your assignments. The proposal was a huge part of the grade. After the TA graded my proposal, it took me down to 91-92%, and therefore pretty much meant I had to get an A on the final project to get an A in the course. The quizzes are pretty easy. There’s only one trick question per quiz, so you’ll end up either getting a 100 on the quiz or just one wrong. Everything else is Ctrl-F from the PowerPoints. There is a wealth of information presented in the course, and the content will be a very good reference for practitioners. I’m kind of disappointed that many here gave ‘Strongly dislike’, y’all shouldn’t rate the course based on the unfair grading from the TA’s. Btw, completed the course with an A.
The quizzes and discussions are straightforward and easy to get full points. The R and Python exercises had no defined deliverable outside of “make changes and document what you did” so the grading for those, and the project papers, seemed arbitrary despite being generous. While I’m pretty sure I’ll end up with an A, the class just made me feel a bit uneasy all semester because I never felt like I understood what they were expecting as the rubrics were vague to the point of uselessness. The example given for the final paper, which was written by someone who really, really got into it, he said it would get about a 95 which made me laugh a bit because I know my group didn’t have that same passion about it.
Between the first paper and the final paper (they tie together) there was a great deal of granular data analytics that felt like it could have been left at a higher level with the same end result.
The professor was passionate about the topics and the material itself was interesting. I wouldn’t have taken it if there were other offerings but I don’t regret it. Made for a relatively stress-free summer.
Low quality, non-technical course. Most of the assignments are busywork. Quizzes are just an exercise in looking through slides for the answer - they don’t help you learn anything. Expect to get ~1 question wrong per quiz because of 1-2 trick questions that aren’t clearly answered by slides or lectures (basically for artificial difficulty). Terrible design. Not even worth the hassle of trying to ask for points back. Discussions are so trivial to your grade, you might as well do none of them because you can still easily get an A. R / Python exercises had very vague and unclear instructions, and the professor had us change the format of our submissions literally a day before the deadline.
My TA grader has graded my papers and discussions arbitrarily - had points deducted just because the TA felt like it I guess. No clear explanation provided as her comments felt like nitpicking for sake of nitpicking. I felt I put forth honest efforts in all of these assignments. Note that these discussions are worth 0.25% of your overall grade each, so they are completely trivial. Either way, I welcome the deductions because they’re worth the comedic value - hilarious to think that this TA wastes that much time with these nits for 15 bucks an hour. Great job! In other courses with discussion / essay components, I’ve never lost points due to this sort of nonsense.
Group project is shaping up to be a pain (hint: it’s just more busywork in the form of a 10 - 30 page group paper and a presentation). If you want an easy course where you’ll actually learn something, try digital marketing. No problem with the graders there and no pointless group project.
This was a weird class, especially as something that’s considered an elective for the OMS cybersecurity program. The class has the word “security” in it, but it has nothing to do with cybersecurity. I took this class because I didn’t really have other options due to the severely limited elective offerings in the policy track.
The class touches on data science topics but never actually teaches you them, nor does it expect you to actually learn or apply them.
Half of your grade is based on discussions and open book quizzes that you can get 100% on using CTRL + F. The other half of your grade is based on a group project, so your experience and grade will vary on your group.
My group was a major pain in the ass, so that negatively impacted my experience in the class. I also feel like I didn’t really learn anything.
I paired this with another class and it was an easy A, so at least that’s something.
This class is very straightforward. Quizzes are straight from the slides, and the assignments are mainly just about putting in the effort. There are a few R exercises which just require altering some provided code and writing a short summary of your changes. Discussions are also mainly effort based.
The main deliverable in this class is a group project which involves a paper and presentation. Overall, it’s pretty simple and grading is lenient. This is a great class to double up with another class.
The course was very easy. Quizzes are straight from the slide. The assignments are straightforward and you get good marks even if you run the assignments and share the output. To get full marks, you have to make some changes (which could be any) and explain them. Project is simple, you just require a good team to work. Professor is nice and holds regular office hours and so does the TAs.
You may not end up learning much, but it’s a good course to double up with another difficult course.
Its a good course and workload is on the lighter side.
Lectures are great, instructor is amazing and very supportive. Discussion are good and keep you interested in the content. There are also python and R exercises for you start learning it and not very complex.
There is an individual paper and a group project which takes majority of the time in the course. If you get a decent group and work at a good pace you should sail smooth in the whole course. Group project is in the second half of the semester.
Watching lectures and participating in discussions should take 2-3 hours per week. Group project took more time for me though hence I have put higher time than rest of other reviews.
Overall recommended.
It’s a pretty easy class. Everything is graded fairly easy and should be an easy A. The quizzes are straight from the slides and it should be maybe 30 minutes to an hour on the weekly lecture assignments. The project can take a bit of time later on, but if you have a good group, then it will work out very well.
This is a very easy class that would be good to pair with a more difficult one. Overall, I spent about 2-3 hours every other week on it.
The lectures are generally released on a weekly basis and you have a week or two to complete the homework. Every lecture module comes with an open note quiz. The quiz questions are taken directly from the slides, and honestly you could just use ctrl + f instead of watching the lectures all together. There are a total of 12 discussion posts which are fairly light and usually ask your opinion or understanding of a certain subject. Honestly I found this to be be the most challenging part of the class - I’m a programmer, I’m not used to writing about my opinions and feelings! There are also 5 mini programming assignments (1 in python and 4 in R). Calling them assignments is kind of a stretch. As long as you can run the code successfully and make minor changes to it (I’m talking real minor - liking changing parameter values kind of minor) then you’ll do fine. The class is offered to students from the cybersecurity program and because some of them have no programming experience they really hold your hand through all the programming required in the class. The major deliverable for this class is the course project. The project is fairly straightforward and is done in groups. The best part of the class is that there is no tests to study for!
I’m not sure I’m learning that much from the class though. The lectures give a super high level overview of big data and data analytics, and I doubt I would be able to understand it all without taking previous classes on the subject. However, the TAs and office hours are super helpful if there’s a topic you don’t understand. Also, if you don’t understand something and are too lazy to do anything about it, that’s cool too. The quizzes are open notes and the coding assignments and course project have very little to do with the details of the lectures. The course is really what you make of it. If your taking two classes and your goal is to put in the minimal amount of effort required to get an A, that’s okay but you might walk away without learning that much.
Overall the class is great if your looking for a light course load. Having previous experience with python and R is a plus, but you could definitely come in knowing nothing about computers or statistics and you’ll do just fine.
Good luck!
Overall, the class was very easy. There weren’t a ton of projects and the grading was very lenient. As long as you attempt the work, then you will likely get an A on the assignment.
The content is essentially just an overview of various analytical methods and tools. You don’t dive into the tools or techniques much or even have to implement them on your own. I really hoped that there was more content directly related to data analytics for security, but this was an easy A.
This class is the easiest class on the OMS Cyber - Policy track. The grading is also leniently done. Easy A