DAS was my second OMSCS course, and I paired it with another relatively medium-difficulty course. I previously worked as a data analyst and already had experience with data analysis, so I honestly did not do much preparation before the semester started, and it turned out that was completely okay.

First of all, I do think the TAs had quite a bit of mismanagement on Canvas during our semester. Although they normally do not release all quizzes and assignments upfront, due to their mismanagement, everything ended up being released around the middle of the term, which was something students had already been asking about since the beginning of the semester. However, one thing I appreciated was that the teaching staff genuinely seemed willing to improve. If you asked questions on Ed Discussion, they usually tried their best to support students. For example, there were assignments where the grading rubric was not initially disclosed, but if someone asked about it on Ed, the TAs would explain the rubric clearly. So while there were definitely management issues, I still felt that the staff cared about improving the student experience.

The lectures themselves were somewhat vague, but the quizzes were generally easy as long as you paid close attention to the lecture details. The discussion posts took longer to write, but they were manageable and nothing too overwhelming.

For the programming portion, there were 4 R assignments and 1 Python assignment. The interesting part is that even though they do not really provide programming lectures, you are still expected to make your own code modification and explain the reasoning behind your change after reviewing their original code. If you are unfamiliar with R or Python, this part can feel difficult because they do not explicitly tell you what to change.

My advice is:

1. Carefully study what the original code is doing
2. Review the dataset and outputs closely
3. Ask yourself a follow-up question such as: “What additional insight would I personally want to know from this data?”
4. Implement a code change that answers that question
5. Clearly explain your reasoning and findings in the write-up

Once I started approaching the assignments that way, the coding portion became much more straightforward.

There were no exams in the course, but there was a project. The first half of the project, which was the proposal, was an individual assignment, while the second half became a group project. My group only had 3 members including myself.

Spoiler alert: sometimes a free loader is honestly easier to deal with than someone who constantly works very hard in the wrong direction.

One teammate was clearly a free loader, but the other teammate was extremely proactive while misunderstanding the project direction most of the time. Ironically, I had more headaches dealing with the latter situation. There were many moments and I did not even want to recall everything, but I ended up doing most of the project work myself.

That said, the project itself was not particularly difficult. The most important thing is understanding the general flow of data analysis:

• understanding the data
• cleaning/preprocessing
• identifying meaningful questions
• performing analysis
• interpreting results
• presenting findings clearly

As long as you are willing to get your hands dirty with the data, you will eventually find a way to analyze it, write the report, and complete the presentation video successfully.

I walked away with an A, and honestly, there were several weeks where I barely touched the course at all. However, during the project periods, the workload definitely became much heavier, especially because of the group project and project paper writing.

Overall, I think DAS is manageable if you already have some experience with data analysis or are comfortable exploring datasets independently. The course does not hand-hold you much, especially for the coding assignments, so being proactive and willing to experiment is important.

For me, this course felt less about memorizing difficult theory and more about developing the mindset of asking meaningful questions from data and figuring out how to support those answers analytically. If you can do that, you will probably do well in the course.

I received an A in the course, however it is an extremely badly organized course by the professor and especially the head TA. The course content is also just basic statistics and an intro to Python and R course.

Assignment and project instructions are extremely vague, rubrics that are given are not the standards that the TAs mark with according to both the professor and the TAs.

According to the head TA Emma Kathryn Shumway, she's been working as a TA for this course for 10 semesters. The course still being this badly organized with the exact same problems that other reviews have discussed years ago shows that the problem is with the professor as well as whoever is leading the TAs (probably the head TA). The head TA also deducts marks for things that she said was acceptable on Ed discussion, and when brought up she refuses to adjust marks accordingly.

When asking private questions on Ed discussion about projects and assignments, myself and multiple other people that I've talked to have been ignored.

The professor, Dr. Borowitz seems nice during office hours, but over the semester I sent him 3 emails regarding assignments or projects and he did not respond to a single email.

Overall I have to say this course is the least organized and the most frustrating course I've taken at Georgia Tech.

I achieved a high A in this class.

Pros: Subject matter and quizzes are straightforward and do not take much time. For half of the semester, you can complete your week's work in about 1-2 hours. The course is heavily weighted toward the final project and paper. If you work on that consistently and early, the course is a breeze. If you have no experience in data analytics, its a great foundational course to get your feet wet.

Cons: Some of the TAs' grading does not demonstrate competence. I spent around 80 hours on the final project alone because I wanted to really blow it out of the water. Those 80 hours do not count my teammates' contributions. And we received a B on our final project because the TA "significantly" did not follow the grading rubric. I found that quite frustrating and un-academic. I professional brought it to the TA's and the Professor's attention, and received no response. Many people complained about the TAs grading on the mid-semester project, and I can see why.

Takeaway, I find that this class is overly weighted toward a complex, many-faceted, final project (30 page paper + 20 minute presentation) that is too complex for TAs to grade correctly.

Join this course if you

• want an easy B or C grade
• Light coursework
• Just care about passing, not really understanding anything

Do not join this course if you

• want a satisfying A
• want to actually learn anything about cybersecurity
• Have a low tolerance for bad TAs

Having said that - here's my experience with this course

1. THIS IS NOT A CYBERSECURITY COURSE - This is a 100% STATISTICS course. Barring maybe a throwaway module on security concepts, the entire course is about statistics. Linear models, regression models, clustering etc and then implementing those in R. Final project is also pure statistics, finding some patterns and trends in data - zero cybersecurity. As someone with no interest or background in statistics this course was entirely awful - and I ended up just focusing on whatever needs to be done for grades. I didn't learn anything relevant or useful that could apply to any real world cybersecurity scenario. As a policy s

2. TA's will ruin this course for you - The assignments are vaguely worded, the rubrics are just as vague and the TA's make random judgement calls with no real recourse. Blanket "no regrades" are issued by TAs and the professor is hands-off, blaming students' grades on "low effort" (his words, in an actual Ed post). No reflection whatsoever that an entire class of 100+ students got bad grades and were complaining daily about TA's. Instead he blamed it on low effort. Students lost 5 to 10 points because TAs thought the paper had too many bullet points, or they didn't agree on where periods should be used, or they don't agree with the grammar structure or format of the write-ups etc.

3. Group project is a luck of the draw - you're paired against randoms for the group project. I had an awful experience with one person who literally did nothing (not even one word contributed to the final reports). The other one refused to hear any input and made the "group" project his personal project.

This is my fifth OMSCS course. I chose it as an easy summer class, and it is easy—the curve means almost 90% people gets an A?—but I wouldn’t recommend it. The material is shallow and the coding assignments feel random; I’d rather solve a clear problem than explore without a goal. As others have noted, it’s basically Python/R 101. The grading rubric is vague: I took an unexpectedly low score on the first part of the final assignment, which dropped my grade from 99 to the mid-80s. I eventually earned an A by writing the final paper in a way more academic style—something never made explicit—but the whole thing felt like guesswork compared with my other courses. Even as a light companion to a tougher class, I’d skip it for your sanity.

Finished the course with an A, achieving a 88.81% (A: 86% and above, B: 76% - 85.9%, C: 66% - 75.9%)

Background: Bachelor's degree in Computer Science from a university ranked #377 out of 436 National Universities in U.S. News English is my second language (TOEFL score: 95/120) 1 year of experience as a full-stack developer and 6 months of experience in data analytics

Overall: This is the sixth class I’ve taken in the OMSCS program, and honestly, it’s been the most frustrating one so far. The course content is disappointing. I don’t even know how to describe it. I signed up for “Data Analytics & Security” hoping to learn the basics of data analysis, how to make data more secure, and how to write solid analytical reports. None of that was covered in the course. I took the ML course in OMSCS, and this class title should be changed to "Intro to R, Python, and ML algorithms" to avoid misunderstandings about the class content.

The assignment instructions are vague and hard to follow. You have to read them multiple times to figure out what’s being asked. It feels like the focus is more on guessing what the instructors want than actually learning anything meaningful. They try to frame the assignments as “open-ended,” but the grading doesn’t reflect that at all, so you’re left completely unsure of how you’re doing or what you’re supposed to be getting out of it.

The TAs in this class honestly have no idea what they’re doing. They respond very slowly and often can’t answer students’ questions. You’re better off searching Google or Reddit than relying on them. The TA group seriously needs to be replaced. If you're too busy with your personal life, then don't apply for a TA position and use "I'm busy" as an excuse.

Lecture Activities (28.78 / 30%): This assignment combines a quiz and a discussion, but don’t be misled by the title. It should be called "homework." The quiz part is easy, but the discussion can be tricky. Some prompts require you to provide actual examples, even though that’s not clearly stated in the instructions. That’s frustrating. You can see the impact in the score breakdown; discussions with these hidden expectations tend to average 80% or lower, compared to those with clearer requirements.

Computing Activities (18.2 / 20%): This coding assignment is worse than anything I did in high school AP Computer Science. It asks students to “explore” and modify code without clear direction or explanation of what’s expected. Many of us ended up confused, and when our exploration didn’t match the TAs’ expectations, we lost points. It’s hard to believe this is a master level class. If the assignment is open-ended, grading should be based on what students submit, not on a hidden rubric. This is also the first time I have submitted a coding assignment as a PDF since high school. Back then, we even submitted .cpp files when GitHub wasn’t popular yet, so this feels very ridiculous. You also have to make sure the margins of the PDF layout fit properly on the page, including the parts from the original layout provided by the TA. If not, they will deduct points for that too.

Project Activities (41.83 / 50%): This section is the worst part of the course, and it counts for up to 50% of the grade. They expect you to write an analysis report, but the course content doesn’t teach you how to do that at all. Fortunately, I had a great teammate who explained what makes a good analysis report and what doesn’t. Otherwise, I wouldn’t have had any idea what I was doing wrong. If your group isn’t clear on the expectations, this part can be extremely frustrating.

If you want to take this class, ask yourself a few questions:

1. Do you mind getting a B?
2. Do you mind not learning anything useful?
3. Would TA going on a power trip drive you crazy?

I took over 15 courses in OMS program. This is the worst course I have ever taken. The material is outdated and is totally useless for data analytics or security. It's a shame that this is a graduate level course. I can most likely teach my 8 years old to get a B in this course.

Adding insult to injury is TA has to randomly taking off points and not follow Rubric on grading. It's almost seem like they are worried about too many people getting A.

They need to CURVE for all these ridiculously simple assignments. So go figure.

The course allows ChatGPT, so this is how you can spend less than 1 hour to take care of everything

All the discussion? Everyone is just posting random ChatGPT nonsense, so just do the same. All the Python , R Assignments? Totally useless with vague expectations. It's like your first assignment you would expect after you learn Hello World in python 101. But the fun part is TA's grading. They wouldn't tell you what they expect, and they don't follow Rubric anyway. So just dump it in R-Studio, export, and ask Chatgpt to expand your code. All the Quiz? It's open book, ChatGPT can solve 99%, or if you feel like too easy, just search in the provided transcript. The material is useless, so don't waste your time Final Project? Good luck getting a team that would work in the last month. Grading is a total joke, highly depending on the TA. I ended up just doing almost everything and put everyone equally contributed as a I need an A.

Did I get an A? Yes, but I felt this class was more challenging than ML, AI and other difficult classes that I spent 30+ hours/week. My struggle is by the design, this course doesn't evaluate your knowledge. You need luck to get an A.

Stay away. Dated materials, slow to respond TAs, Honorlock - all of the negatives that appears in various GA Tech courses, nothing to balance it out. Group project too - YMMV on those.

Seriously, stay away from this course. As someone who has a very busy life, I was excited to take this class alongside another class to hopefully not have a terrible workload and enjoy my life a bit.

The good news is that the effort for the beginning portion of the class was relatively light. The bad news is that the paper and presentation portion of the class is NOT light and requires quite a bit of effort.

That in itself wouldn't be an issue, but the inconsistencies in grading is what's going to kill you. One T.A. in the ed discussion will say one thing, and your final grade will legitimately say a different thing contradicting it all.

Like others in the course, I received a very low grade for my initial proposal and legitimately received like 5 or 6 comments, with half of them accusing me of using AI. After clarifying I did not use AI (plus if I did... I probably wouldn't have gotten such a low grade), the grader mentioned that this wasn't the reason I received a low grade. So... why did they comment that at all (and consist of half my comments)?

That is just a taste of what you'll get at this class. Everything else is super easy, and if you get lucky and get a great group, you might be able to coast through, but this class requires so much luck on a merciful grader that it's just not worth it.

Shockingly horribly organized. Module 9 is the same time as module 3? They also make announcements to do work and mention projects that we have no access to until weeks after the announcement, obviously causing confusion and stress among students. They tell you to access things that are not accessible, and if you tell them they're not accessible they give sass about "being imprecise exactly as to what we mean", as if they are not the ones organizing the canvas courses and availability dates? They seem to make things as annoying as possible on purpose.

That said, the course material is interesting and easy. It's a good intro to the concepts, and presented well. The actual professor seems like a cool and smart guy, and I like his videos quite a bit. Giving this course a 2/5 as in asynchronous online classes, the organization of a course is EVERYTHING and in today's day and age, there's no excuse for not fixing clear organizational issues immediately. Thanks!

You have about two weeks per section. There are lectures with slideshows included. You can have the slidehow open while answering the quiz questions, which are answered directly in the slides. There are several required discussion posts. Apparently some people used AI to write them, which is ludicrous. Just answer the questions and you'll be basically fine. There is some Python and R. You choose whether you want to write the programs from scratch or start with the program pre-written. You get the same number of points either way so unless you just want to do work, the pre-written code is the way to go.

A weird thing, module 9 is due the same week as module 3. Watch that schedule!

The big bad thing here is the paper. You are meant to do the first paper individually then pick a team for the second paper, both on the same subject - Enron or SecureNow. As with every other group project anywhere, your team makes all the difference. Because of the weight of the paper on your final grade, you definitely want to get yor team together early. I got mine during the first week of class so we were miles ahead. It still took us until a few weeks before the due date to buckle everything up.

The TAs seemed wildly disparate in their scoring. Some of my more detailed discussion answers we scored lower than my mailed-in ones. Unfortunately, we seemed to get harsher TAs on our papers so the 3 point curve the professor gave ended up being handy. Which is wild for the quality of work our group had.

I highly recommend pairing this with another course so you keep busy for the semester.

30% of the class is quizzes and discussion, if you go through the course material this should be easy for you. 20% of the class is coding, you are expected to make an enhancement to a working code (R and Python), they are not too hard, I didnt knew R but picked up on the way, and 50% of class is group project. You have a chance to either pick Enron (Email analysis) or NowSecure(Find Malware from the data). If you choose project Enron(like me) then you will question yourself why this class has Security in its name, it should be replaced with Forensics. You will be put up in a group of 4 and if you are unlucky, you might have hard time with project. 2 of my teammates were very active and 1 was not - he practically waited until last weekend before the submission to start working on his tasks. By that time he was too late, we already picked up his work tasks and finished the project. 3 of us had to put in extra time to work on the project. I would advise to start early and make your teammates accountable for the tasks assigned to them.

The content from the course is all theory with 0 crossover to practical use. If your team is useless (like mine was), good luck with the final project. I had to teach my self so much with 0 help from the course or my group.

Overall, this was a very easy course that is heavily backloaded with the final paper. Most of the assignments are very easy and will not take any time. The quizzes are also very simple as the questions are mostly taken directly from the lectures. The final paper/presentation could be very time consuming depending on your group, but as long as you start early when the project comes out it should not be that bad.

The previous reviews were still true in Summer 2024. I'm providing this review for the purpose of providing tips for students who are more like me. I do not have a traditional CS Bachelor's background. This is my third class in the OMSCS program. I took this class as an introduction to learning about the security. Some, maybe majority of the, students in the section were in OMS in Cybersecurity.

The course lectures introduced a variety of topics which were new to me. However, I did not feel the learning experiences designed were helpful for me to internalize what was taught. The quizzes were on the lectures, but there was no expectation of thinking because all quiz questions could be answered by searching the slides. In fact, the response could be marked wrong if some thoughts were put into understanding the lecture.

There were two projects to choose from. Signing the nondisclosure agreement (NDA) did not limit your choice to that project. You could sign it early and get the data before you decide which project you would like to choose. NDA can be signed as soon as the semester starts. I had never worked with JSON files before so I appreciate my project experience in this class. I also suggest view the last two modules for the project, each had information on one project. I also felt the details expected on the midterm/proposal were to the level of a completed project rather than a proposal.

The instructor had weekly office hours. Some students got specific help and even code snippets, but some other students would not get a response other than "I don't know," depending on the question.

I felt the execution of the class was poor. The Canvas course material was made available throughout the semester instead of at the beginning, which I did not like. There were out-dated instructions and links in the course material. Students may ask questions on Ed and the response would be different from what was in Canvas. I would suggest reading Ed posts often.

Some of my expectations as a student (stated in XXI. Student-Faculty Expectations No. 8-10) were not met. I did not feel grading cretiria were clear or grades were posted in a timely manner. For example, I could get different number of points deducted for the same reason on different assignments of the same type. Out of xxxx graded assignments, xxxx of them had grades released outside of the two week window as stated in the syllabus. Note there was also a ceiling effect since there was a deadline to release grades set by the university. TAs could discuss what was sent in a private message in the public forum, which led me to wonder if they were trained sufficiently. Letter grades seemed not to be criterion-referenced because the conversion was only posted after all grades were posted. For Summer 2024, directly copied from the announcement was: A: 86% and above B: 76% - 87.9% C: 66% - 77.9%

As for TAs, all previous reviews touched on a lot of aspects, so I will not repeat much. One difference could be that this semester, they specifically pointed out that there were re-grading of assignments unless it was a setting problem on the auto-graded quizzes. This meant any mistakes made by the TAs would not ever be corrected. I suggest reading the instructions carefully, treating any seem-like suggested examples or guidelines as required, listing out each question separated by a question mark in the discussion prompt and response to the question, leaning on the upper limit of the word count, posting on Ed publicly with any questions, reading Ed posts, and making sure the one-sentence response is easy to find plus a lot of details.

This course was one of the worst I've ever taken. The content was extremely disappointing, and I felt like I learned nothing. The videos provided were unrelated to the assignments and projects, making it difficult to follow the course material. Also, the quality of the videos was poor, with unclear audio.

The assignments were very easy yet ambiguous, often leaving me confused about what was expected. The quizzes are very easy and everyone get high grades in them, but, this led to an unfair grading system where the TAs and professor would randomly deduct points without clear reasons, just to create a grade distribution. So, even though the course is very easy, don't expect to get a good grade. There's a high chance you might end up with a lower grade than anticipated due to the arbitrary grading practices.

Additionally, the feedback on assignments and projects is often given so late that there's no time to apply it to future work. By the time we receive feedback, we've already turned in the next few assignments, making it impossible to make improvements. This delay gives them the chance to deduct points for the same issues repeatedly without giving you a chance to address them.

This was the 2nd worst class I have taken in the OMCSY degree – the 1st being Software Development. The professor in INTA 6450 - Data Analytics and Security was nice but his lectures were mediocre. The good thing is the material – it is very easy to pick up. The problem with the class is how it is run by the teaching assistants. They grade the assignments inconsistently and often leaned toward scoring with a heavy hand. They would arbitrarily take points off for some innocuous reason and contradict the rubric. While other times not even look at your work and given 100%. They could not be trusted to do their jobs honestly and be not accountable for their mistakes. The worst was the lead TA. She set the tone for the group and was probably responsible for their group mindset – “birds of a feather”. I had to go over their heads on 2 occasions just to get things right.

Project Activities 50% Computing Activities 20% Lecture Activities 30%

I think this the most easy course of I took (even easier than AIES, AIES was easy but took more time).

Advantages:

The entire project can be completed using Python, and for many assignments and projects, the instructor provides most of the code. You only need to modify or add new functions based on your objectives. It's quite straightforward.

There are 11 simple discussion activities during the lectures.

Disadvantages:

The assignment requirements are vague. Although it's not specified that you need new functions, remember to include new functions in your exercises (some students reported losing points even when adding new functions, as their functions were deemed not particularly useful, which has been a point of controversy).

TA responses are slow, and grading errors occur. When errors are found, TAs often do not apologize or respond, requiring persistent follow-up to correct the grades.

Unlike my other courses, the same TA graded all my work throughout this course. Typically, grading is done randomly by several TAs or different TAs handle different parts of the assignment. This grading system in this course might introduce personal bias, making it less objective and fair.

Other:

Individual proposals and group project are closely related. Group projects require forming your own teams, and choosing the right teammates is crucial. For group project, in addition to writing a 10-30 page paper, you also need to create a 10-20 minute video presentation (face not required).

Goods: The lectures were the easiest to watch, understand, etc. of any i've seen at the graduate level. The professor has skill at delivering content & it made me actually want to consume the lectures. There is an overall curve at the end of the class based on buckets, this semester it was approx. 3 total points.

Bads: Overall THE WORST led class I have been in, and this falls squarely with the TAs or the direction they were given - you can't tell which it is, to be fair. They were nit picky with grades to the point where the class did not accurately assess your mastery of content, but rather was an assessment of where you fell in their curve (which they do not advertise). Severe points were taken off the largest project in the class because it was 'wordy', which is straight opinion. Discussions were graded like academic papers, without that being clear in the assignment. TAs chose their own interpretation of syllabus policies rather than following it.

Overall, just inconsistent leadership that felt like all grades were grasping at straws for something to take points off for. I get that its an 'easy' class with minimal coding, but that doesn't mean that feedback can be constructive to conduce mastery of the content - rather than nit picky & deducting just to keep everyone from having a high A.

Additionally - about 1/10th of the class, if that, is devoted to cybersecurity. The curriculum needs to be changed, and ASAP. Or retitle the class "data science" without security.

This class is easy and you won't learn a single thing - However, the TAs in this course make it less enjoyable by grading arbitrarily. To make the class harder, they just take points off for random things without explaining in detail. They gave a 3 point curve this semester - while this course is already easy as hell the fact they give a curve is just outrageous to me

I do not recommend this course. The course has lectures, quizzes, small coding assignments that require handful of line changes at most, and two large essays. The lectures are fine and informative. The quizzes are directly from the lectures and do not require honor lock so you can follow along while completing it. The coding assignments generally take less than 15 minutes for each one as most of them are “make one unique change to the code adding some new functionality”. You are allowed to make any change to it essentially.

There are two essays, one being a solo assignment and the other being a team project. As many of the other reviews state, your grade on any give assignment is completely dependent on the TA that grades you. Some hand out 100s without verifying the quality while some mark off points without specifying where. After the first essay grades were released, the TAs declared no form of regrade request but provided them on an individual basis for students that complained.

Both essays are purely tedious the first having a 5-10 page requirement and the team essay have a requirement of 10-30 pages. The assignment requirements are succinct and vague, leading me to believe this is the equivalent of a creative writing course. I spoke with multiple other students who voiced similar concerns that there was not enough to write about since the requirements were so short so they were forced to include unnecessary details to hit the page requirement.

At the end of the course, they give a pretty significant curve to the extent that I believe very few students received a ‘C’ if any at all. I was given an arbitrarily lower grade on my first essay and with no regrade requests, I thought my chance at an ‘A’ was over but the curve pushed me up to one. Perhaps this is the experience that the teaching staff are trying to give to make it seem like a legitimate course - vague requirements, arbitrarily lowered grades, then a curve at the end to reassure students. Absolutely silly course that is simply busywork. Do not take it if you don’t have to.

When your assignment is handed over to certain TAs, you are likely to receive a grade of B. This indicates that the course has been deliberately made more challenging by employing an unjust grading system, instead of focusing on improving the overall quality of the course.

Easy class, but this is by far the worst class I've taken. The TAs are actually idiots and give deductions on grades without any explanation. Instructions for assignments are vague and the head TA is a hard grader for absolutely no reason. This class is definitely a low time commitment easy B and your chances for an A are random and at the mercy of the TA who grades you. This is my 8th course in the program and is by far the worst one I have taken.

A very easy and low time commitment course. Easy to pair with other courses. Only issue is the grading which completely depends on the TA. You would never understand why you got the deduction. I felt that grading was done to maintain the curve and I was the unfortunate one to fall on the B grade level. This was my 9th course and never I have felt that marks deductions were not fair. Easy A if you do not fall under the head TA for grading.

Should have been fairly straightforward, but the head TA is super nitpicky and makes the whole experience fairly bad. Grades take forever to be released so you never really know where you stand. So much busy work with no value. Given the opportunity again I would have not take this class.

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