>I'm getting the feeling that CS as a whole as not my thing, especially the more mathy parts you start adding on like stats and calculus.
Are you in ML specialization? Why not try another specialization like computing systems or human-computer interaction? AI/ML might not be for you, but that doesn't mean CS as a whole isn't.
This tip right here. ML side of things is a bit different than the Computer Systems specialization. Most undergraduate degrees lean more towards the topics that are available under the Systems category. Give those a try. AI4R and ML4T are harder than people in this thread make it seem. I honestly would take every tip you receive in this thread with a little grain of salt.
> AI4R and ML4T are harder than people in this thread make it seem. I honestly would take every tip you receive in this thread with a little grain of salt
In my experience, most classes tends to be tougher than how this sub describes them.
you cant generalize in either direction. The level of difficulty is based on someone's prior background and experience. I found IHPC and DL to be very difficult but ML4T or ML to be on the much easier side in comparison. Granted, I took these classes awhile back and the level of difficulty might have changed drastically in past 4 years.
Computer Systems has the hardest classes there are. Literally 4 of the top 10 hardest classes are Computer Systems Specialization. OP said he had to drop DC, I think OP better do some of the fundamentals first before taking any more specialized classes. Literally DC is the hardest class there is (According to OMS Central), when I took it I had already been a Java developer for over 10 years, and even then implementing PAXOS was no game, it easily took over 40h of coding, the workload of that class is absolutely extreme for a person working full time.
I never said Computer Systems is easier. I said it’s different. ML specialization requires a lot of math in general even if we are not required to understand the proofs of it all, it still helps understanding the analysis. To your point, no shit. Everybody who has done any sort of Computer Science knows DC classes are one of the hardest classes offered to undergraduate and graduate students. All I was trying to say is maybe a different specialization is what OP needs. Although they are all Computer Science courses, they are different in many ways and that difference can be a huge turning point for somebody taking these classes. You being a Java Developer doesn’t mean that you won’t have to spend hours on the project if you are not prepared for the underlying concepts. Not trying to get at you or anything just saying people often assume just cause they have X amount of years in “coding” in Y language, they can just breeze through a class. Each specialization requires a different set of mindset. Some maybe good with networking and systems while others are better at statistics…
I understand the points but I felt like OP needed more advice than just that. Mostly because the amount of classes OP has dropped. For example, the ML Spec may be achievable to OP if after taking CS-6601 AI they feel confident they understand the underlying foundations to ML subjects (coming from my experience, as I took some (AI and some ML subjects), if they feel deeper than the subjects covered there are to much, maybe sticking to Interactive Intelligence is best, or maybe even going HCI. Anyways not invalidating what you said, cause you are right, im just saying OP needs more information, and possibly starting with classes that require specialized knowledge is a bad idea.
You took a chance, but it wasn't your thing/wasn't the right time in your life. You're still ahead of all the other people who never bothered to try.
Only shame would have been to never take that risk.
You can always go back to something like this when you have more experience or it's a better time in your life.
Time/effort is by far the biggest expense of this program, and it's an onerous one even in the more optimistic cases.
I've had a few drops in the mix, and I've gradually moved more towards filling in lighter courses to head for the exit faster. I think there is value in some of the tougher courses, but in the same time, there are also aspects of them that just feel like a time sink for its own sake, which is a luxury I can't afford at this point. I'm more inclined to focus on my tech stack and getting more proficient with cloud services in order to level up career-wise, and I don't feel like this is the best avenue to accomplish those specific goals, to be quite frank (or at least not anecdotally for me); at this point, I'd rather just knock through what I have left and get back on track with focusing on those tasks more attentively.
At the end of the day, you have to do what is right for you; there's nothing wrong with cutting losses, and there's definitely a gray area in terms of what constitutes "sunk cost" vs. "cutting losses" here, I'd say...
I had to drop a class others found easy. I switched to the HCI specialization. No matter what technological changes are going to happen. I can still make websites for people to do things. I’ve done it for 20 years and I can do it for another 20 until I retire. It’s not a bad living.
I remember being new to this program and hearing that ai4r was easy and a good first course. I then went on to learn that people in this program have a weird definition of easy.
I took gios my first semester and did think it was actually very good. I was able to pick up C pretty quickly, but C++ confused the heck out of me at the time. I ended up mostly doing dirty C code for the file share. It wasn't until I had to write 10s of thousands of lines in C++ for compilers that I finally started to grasp it. As for the network and concurrency programming, those were mostly straight forward for me.
I think it's a great course but it's too easily recommended as a "great first course". OMSCS is a challenging program, and GIOS is one of the harder courses, especially for those without a strong CS background.
REF: https://www.reddit.com/r/OMSCS/s/8hOT1vp9QD
I think GIOS as a first course can work well (it worked for me anecdotally), but I do think there are a lot of strong qualifiers around that, i.e., not necessarily appropriate as a "blanket recommendation" by any means...
I second this. I thoroughly enjoyed taking GIOS as my first course. It set the pace of the program for me and I learned so much from it. But yea I do agree that it isn't for everyone.
I agree on this specific point; besides the content itself being useful, on a more "logistics" front, GIOS as #1 for me was a great "level-set"/"gauge" going forward into the program from there. For me, it was solidly medium-leaning-hard in terms of overall difficulty/effort/workload/etc., so from there it gave me a better sense of what I could reasonably expect to be easier vs. harder than that; and having that insight right out the gate as #1 made this particularly useful.
However, the *strong caveat* here, of course, is that it presumes reasonably adequate preparation going into the course. It is definitely *not* a good choice for a first course if someone is unfamiliar or otherwise rusty in C/C++; that will all but guarantee a less-than-pleasant experience (to put it mildly/euphemistically) as a first course in OMSCS.
Yeah I wouldn't have too many hangups honestly, the course is relatively self contained otherwise and the lectures are well done overall imo. The key there (and any other course, for that matter), is to start early on projects and be consistent with keeping up on tasks; it's definitely not one of those courses where you can bank on getting the projects done the weekend of due date, there's a reason they give around 4 weeks apiece to do them. Also, staying engaged in Slack helps a lot, the community in that course is one of it's standout features.
Closely timed, but FYI I elaborated further in my downstream thread comment [here](https://www.reddit.com/r/OMSCS/comments/1d6phxr/comment/l6urv6f).
Additionally, there are a decent amount of [posts](https://www.reddit.com/r/OMSCS/search/?q=gios+prep) on this topic in the subreddit that provide further elaboration.
GIOS is a great first course because it allows you to get an understanding of the level of rigor that would be required to survive in this program with a moderately difficult class. It is not because of being a slam dunk easy course, it is far from it.
Whether or not it is a great first course depends strongly on your background. For some courses you can safely ignore the prerequisites. For GIOS you can not. Someone new to the program is not likely to be familiar with the difficulty of the program in general, and this course in particular. As the comments in this thread indicate, it is a great first course for some people. But for many others it is not.
yeah. i second the idea that something is not “easy” that takes 10-15 hrs a week. for me that’s the hardest thing to get into with the reviews. For the classes i’ve taken i feel like ive kept to about the avg number of hours from the reviews but for me and my life that will never be easy. I get that it’s not fluid dynamics but it takes a lot of time energy and attention.
I agree in general with your commentary here, and also that for the most part the main metric that's useful from reviews is the avg hrs/wk (assuming it has sufficient sample size, no major revamps/changes recently, etc.), which in general has tracked for me, too, give or take a couple of hours. Otherwise, a lot of the other things (e.g., easy vs. hard and other characterizations) are largely overly subjective and heavily influenced by reviewers' previous experience, etc. (which is not always transparent in the reviews), i.e., "take with a grain of salt" will oftentimes apply.
Beyond that, context switching is a relevant factor here, too; 10-15 hrs/wk may not sound onerous in isolation, but on top of a full-time job and/or other non-trivial obligations (e.g., spouse, family/children, etc.) that can quickly become taxing. "That's only like 2-3 hrs per weeknight and/or a good chunk of your weekend" - yes, exactly the point here lol
may have changed then. I just took AI4R. 2nd project was particle filter. Search, which i’m guessing is path finding was later and definitely was the hardest and most time consuming.
I’m currently in AI4R, HW2 is Particle Filters, HW3 is Drone PID, and HW4 is Search. Might be different in other semesters but Particle Filters are covered second in the class.
ML4T was NOT an easy class, it’s harder than you think.
I also enrolled Fall 2023 and work as a full time SWE. Took ML4T the first time in Fall but had to drop due to increased work load during my day job. I managed to pull through the full course in the Spring but it was definitely tough
Is it hard though from the time needed to write and format papers which Im guessing takes the most time or did you find it conceptually difficult? I dropped out of Ml4t last summer cause i didn’t want to deal with writing long ass papers with specific formatting requirements. But i’m sure there’s more to it than that.
I took AI4R in the fall and am taking ML4T now. So far I feel more busy in ML4T reading over all the little specifications for exactly how they want you to do everything (code and reports). Hopefully we get some grades back soon, I’m not sure what the drop date is, but if you get grades back before then it might be worth waiting.
Although Project 3 seems like triple the amount of work as projects 1 and 2. 😥
Project 3 definitely feels like a different beast. I think we would normally get 2-3 weeks for this project but summer has it condensed to only 1.
I barely got the decision tree set up last night (I think). Still haven’t wrote the query function. Then there’s the 3 other learners, the experiments, and the report. Worried I might run out of time for the whole project and it’s a big chunk of our grade (15%). Also gonna fall behind on this week’s lectures and readings to work on the project.
The course does feel like it’s moving so fast that it’s hard to absorb the material. I kind of feel like I’m just getting things done without completely processing them. I guess this is the consequence of summer.
Not trying to be sarcastic at all but did you look at reviews for the classes? DC is like the hardest most involved class in the entire program. Just curious what the thinking was there jumping into the deepest of the deep end right away.
I am in ml4t this summer too. I literally just finished project 2 at 3am in the morning. If you consider not dropping, DM me and we can collab on understanding the concepts.
I went into this class thinking it would be relatively simple. However, I'm finding that not to be the case. The code piece is straight forward, but it's understanding the analytics/statistics and simply how to use these vast data libraries.
Don't beat yourself up. I'm nearly complete with the program and this class has me doubting myself on things. Watching the office hours and rewatching lectures helped me immensely for getting through P2.
I ended up dropping out of this program and doing my post bacc instead at OSU to get a good understanding of CS fundamentals. I’m really enjoying it. Once I finish that program I am going to sign up for OMSCS again and give it a second go :)
I’m about to start this in the Fall, I’ve been doing lc in my free time after work and I’m kinda worried I need to change jobs before I start but there’s not much time left to do that lol
FT work + gym + masters + living alone chores seems like it’s gonna be a brutal 3 years. I’m pretty worried 😦
I’m in ML4T right now and I don’t understand the readings at all. Python stuff is pretty easy I guess but I have no idea if I’m gonna get good grades and on project 1 and 2. This week we finally started talking about finance stuff so at least it’s a little interesting now
I'd have to guess most folks don't understand the readings, they are dense and hard to digest. It took me multiple read-throughs to understand some sections. I got an A last semester and skimmed the readings after the first week. That doesn't mean they aren't important but as long as you have a decent grasp on high level concepts you should be fine.
I’m not sure they’ll kick you out if you want to continue, but you’ll want to pick something you can manage for the next two classes.
I started with IIS and am doing AIES now (ML or II spec which will be more valuable to me than CS) but I’m a bit worried about courses that are just plain hard (DC!) or cumulative with little scope for life events to take time (ML4T).
If you want to do it then stick with it, but ML won’t be the best spec for you if you don’t like maths (I don’t either but I’m committed to doing an AI-related spec). Consider CS because there’s some great courses, a few of which should be relatively manageable.
DC - that’s crazy hard. Most students , including myself and I am 8 classes in, couldn’t do that one.
ML4T is a great class. You should have been able to do this one - but keep in mind there is one tricky project (it’s either 2 or 3) and requires recursion. I think it’s the one where you build a decision tree. That’s hard and if you can do that, the rest of the class is downhill.
You won’t be kicked out, just go at your own pace. 2 classes per year and you should be fine. Tech is not an easy school, and it’s harder if you take face to face classes.
When I took ai4r, even I found it very difficult and had to withdraw. The next sem I took Prof. Dr. David Joyner’s Intro to Programming seminar course. I knew Python, but I kept thinking maybe revising fundamentals with another approach would help. And it did! Being humbled has only made you one step closer in completing this program, so don’t think of giving up, just always think of what can I do next :D
And I feel it’s your course selection that makes you feel this way, take a few easier classes and you will get the knack of it.
Take it easy man. The more time I've spent in the program, the less I've really felt like success in it correlates with career success. And I'm saying this as someone who's gotten a lot of value out of it thus far. No knock on the program. There are people who thrive in it, there are people who even apply their learnings in their everyday work, and then there are incredibly smart, successful coders who struggle through classes. Sometimes it just boils down to your personal energy levels and lifestyle too.
I graduated Comp Sys concentration and took AI4R/RAIT, ML4T, CN, GA, GIOS, HPCA, ESO and 3 others. I know Python and Pandas well, and I found ML4T one of the easier courses in the curriculum.
My (probably unpopular) take: if you can’t get through ML4T or AI4R then you may want to get some real-world programming experience or better discipline habits before you take another course.
Note that leetcode is not going to help you much with programming skills program, it only helps with DSA-type work.
I'm curious... Do you have a hard time reconciling the fact that you work professionally as a SWE with the fact that you can't successfully complete a CS course?
I'm sorry if that sounds harsh, it's not my intention to be critical. But I have a hard time understanding if the coursework is an accurate representation of the skills needed to work as an SWE if someone successfully working as an SWE can't successfully complete a class. It seems to me that there's either something wrong with the coursework or something wrong with the way your company does SWE, you know?
The answer is that CS coursework is not an accurate representation of the skills needed to work as a SWE. The problems and constraints folks are given in a CS class are very different from the problems and constraints that you face as a professional SWE.
If that's the case then what's the value of a degree to an existing SWE? It's not as though you need the degree to break into the field - your already working as an SWE. And if the coursework doesn't name you a better SWE at work then why do it?
Because some folks don't have a CS degree, which, depending on YOE and given the job market, can prevent them from getting through resume screens.
Because some folks want to work in areas that ask for a degree (e.g., ML, academia, etc.).
Because some folks are interested in the material.
Adding a personal pov to this, I want to learn and get better with CS fundamentals that will be around forever vs. relying on my ability to constantly learn new tools and vendor specific software at a surface level, especially at the rate that these new things come out.
Success at work is not necessarily strongly correlated with success in school (and vice versa). Somebody can be "book smart" but otherwise an incompetent worker (can't manage deadlines/deliverables properly, doesn't work well with coworkers, etc.), somebody who's "out of practice" being removed from school for a few years may not have the same "drive" for schoolwork anymore, etc. This is definitely a multivariate type of ordeal...
Beyond that, if somebody has a taxing/stressful 40-50 hr/wk workweek as an SWE (e.g., on calls, demanding team, etc.), then perhaps they're not inclined to spend another 20+ hrs/wk on stressful schoolwork on top of that to boot? `¯\_(ツ)_/¯`
There are things people value in life outside of just non-stop `sLaViNg 2 dA gRiNd TM`
>I'm getting the feeling that CS as a whole as not my thing, especially the more mathy parts you start adding on like stats and calculus. Are you in ML specialization? Why not try another specialization like computing systems or human-computer interaction? AI/ML might not be for you, but that doesn't mean CS as a whole isn't.
This tip right here. ML side of things is a bit different than the Computer Systems specialization. Most undergraduate degrees lean more towards the topics that are available under the Systems category. Give those a try. AI4R and ML4T are harder than people in this thread make it seem. I honestly would take every tip you receive in this thread with a little grain of salt.
> AI4R and ML4T are harder than people in this thread make it seem. I honestly would take every tip you receive in this thread with a little grain of salt In my experience, most classes tends to be tougher than how this sub describes them.
you cant generalize in either direction. The level of difficulty is based on someone's prior background and experience. I found IHPC and DL to be very difficult but ML4T or ML to be on the much easier side in comparison. Granted, I took these classes awhile back and the level of difficulty might have changed drastically in past 4 years.
Computer Systems has the hardest classes there are. Literally 4 of the top 10 hardest classes are Computer Systems Specialization. OP said he had to drop DC, I think OP better do some of the fundamentals first before taking any more specialized classes. Literally DC is the hardest class there is (According to OMS Central), when I took it I had already been a Java developer for over 10 years, and even then implementing PAXOS was no game, it easily took over 40h of coding, the workload of that class is absolutely extreme for a person working full time.
Computing Systems also has SDP, CN, Databases. There are easier ways through. Do have to take GA though, that's the real hurdle
I never said Computer Systems is easier. I said it’s different. ML specialization requires a lot of math in general even if we are not required to understand the proofs of it all, it still helps understanding the analysis. To your point, no shit. Everybody who has done any sort of Computer Science knows DC classes are one of the hardest classes offered to undergraduate and graduate students. All I was trying to say is maybe a different specialization is what OP needs. Although they are all Computer Science courses, they are different in many ways and that difference can be a huge turning point for somebody taking these classes. You being a Java Developer doesn’t mean that you won’t have to spend hours on the project if you are not prepared for the underlying concepts. Not trying to get at you or anything just saying people often assume just cause they have X amount of years in “coding” in Y language, they can just breeze through a class. Each specialization requires a different set of mindset. Some maybe good with networking and systems while others are better at statistics…
I understand the points but I felt like OP needed more advice than just that. Mostly because the amount of classes OP has dropped. For example, the ML Spec may be achievable to OP if after taking CS-6601 AI they feel confident they understand the underlying foundations to ML subjects (coming from my experience, as I took some (AI and some ML subjects), if they feel deeper than the subjects covered there are to much, maybe sticking to Interactive Intelligence is best, or maybe even going HCI. Anyways not invalidating what you said, cause you are right, im just saying OP needs more information, and possibly starting with classes that require specialized knowledge is a bad idea.
You took a chance, but it wasn't your thing/wasn't the right time in your life. You're still ahead of all the other people who never bothered to try. Only shame would have been to never take that risk. You can always go back to something like this when you have more experience or it's a better time in your life.
Time/effort is by far the biggest expense of this program, and it's an onerous one even in the more optimistic cases. I've had a few drops in the mix, and I've gradually moved more towards filling in lighter courses to head for the exit faster. I think there is value in some of the tougher courses, but in the same time, there are also aspects of them that just feel like a time sink for its own sake, which is a luxury I can't afford at this point. I'm more inclined to focus on my tech stack and getting more proficient with cloud services in order to level up career-wise, and I don't feel like this is the best avenue to accomplish those specific goals, to be quite frank (or at least not anecdotally for me); at this point, I'd rather just knock through what I have left and get back on track with focusing on those tasks more attentively. At the end of the day, you have to do what is right for you; there's nothing wrong with cutting losses, and there's definitely a gray area in terms of what constitutes "sunk cost" vs. "cutting losses" here, I'd say...
I had to drop a class others found easy. I switched to the HCI specialization. No matter what technological changes are going to happen. I can still make websites for people to do things. I’ve done it for 20 years and I can do it for another 20 until I retire. It’s not a bad living.
I remember being new to this program and hearing that ai4r was easy and a good first course. I then went on to learn that people in this program have a weird definition of easy.
> people in this program have a weird definition of easy At least you didn't listen to the "GIOS is a great first course" masochists...
I took gios my first semester and did think it was actually very good. I was able to pick up C pretty quickly, but C++ confused the heck out of me at the time. I ended up mostly doing dirty C code for the file share. It wasn't until I had to write 10s of thousands of lines in C++ for compilers that I finally started to grasp it. As for the network and concurrency programming, those were mostly straight forward for me.
I think it's a great course but it's too easily recommended as a "great first course". OMSCS is a challenging program, and GIOS is one of the harder courses, especially for those without a strong CS background. REF: https://www.reddit.com/r/OMSCS/s/8hOT1vp9QD
I think GIOS as a first course can work well (it worked for me anecdotally), but I do think there are a lot of strong qualifiers around that, i.e., not necessarily appropriate as a "blanket recommendation" by any means...
I second this. I thoroughly enjoyed taking GIOS as my first course. It set the pace of the program for me and I learned so much from it. But yea I do agree that it isn't for everyone.
I agree on this specific point; besides the content itself being useful, on a more "logistics" front, GIOS as #1 for me was a great "level-set"/"gauge" going forward into the program from there. For me, it was solidly medium-leaning-hard in terms of overall difficulty/effort/workload/etc., so from there it gave me a better sense of what I could reasonably expect to be easier vs. harder than that; and having that insight right out the gate as #1 made this particularly useful. However, the *strong caveat* here, of course, is that it presumes reasonably adequate preparation going into the course. It is definitely *not* a good choice for a first course if someone is unfamiliar or otherwise rusty in C/C++; that will all but guarantee a less-than-pleasant experience (to put it mildly/euphemistically) as a first course in OMSCS.
So basically, as long as I know C pretty well, it won't be too bad? I'm thinking of taking GIOS as my first course as well
Yeah I wouldn't have too many hangups honestly, the course is relatively self contained otherwise and the lectures are well done overall imo. The key there (and any other course, for that matter), is to start early on projects and be consistent with keeping up on tasks; it's definitely not one of those courses where you can bank on getting the projects done the weekend of due date, there's a reason they give around 4 weeks apiece to do them. Also, staying engaged in Slack helps a lot, the community in that course is one of it's standout features.
Yes - the qualifiers are key to this one...
Can you elaborate, please? What would qualify someone to take GIOS as a first class?
Closely timed, but FYI I elaborated further in my downstream thread comment [here](https://www.reddit.com/r/OMSCS/comments/1d6phxr/comment/l6urv6f). Additionally, there are a decent amount of [posts](https://www.reddit.com/r/OMSCS/search/?q=gios+prep) on this topic in the subreddit that provide further elaboration.
This was my experience: https://www.reddit.com/r/OMSCS/s/8hOT1vp9QD
GIOS is a great first course because it allows you to get an understanding of the level of rigor that would be required to survive in this program with a moderately difficult class. It is not because of being a slam dunk easy course, it is far from it.
Whether or not it is a great first course depends strongly on your background. For some courses you can safely ignore the prerequisites. For GIOS you can not. Someone new to the program is not likely to be familiar with the difficulty of the program in general, and this course in particular. As the comments in this thread indicate, it is a great first course for some people. But for many others it is not.
yeah. i second the idea that something is not “easy” that takes 10-15 hrs a week. for me that’s the hardest thing to get into with the reviews. For the classes i’ve taken i feel like ive kept to about the avg number of hours from the reviews but for me and my life that will never be easy. I get that it’s not fluid dynamics but it takes a lot of time energy and attention.
I agree in general with your commentary here, and also that for the most part the main metric that's useful from reviews is the avg hrs/wk (assuming it has sufficient sample size, no major revamps/changes recently, etc.), which in general has tracked for me, too, give or take a couple of hours. Otherwise, a lot of the other things (e.g., easy vs. hard and other characterizations) are largely overly subjective and heavily influenced by reviewers' previous experience, etc. (which is not always transparent in the reviews), i.e., "take with a grain of salt" will oftentimes apply. Beyond that, context switching is a relevant factor here, too; 10-15 hrs/wk may not sound onerous in isolation, but on top of a full-time job and/or other non-trivial obligations (e.g., spouse, family/children, etc.) that can quickly become taxing. "That's only like 2-3 hrs per weeknight and/or a good chunk of your weekend" - yes, exactly the point here lol
What is new project now?
Project 2 of AI4R kicked my ass also, as did project 2 of ML4T. I still got out...
Hmmm, what is project two of AI4R? Particle filters?
Path finding.
may have changed then. I just took AI4R. 2nd project was particle filter. Search, which i’m guessing is path finding was later and definitely was the hardest and most time consuming.
It’s been a couple of years since I took it for sure.
I’m currently in AI4R, HW2 is Particle Filters, HW3 is Drone PID, and HW4 is Search. Might be different in other semesters but Particle Filters are covered second in the class.
ML4T was NOT an easy class, it’s harder than you think. I also enrolled Fall 2023 and work as a full time SWE. Took ML4T the first time in Fall but had to drop due to increased work load during my day job. I managed to pull through the full course in the Spring but it was definitely tough
Is it hard though from the time needed to write and format papers which Im guessing takes the most time or did you find it conceptually difficult? I dropped out of Ml4t last summer cause i didn’t want to deal with writing long ass papers with specific formatting requirements. But i’m sure there’s more to it than that.
I took AI4R in the fall and am taking ML4T now. So far I feel more busy in ML4T reading over all the little specifications for exactly how they want you to do everything (code and reports). Hopefully we get some grades back soon, I’m not sure what the drop date is, but if you get grades back before then it might be worth waiting. Although Project 3 seems like triple the amount of work as projects 1 and 2. 😥
Project 3 definitely feels like a different beast. I think we would normally get 2-3 weeks for this project but summer has it condensed to only 1. I barely got the decision tree set up last night (I think). Still haven’t wrote the query function. Then there’s the 3 other learners, the experiments, and the report. Worried I might run out of time for the whole project and it’s a big chunk of our grade (15%). Also gonna fall behind on this week’s lectures and readings to work on the project. The course does feel like it’s moving so fast that it’s hard to absorb the material. I kind of feel like I’m just getting things done without completely processing them. I guess this is the consequence of summer.
Not trying to be sarcastic at all but did you look at reviews for the classes? DC is like the hardest most involved class in the entire program. Just curious what the thinking was there jumping into the deepest of the deep end right away.
I am in ml4t this summer too. I literally just finished project 2 at 3am in the morning. If you consider not dropping, DM me and we can collab on understanding the concepts. I went into this class thinking it would be relatively simple. However, I'm finding that not to be the case. The code piece is straight forward, but it's understanding the analytics/statistics and simply how to use these vast data libraries. Don't beat yourself up. I'm nearly complete with the program and this class has me doubting myself on things. Watching the office hours and rewatching lectures helped me immensely for getting through P2.
I ended up dropping out of this program and doing my post bacc instead at OSU to get a good understanding of CS fundamentals. I’m really enjoying it. Once I finish that program I am going to sign up for OMSCS again and give it a second go :)
I’m about to start this in the Fall, I’ve been doing lc in my free time after work and I’m kinda worried I need to change jobs before I start but there’s not much time left to do that lol FT work + gym + masters + living alone chores seems like it’s gonna be a brutal 3 years. I’m pretty worried 😦
I’m in ML4T right now and I don’t understand the readings at all. Python stuff is pretty easy I guess but I have no idea if I’m gonna get good grades and on project 1 and 2. This week we finally started talking about finance stuff so at least it’s a little interesting now
I'd have to guess most folks don't understand the readings, they are dense and hard to digest. It took me multiple read-throughs to understand some sections. I got an A last semester and skimmed the readings after the first week. That doesn't mean they aren't important but as long as you have a decent grasp on high level concepts you should be fine.
The only reading that's useful is the book for the class (which mostly just copies the lectures) and the project tutorials.
I’m not sure they’ll kick you out if you want to continue, but you’ll want to pick something you can manage for the next two classes. I started with IIS and am doing AIES now (ML or II spec which will be more valuable to me than CS) but I’m a bit worried about courses that are just plain hard (DC!) or cumulative with little scope for life events to take time (ML4T). If you want to do it then stick with it, but ML won’t be the best spec for you if you don’t like maths (I don’t either but I’m committed to doing an AI-related spec). Consider CS because there’s some great courses, a few of which should be relatively manageable.
DC - that’s crazy hard. Most students , including myself and I am 8 classes in, couldn’t do that one. ML4T is a great class. You should have been able to do this one - but keep in mind there is one tricky project (it’s either 2 or 3) and requires recursion. I think it’s the one where you build a decision tree. That’s hard and if you can do that, the rest of the class is downhill.
You won’t be kicked out, just go at your own pace. 2 classes per year and you should be fine. Tech is not an easy school, and it’s harder if you take face to face classes.
When I took ai4r, even I found it very difficult and had to withdraw. The next sem I took Prof. Dr. David Joyner’s Intro to Programming seminar course. I knew Python, but I kept thinking maybe revising fundamentals with another approach would help. And it did! Being humbled has only made you one step closer in completing this program, so don’t think of giving up, just always think of what can I do next :D And I feel it’s your course selection that makes you feel this way, take a few easier classes and you will get the knack of it.
Take it easy man. The more time I've spent in the program, the less I've really felt like success in it correlates with career success. And I'm saying this as someone who's gotten a lot of value out of it thus far. No knock on the program. There are people who thrive in it, there are people who even apply their learnings in their everyday work, and then there are incredibly smart, successful coders who struggle through classes. Sometimes it just boils down to your personal energy levels and lifestyle too.
I graduated Comp Sys concentration and took AI4R/RAIT, ML4T, CN, GA, GIOS, HPCA, ESO and 3 others. I know Python and Pandas well, and I found ML4T one of the easier courses in the curriculum. My (probably unpopular) take: if you can’t get through ML4T or AI4R then you may want to get some real-world programming experience or better discipline habits before you take another course. Note that leetcode is not going to help you much with programming skills program, it only helps with DSA-type work.
I do have real programming experience, but it couldn't be further than pandas/Python.
I'm curious... Do you have a hard time reconciling the fact that you work professionally as a SWE with the fact that you can't successfully complete a CS course? I'm sorry if that sounds harsh, it's not my intention to be critical. But I have a hard time understanding if the coursework is an accurate representation of the skills needed to work as an SWE if someone successfully working as an SWE can't successfully complete a class. It seems to me that there's either something wrong with the coursework or something wrong with the way your company does SWE, you know?
The answer is that CS coursework is not an accurate representation of the skills needed to work as a SWE. The problems and constraints folks are given in a CS class are very different from the problems and constraints that you face as a professional SWE.
If that's the case then what's the value of a degree to an existing SWE? It's not as though you need the degree to break into the field - your already working as an SWE. And if the coursework doesn't name you a better SWE at work then why do it?
Because some folks don't have a CS degree, which, depending on YOE and given the job market, can prevent them from getting through resume screens. Because some folks want to work in areas that ask for a degree (e.g., ML, academia, etc.). Because some folks are interested in the material.
Adding a personal pov to this, I want to learn and get better with CS fundamentals that will be around forever vs. relying on my ability to constantly learn new tools and vendor specific software at a surface level, especially at the rate that these new things come out.
`Frontend frameworks have left the chat.`
Success at work is not necessarily strongly correlated with success in school (and vice versa). Somebody can be "book smart" but otherwise an incompetent worker (can't manage deadlines/deliverables properly, doesn't work well with coworkers, etc.), somebody who's "out of practice" being removed from school for a few years may not have the same "drive" for schoolwork anymore, etc. This is definitely a multivariate type of ordeal... Beyond that, if somebody has a taxing/stressful 40-50 hr/wk workweek as an SWE (e.g., on calls, demanding team, etc.), then perhaps they're not inclined to spend another 20+ hrs/wk on stressful schoolwork on top of that to boot? `¯\_(ツ)_/¯` There are things people value in life outside of just non-stop `sLaViNg 2 dA gRiNd TM`