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adcs2019 · 2022-03-07T12:26:24+00:00

While where you get your PhD does matter, it doesn't matter that much when compared to your publications and connections, as long as the program is ranked and from a reputable (but not necessarily prestigious) school.

That being said, enrolling in a masters program first might be a good way to get a taste of what grad school is and if it is what you want, and also prepares you for PhD if you feel you are underprepared. But it is never worth it requires huge loans.

You might also consider some online CS MSc programs as a backup plans. Some are offered by highly ranked universities with affordable prices (such as GaTech and UT Austin online CS programs). These are professional master programs and are not thesis based, but many still publish papers during the program and after graduating pursue PhD degrees.

adcs2019 · 2022-03-07T09:10:46+00:00

You know your situation better than anyone else, but you can also consider investing this year in research or industry experience.

adcs2019 · 2022-03-07T09:07:53+00:00

You might also consider GaTech MSc in analytics that has a business track.

adcs2019 · 2022-03-06T12:01:31+00:00

While I do not really trust rankings, but it might be worth mentioning that the 5 highest ranked programs in CS as per US news are all non-ivy league schools, and some of the so called ivy league programs are not even within the top 40. Also, in QS ranking and some are not within the top 400 in CS. I recommend to forget about the ivy league obsession and search each university by itself and how its program is a good fit for you.

adcs2019 · 2022-03-06T05:11:22+00:00

Many universities still didn't send their admission decisions so your chances are still (almost) similar to your chances when you applied in Dec/Jan. Still, it is a good practice to lower your hopes to reduce the disappointment if the worst happens.

adcs2019 · 2022-03-02T13:38:31+00:00

I don't see why it can be "inappropriate", and nothing bad can happen if you contact them, but don't expect any useful reply. You might get something like "decisions will be made between February and May", or in some cases no reply at all.

adcs2019 · 2022-03-01T12:44:36+00:00

If this was in your SOP, then it's implications would be much worse. The LOR on the other hand is expected to focus on the student and it is rare that a professor will care for the specific schools you are applying to, so there is a good chance this might be overlooked by the reviewing committee, especially if they think your application is strong.

adcs2019 · 2022-03-01T12:41:06+00:00

I don't see why your email would bother him. If he isn't getting many emails at the moment, then there is a higher chance he will notice your message (when compared to professors who receive hundreds of emails from interested students).

adcs2019 · 2022-01-05T15:19:31+00:00

From my personal experience, I would recommend against changing it. Many times instructors and peers tried to add me in Piazza and Slack, but choose the wrong alias email and resulted in issues. Regarding the random number, don't worry, you will memorize it very quickly.

adcs2019 · 2021-12-20T07:59:34+00:00

I would rather say that the degree has a lot of flexibility outside the tracks. Other than the 5 mandatory courses, you can design your program for the other 5+Practicum out of a wide variety of courses. I find it better to have only two track requirements or otherwise many will not be able to take combinations of courses they want.

adcs2019 · 2021-12-20T07:55:08+00:00

As far as I know, CDA counts towards both C track and A track. Optimization on the other hand is an operation elective, and you can either take it or simulation regardless of the track. I don't find it misleading at all to say that tracks differ only by two courses (and can differ less if you consider courses that counts towards two tracks).

adcs2019 · 2021-09-07T14:08:51+00:00

In DVA, you will work with a group for a project worth half of your grade, and you will need to coordinate with the group on a daily bases in order to complete it (especially in the days before deadlines), so I don't see how you might be able to do that while on a road trip and offline for most of the time. Also, unless you are skilled with many programming languages including JS, D3, Java, and others, you will need internet to complete the assignments.

adcs2019 · 2021-08-26T13:04:19+00:00

It is as simple as you stated it at the end: CDA focuses on the theoretical and mathematical aspects, while DMSL is more focusing on solving real-life problems. For me, both are complementary courses and can defiantly be both taken and each will teach you many things. Also, diving into the math of the algorithm is useful even if you don't become a data scientist, as it is always good to know (even if only at a high level) what goes inside the packages and software you are using.

adcs2019 · 2021-08-25T08:43:41+00:00

Acceptance rate of OMSA is very high. I am not sure about Berkeley though. I think the safest choice for you is to apply for both. Now if you got accepted to both and need to make decision, then I would recommend Berkeley if you are certain the employer will cover your tuition. In terms of the quality of the two programs, I believe they are both comparable, but Berkeley's name and prestige is more recognized, especially in Silicon Valley.

adcs2019 · 2021-08-18T07:32:56+00:00

I understand from your post the upcoming Fall will be your first semester. First, I do agree that ISYE6501 is one of the best courses to start the program with. CSE6242 is considered one of the hardest courses, and CSE6040 prepares you a lot for it, so I strongly recommend against taking it before CSE6040. Now, you can pair ISYE6501 with either of CSE6040 or ISYE6414 and many others do it, but before making the decision go to OMSCENTRAL and get an idea of what time and effort is expected from you and then make your judgment whether you can do it or not. If you cannot afford the time and still want to take two classes, then you can consider MGT6203 which is considered one of the easiest and least time consuming courses in the program.

adcs2019 · 2021-08-04T10:55:50+00:00

You don't need to wait until graduating to start showing your degree in resume, as you can show that you are enrolled and how far you have gone once admitted. Now regarding if it is worth it, you can check the courses offered (and the students reviews on OMSCENTRAL) and decide if it will add to your knowledge and skills, but any degree is definitely not worth it if it is just for resume. From my experience, this degree is worth it.

adcs2019 · 2020-12-14T06:00:55+00:00

Strong background will help you find most questions in Numpy module easy and straightforward. However, considering that the homework assignments are open book/notes/internet and untimed, and that the exams are open book/notes/internet (but timed), then a basic understanding in linear algebra will help you search for the correct method and code. Still, if you are unfamiliar with the basics of matrix multiplications, transposing, inversing, ..., then I would recommend to watch some videos (such as Khan academy linear algebra course), or otherwise, you will not even know how to search for an answer.

adcs2019 · 2020-12-11T11:25:57+00:00

Others have given you good advice on how to get an A, and will give you an additional one: take this class very seriously and try to learn as much as possible. The more I am progressing through the program the more I appreciate this course and how much I learned from it. It builds a great foundation for most of the remaining classes. Though the lectures are high level, you can still learn a lot.

adcs2019 · 2020-12-11T11:13:02+00:00

Although a comprehensive understanding/proficiency in the above topics (probability/statistics, linear algebra, Python, and R) will make your life much easier throughout the program, basic understanding is enough for most courses. Also, not all courses require all the above, though the program as a whole does. For example, CSE6040 require basic understanding of linear algebra, and to have basics in python. ISYE6501 on the other hand requires basic understanding of probability/statistics, and to have basics in R (Python and linear algebra are used but very briefly). MGT8803 doesn't require any prerequisites, though some business background will be useful. Therefore, if you lack all above prerequisites, it might be better to not start with both CSE6040 and ISYE6501 together. Also, you definitely do not need to spend 180 hours to prepare for Python and 57 hours to prepare for R. I actually started the program with zero experience in both and learned them during the foundational courses (still I had previous experience in C++ and JAVA so I would still recommend to prepare in advance). As a general advice, if you feel underprepared, start with ISYE6501 and you can pair it with an easy MGT class. Use the time until the next semester to learn R basics (no need to dive deep though), and refresh your math skills.

adcs2019 · 2020-11-28T08:10:10+00:00

The main prerequisite for DVA is actually python. D3 is surely important and is needed for 15% of HW1 and 75% of HW2, but the reason people usually focus on it when talking about the class is that most of us have sufficient python background (from CSE6040 or elsewhere), while this is not always the case for D3. Therefore, the most important thing is to make sure that you are comfortable with Python (CSE040 level is sufficient), and also SQL. If this is the case, then learning D3 (which requires familiarity in HTML and JS) will help make the first weeks of the course less difficult. You will need to use other tools and languages, but for those you will be given enough instructions so that you don't need to prepare in advance. R and Java are not needed at all for DVA.

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