This was 12 years ago though. you will not really read (not just skim) and synthesize the content in Network Science (Barabasi) book. Just because I allowed that slack doesnt mean it was a good thing to do, but it did not prevent getting a good grade (before any grades or letter grade level cut-off dropped). Otherwise, be prepared to work hard. Ill update after its over if anything changes. After discussing routing and router technologies, the course will continue with Software Defined Networking technologies and discuss topics that intersect Network Security and Computer Networks, for example, attacks on Internet routing such as BGP hijacking. So, I ended up searching elsewhere to learn then come back to read the lectures and then take the quiz. This class is appropriate for students with previous background in networking. It is really hard to score more than 70% on average. I learned less, as a result. Throughout the course, students will work on hands-on projects to learn about routing, SDN, BGP hijacking, and Internet measurements. Pros: * CS 7632: Game AI. Available from : 2020-05-06. For the motivated you could easily spend another 10+ hours a week reading papers and working on food for thought (ungraded) exercises in the lecture notes that are both very interesting and help solidify your understanding of the material. Occasionally there will be a one or two minute video example in one of the (15 - 20) slides, but some modules had none. When students asked about downloading the materials, the answer they got was I am afraid that currently we dont have a slide version of the course material. Some quiz responses were arguably incorrect. You should have a basic college algebra / calculus background as well as some familiarity with python. Work fast with our official CLI. We have to always rely on student discussions on the Piazza. Projects involve a token amount of python knowledge (use this library, transcribe this equation, make a chart, etc) but the meat of the course is mathematical graph theory. TAs have some unknown (to us) rubrics based on which they grade. Ill rate this class highly. Are you sure you want to create this branch? *CS 6795: Introduction to Cognitive Science. There was a problem preparing your codespace, please try again. The rubric definitely could have been better there. I personally wanted to just focus on what the concepts were and learn how/when to apply them, so I didnt mind. However, despite network science explicitly being an application of various fields to the study of real-world networks, the projects and quizzes feel very impractical and not useful. I didnt get 100-s on all of the assignments, but getting an average of well above 90 I would not consider difficult with effort spent, and those are the other 65% of the grade. For grades I have a low A with the last project still to be graded. The actual solution itself involves undergraduate-level probability, statistics, and linear algebra and is fairly straightforward once you get into the details. Next, the course will dive into intradomain/interdomain routing, peering and networks relationships with a follow-up into router design and functionalities. There are weekly required readings and recommended readings. The professor said, he has some cutoff in mind for A,B,C but wont disclose. I got an A without the curve and a much better A with it. But, it did not change and the professor somehow cancelled his office hours right after, saying that he didnt find the office hour to be effective. I consistently scored 10-15 points higher than I should have, under a more strict grading policy. Work fast with our official CLI. Use Git or checkout with SVN using the web URL. I proposed this as a change to the instructors (sorry, later classes). You will fail miserably in the open book quizzes. It was easier compared to my other late program courses, this was my 9th/10th (took with GA). The main text book, is called Network Science by Albert-Lszl Barabsi and is available online. They definitely make you think deeply about each question which is what you should be doing if youre in grad school. I did not study graph theory in my undergrad and I felt a bit more familiarity with it would have helped. I was really excited about this course coming in but found it pretty lacking. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Quizzes are open-everything, no time limit (other than due date). This is a math-heavy course with some scientific computing (primarily using linear algebra and some graph-specific algorithms). All with a very strong mathematical base. MSCSO at UT Austin (Master of Computer Science Online) program- anyone do it? Weekly modules are basically just reading slides, and the slide are pretty much just a summary of the reading. Can you explain the main distinction between TCP and UDP? The breadth and depth of subject matter offered in specializations such as computing systems enable our students to fine-tune their degree. I think the course is still going through some growing pains in its second semester, but the material is very interesting and there are enough challenges to keep you busy. The assignments were quite tunnel vision: compute this metric, generate a graph using this method, find communities using this method, etc. Id rather have 25 questions that reinforced the learning instead of hunting down some miniscule details for 6, then worry about wording quirks or edge cases that inevitably blow up your answer. I found the pace of the course to be pretty intense during summer because Im a try-hard. TAs were always active on Piazza. Given that this course is new I am only going to comment on how the class is structured and the material presented, not things being worked out due to a new course. I could see someone getting through with a 10-15 hour workload. They make up a third of your final grade and are the most nit-picky, tedious things I have done in this entire program. TA and professor are active on piazza. If you go into this class thinking that you will be programming these algorithms from scratch, you are mistaken. Courses. It is really hard to consume endless hours (book, exhaustive slides, papers) of text where a minor word if missed can cost of in the quiz. The TAs do not provide sample solutions. You signed in with another tab or window. Note: the below workload numbers assume you have the adequate background for a Masters in computer science, you are motivated enough to focus properly, and you dont have a learning disability. Are you sure you want to create this branch? Lectures are good but not great, some annoying ego in them like it is not hard to show that insert some math thing, which sometimes leads to making pretty big jumps in derivations that took a while to follow. Quiz questions often hinge upon a must, may, or only statement. GA Tech's OMSCS is the golden standard for online MS CS programs- so how's UT Austin's newer MSCSO?UT Austin is a comparably well-regarded school, and the price for the MSCSO is about as cheap.. "/> I completed 3 assignments, so I do have a fair idea about the class. Having taken GA concurrently with the Network Security (not IIS) classAbout github Cs6035 2019 Present) Teaching Assistant for CS 4235/6035: Introduction to Information.. . . Lec :. Most lectures are reading assignments. This was my 6th course. So we dont know yet what grades we are getting and just trying to do our best. This would make the course more challenging and bring the workload numbers up a bit, more in line with the heavy hitters in the program. I found most of the wording to be very ambiguous, I had to guess what the question was actually asking about. Numpy knowledge is beneficial. A lot of the workload for this course was in the required readings and the 14 quizzes. for isolating occasional long-running parts, to get the data, and then working separately on better plotting/analysis etc. 35% open book quizzes and 65% projects (jupyter notebook, numpy etc.). Summer 2021 semester started off pretty hectic. Looking ahead, there were quizzes due every weekend and projects every two to three weeks. Calculus, statistics, probability, linear algebra, and python are hard prerequisites for the course (you should take the prereq quiz seriously). Add to that the fact that the lower homework grade was dropped (maybe because it was the Summer term - it seemed way too generous), then I can see the point of the quizzes (35% of the grade) being hard, to push things and to help learning (which they did). Lectures were just textual summaries of the required reading with the occasional video strewn about. I consistently scored 10-15 points higher . You really need to read the papers to do better than average on the quizzes. Ill say this is very rich and interesting class. Thanks a lot for the responses, I managed to get in . Professor Dovrolis is one of the kindest people you will encounter. If so, Georgia Tech has the answer. Nothing too intense. You may learn a lot about the properties of different networks, not just computer networks, but also social networks, traffic networks, and so on. There are many pick all that are true or false that are also frustrating. Lots of reading: texts and papers. For the most up-to-date information, consult the official course documentation. I started early in the first assignment, but end up changing a lot of things before the deadline because there were so many clarifications needed in order to complete it. { { helloChapter }} Network Science. Finally, as this is the first semester that this course is offered, Id expect it to get better. In most cases, the instructor just introduces a concept in those slides and leaves bulk of the things for you to read up on our own. While this is useful for a summary, it would be helpful if presentations were extended. Online Master of Science Computer Science (OMS CS) at Georgia Tech. The notebooks have some advantages, I missed a bunch of points with no partial credit due to an equation being slightly off on a question in the 3rd assignment. Note that assignments are due roughly once every 3 weeks. 15 Hours / Week: I really like Network Science!. The math becomes harder as you get further into the subject. Congratulations! It's using a powerpoint-ish format with slides and . TAs and professor are open and respond to students, revising and amending material when necessary. In addition to all that is in the above category, you do the supplemental readings and also ponder the food for thought questions inside the lectures. This may be one of the better "easy" electives to take in the OMSCS program, but it's definitely not one of the best courses in the program. Probably one of the best for OMSCS in terms for learning, structure. Very hard to get full points. I thought it was a nice course with some advanced topics being discussed. The quiz definitely requires some deep understanding of course concepts. CS6300 Software Development Process (Software Engineering) I enjoyed trying to help out in answering questions on Piazza, and the TAs and instructor were quite supportive. Lectures: Tuesday and Thursday 12:30-13:45. The material is not difficult but the class structure keeps you involved thoroughly. Most of the course is summary for The network science book http://networksciencebook.com/. Grade is broken down as 35% quizzes and 65% projects. Generally, each quiz had 6-7 questions, some multiple choice, with one or two easy and some really hard, and like I said, almost every quiz tripped me with something. You dont really have to worry too much about the grade if you spend enough time. I was thorough and curious, I believe Im a decent Python coder but I wanted my code to be clean and sensible and efficient. CS-7280 - Network Science. * CS 7637: Knowledge-Based Artificial Intelligence - Cognitive Systems. If you dont have a good background with these you will struggle or worse miss out on a lot of the richness of the material. It usually takes some time for them to answer questions. The specialization that I would prefer given my long-term career interests is the Machine Learning specialization. This course may impose additional academic integrity stipulations; consult the official course documentation for more information. There were some occasional ambiguities in the homework as well, but I dont think there was any point of unfair grading WRT anything. Jan 15, 2021 5 Comments. Some familiarity with both network programming, scripting languages (e.g., Python), and using virtual machines will be helpful. Semester: Fall, 2021. There are pretty much no lectures. Notes from Summer 2022 OMSCS CS7280 Network Science - GitHub - fding253/OMSCS_CS7280_NetworkScience: Notes from Summer 2022 OMSCS CS7280 Network Science Some people prefer that, some dont. Some people will complain that they didnt get to implement specific things (e.g. Instead of watching videos, you read a lot of long and dry texts. I do all the required readings and take detailed notes and it takes me about 2 hours a week. The course begins with an overview of the evolution of the Internet architecture and a short refresh of the transport layer algorithms and protocols such as TCP and congestion control. You may find yourself worrying less about quizzes (which i spent hours on each week) or maybe taking less verbose notes than me (again, hours each week). This course provides a quick refresh of introductory material, and offers a broad coverage of protocols and algorithms that span across all layers of the Internet protocol stack. This course offers a pretty good introduction to basics and applications of network sciences. This was my first class where I actually logged everything I did in a google sheet and my workload is 100% accurate. This was my 8th course in the program and it felt much more like a math class than a programming one. The class is pretty well structured. This hopefully will get better and better as the semesters go on. My background: ISYE undergrad with many prob/stats and ops research courses, likely a strong background for this class. It was manageable, but not a very good learning experience. My final recommendation is to wait and not enroll in this course until they create videos for the whole material. The videos cover only less than 5% of the total material and the remaining 95% is just reading and didnt really contribute to my understanding. My average for quizzes was about 75%, which was above the mean. There is a good deal of reading material for each weekly chapter; however, I did not note that any of the quizzes were from the readings. There are nice piazza threads for each sub question in the hw that usually clear things up well. A tag already exists with the provided branch name. The lessons are pretty thorough, and mirror the material in the textbooks, both of which are free. CS 7470: Mobile & Ubiquitous Computing. The 5 projects were generally doable in a couple of days, though I personally found stretching them out over a week or so allowed the material to sink in better. Prof Dovrolis will probably one of the kindest people youll ever interact with during the course of this program. They felt pedantic and definitely contributed to my feeling that I wasnt focused on the valuable takeaways from the content. The small class size is an added bonus. Do you understand the three way handshake of TCP? Seeing that 7280 Network Science is still quite a new course I've been skeptical of keeping that for this fall. Instructor: Constantine Dovrolis. This is our group presentation for the paper of the "Collective patterns of diffusion are shaped by Individual inertia and trend-seeking" in the class of Intorduction to Network Science, which is the first undergraduate course about Complex_Net in SHU. I got an A with the curve (2 quizzes dropped, 1 assignment dropped from grading). The degree requires completion of 30 units, and each course is 3 units. My 6th course into the OMSCS. Search: Omscs Course Notes.Deep Learning We now begin our study of deep learning.In this set of notes, we give an overview of neural networks, discuss vectorization and discuss training neural networks with backpropagation. OMSCS Reviews . Some knowledge of statistical tests can be helpful. These cases were fairly rare, but there was evidence that a course in its second semester is still growing. Network security, we will first review vulnerabilities of network protocols such as spoofing and standard prevention mechanisms such as TLS. For students who would like to explore more, there is an additional project that engages with tools for Internet-wide measurements. The course is not inclusive of attendees who come from computing system background because lectures presume a lot. So far project grading is slow. (Im terrible about estimating my time, but I did try to count this last week so that I could give an accurate estimate). This course counts towards the following specialization(s): Georgia Institute of TechnologyNorth Avenue, Atlanta, GA 30332Phone: 404-894-2000, Application Deadlines, Process and Requirements. I actually ended up watching a ton of youtube videos on related concepts and reading a lot of material online in addition to the required readings. NOC:Deep Learning for Computer Vision (Video) Syllabus. You may also be able to get by if you dont have the urge to dig deeper and really understand the material. Overall, I find the course material fascinating, but Im also taking another class which is much more demanding of my time than expected, so I find myself not spending any extra time engaging with this material, which is a shame because its so much more interesting to me than my other course. Then you go through the slides yourself. Projects are interesting and cover the use of NetworkX library in Python. I ended up not watching them because the professor just read off the page, and the content wasn't useful . The class tries to cover a lot of fundamental topics, so unfortunately there isnt a lot of depth. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. In one instance, I wrote a recursive function to find network motifs but made a very stupid error which resulted in massive double counting. You have to scroll them page by page on canvas which is really annoying. Neither did I go deep into any of the papers (saved them for later). Each lecture is not just a slide ( as mentioned in some reviews) but a full topic in itself. I did not have enough time in the course to say anything about the professor. Work fast with our official CLI. It covers a huge variety of terrain in the field, which is new. Instead of saying this is a CS course, it's more like English reading course. You get a min. Speaking of the quizzes, they are open everything with no time limit, but really really tricky. Cognitive Psychology. The wordings of the assignments are not clarified well. * CS 7210: Distributed Computing. Linear algebra was one of the courses I was able to score a 100 on in an exam. No test case / feedback on projects, leads to uncertainty, although Piazza is used extensively to clarify questions. Cons: The course mentions no prerequisite, but I think it definitely needs know-how of statistics and machine learning. I thoroughly enjoyed the subject, and am very interested in learning more. You need to consider that the quizzes are open, un-timed, there are no other exams of any sort, two lower grades were dropped and the grade cut-offs, at least as described by the professor, were several points below the usual 90/80/etc cut-offs. M1 chips are incompatible with our core course VM where most project development occurs. CS 6747: Advanced Malware Analysis C. * CS 6750: Human-Computer Interaction. I hated the quizzes. So there is no use of starting the assignments early. Jupyter notebooks are not everyones cup of tea, so I just did and debugged the assignment parts in Pycharm and then moved to the notebook. There was a problem preparing your codespace, please try again. average class score on quiz is around 70-75%. ML is integral in modern network science and including a project that utilizes it would be an exciting addition to the course. Quizzes were very frustrated. Quizzes arent a walk in the park but definitely not unfair and require you think about the material. This course provides a theoretical base for several things we see in the world around us. The lectures and main text book very obvious written by someone who hasnt had a rigorous math or engineering background, lack of consistency or concise statements is frustrating. Overall networks are a fascinating field, this class did a good job on introducing the theory, but fell short on providing more critical thinking and prescriptive analysis type projects. The staff is comprised of the professor along with an army of TAs, who hold regular office hours and are active on the forums. The lectures are shallow, fast paced, incomplete, and often a waste of time. It just felt like I didnt actually get to focus on learning the network science part. In summary, my experience with the course was not pleasant. At least the theory is rigorous, and I learned how to use networkx well though so that is a plus. There are also knowledge checks which are just ungraded practice quizzes, but they are not necessarily predictive of what will be on graded quizzes, so I dont always do them. The projects take a decent amount of time to work through but if you start early they are certainly manageable. Are you sure you want to create this branch? This degree, ranked 8th in the country for Computer Science, is the best deal in graduate education (at least in the United States) coming in under $7,000. We had two quizzes due on the first weekend and project 1 due on the next Wednesday. Dr. D is awesome. Browser and connection speed: An up-to-date version of Chrome or Firefox is strongly recommended. Choices are sometimes not clear. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. That being said, you dont need to wrestle with the math if you dont want to. Phew! Projects very related to the topics taught and will take 10 - 15 hrs each on average. Factoid hunt that can depend on the quality of the material presented. Learn more. My main gripe are the weekly quizzes. Computer Science Projects. If nothing happens, download Xcode and try again. All in python and require you to play with given dataset using existing libraries ( average class score is 85-89%). I started to go through and individually highlight every sentence as I completed a requirement after missing a couple dumb things early. Programming assignments are non-trivial, and the majority of the workload. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Id love to study NS in more depth. So I just know where I lost points, but do not know how to correct them. Unless you are very comfortable with everything that it covers you are going to suffer. The downside is that it becomes a survey course and you might find it hard to imagine how to apply the topics you learnt. This is a synchronous course (the lectures of future modules are locked so you cant work ahead), but you can still cover the subject matter by studying ahead using the online network science book. Then once you settle in its about 2-3 hours for the lecture material, .5-1.5 hr for the quiz, and 12-15 hrs per assignment. This is a fairly new branch of computer science and already has a great deal of practical application. Get your pencil and paper out to go step by step if needs be, or verify by coding up in networkx. Think of it as a game to find the catch or statement that is untrue. TAs were an amazing team with all continuously being active on the piazza. Grades are split between weekly quizzes and 5 projects. First, to be honest I was horribly under prepared. * CS 7638: Artificial . If nothing happens, download Xcode and try again. Note: Sample syllabi are provided for informational purposes only. MachineLearning-Coursera-Certificate: Certificate of accomplishment from the Coursera Machine Learning (ML) course conducted by Dr. Andrew Ng. It is hard not to appreciate how important network science is in the modern world of social networks and pandemic networks, and the subject matter alone makes this course worth taking. Consists of only quizzes and projects. All in all I would say if youre planning on taking this course you should pay very close attention to the introductory quiz that the professor offers as a way to test your preparedness.
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network science omscs github