TAs are trying their best to be helpful with their delightful sense of humor. No complaints here really. Instead of acknowledging the mistakes and thanking students for pointing them out, they would get defensive and write things like that will also be accepted because we didnt specify how to do X. for more information on how to effectively manage your git repository and troubleshooting information. This was due to a few key factors: We still used the older, 3rd edition of the book. Overall I felt that this course was challenging in a way that actually tested what you were supposed to learn in the course. I would rate it somewhere between medium and hard, so I rounded up to hard. If you get 100 on 4 of 5 of the assignments, it shouldnt be too hard to get an A, as youll only need about 70% on the final exam to do so. There are those working on Ph.Ds in engineering, full-time students in the day program masters, and even professional data scientists taking this class. Project 6 - Hidden Markov Models and Viterbi Algorithm - kind of cool, but the first part is tricky. But like any exam getting a 60 is much easier than getting an 80 is much easier than scoring 90+: assignments and bonuses will help you edge out with a victory even with an imperfect score. The course content is organized and prepared well. This course could have easily been broken into at least 2 parts, one probabilistic (Bayes nets, decision trees, others) and one deterministic (A*, constraint programming, adversarial search etc). I found that they were generous in answering private clarification questions, even if those clarifications werent shared in the public clarification post. For example, for assignment-1, bonnie was running every submission for more than 2 hours and failing for everyone and no one paid any attention until last day of submission. Project 3: YOU CANNOT LEARN EVERYTHING YOU NEED FOR THE PROJECT IN THE GIVEN TIME. I struggled the most with the third lab and this is where I understood why this class is considered hard. At the end of the warm-up, you solve more difficult problems by implementing solutions that had not been explicitly covered in class. This course would be best to take not as a first course, but its high-level enough that I wouldnt push it off until the end either. most of the time i made a small mistake that would pass local tests but fail the submission and had no observability. Even though im only through 3 projects and havent done the mid-term yet I wanted to give my review for those considering the class for Summer or Fall especially after seeing some reviews that I felt were a bit dramatic. Post author: Post published: November 4, 2022; Post category: university of south carolina research studies; Post comments: . Reddit and its partners use cookies and similar technologies to provide you with a better experience. It is a very hard class, but the grading is generous this semester (perhaps because its the first offering). A bit of a rough start with the first project due to it not being quite prepared, but following some backlash from students on how that was unacceptable, it seems the course really got a lot better and the teaching staff took the advice to heart. But its very hard with back to back projects that require you to start the work on day 1 to get full credit. As a previous message said, if you have background in machine learning, you will already know a quarter of this course. This led to some brute-force/blind debugging in some cases, which was a little frustrating. Do all the extra credit. I liked this course for the content. I realize that TAs have their own projects which take their time but when a student takes time to ask a well thought out question, replies from TAs like yes and no dont really cut it. Get access to all 6 pages and additional benefits: read this selection then answer the following questions Earth: There's No Life Like It by Terence Dickinson 1 Does the universe harbour other planets like Earth? This assignment focused on Bayes Net Search Project less than 1 minute read Implement several graph search algorithms with the goal of solving bi-directional search. There was one where they just linked a YouTube video and told you to follow it. There are 6 homeworks, one grade gets dropped. Radiance, Aura World's Biggest Crossword, If you cant, thats ok too and next item will help. Its the classic joke where the teacher says 1+1=2 in the lecture, and then the assignment is 2+2= calculate the mass of the sun. {2} All of the Assignments (including exams) could be hacked (solved by brute force or other techniques with only superficial understanding of algorithms) for ~100%, if you know what to look at. This is horrible when you have less than two weeks to work on the assignments and you need a clarification. If you attempt and get through all of the assignments, you will feel amazing about the course. Every Assignment is manageable, exams could be done in one week, even in one weekend, you dont have to read the whole 1000 page book, normal amount of hair lost and no PTSD, unit tests are usually not such a big problem, 90% is a guaranteed A as usual. After taking two courses as a full-time student, I do not recommend another course at the same time if you work full-time unless you have expertise in python, numpy, and AI concepts. This is somewhat solved by an offline testing suite but it is often limited to the most basic things. Its basically a series of quizzes that assumes you already know it. Quite tedious if you ask me. We would like to show you a description here but the site won't allow us. flutter webview source code. HOUSE State 1 State 2 State 3 I think Dr. Starner said that they had listened to feedback from past students saying the exams were too long, and this semester they cut them down to be more realistic, and I think that they were. The only thing Id do differently looking back: I wish Id spent more time reading the textbook (instead of watching lectures) since its very well written and much more comprehensive. Added notebook and changed tests 0.3456 rounds to 0.346 A surprisingly difficult assignment for such a short algorithm. Create notebooks and keep track of their status here. There are also research opportunities you can apply to at the end of the semester. The greyed out nodes can be ignored to still reach an optimal minimax strategy. Most of the coding assignment is not really CS coding I would say. Thus, when the opportunity came to implement decision trees from scratch using only Numpy, I relished it. I didnt fully understand every part after watching the videos. Then when we got the answers there were more mistakes in them and the exam was re-graded for everyone to account for that. The class definitely has the feeling of being more interested in making money than teaching students. I think anyone taking this course will learn alot and is well worthwhile. Many of the assignments have instructions that leave a lot to be desired; as someone else mentioned these instructions may only include a link to some research paper, or a wikipedia article. Moreover, the TAs were probably understaffed as they were not very responsive. Im sorry you feel lost, but you should not drag down other prospective students because you havent utilized the resources available to you (TA office hours, Piazza forums where you can freely interact with students short of violating the cheating policies, the textbook, 1-on-1 messaging with the TAs, etc.). I front-load most of the video lectures prior to the start of semester which helps me to save some time, There is not much discussion in Piazza. I did and I think its a good investment as it is a great book and i definitely see myself coming back to it in the future to brush up on concepts i am trying to implement or discuss. There was a separate plagiarism quiz that had a weightage of 5%. The projects were error-laden, and the staff participation on Piazza was below-average; however, office hours and instructor participation in the class were much better than other classes. This search is often optimized based on domain-specific heuristics, such as the Minimum Remaining Value heuristic, which chooses the variable with the least possible values given the current configuration. The autograder (i. e., Bonnie) used to grade assignments would get overloaded the weekend that assignments were due and cause all kinds of reliability problems. I guess the takeaway from my word vomit is that this class has a lot of inconsistencies. . It is a mere elective, and does not count toward the ML specialty and overlaps with ML4T and ML. I agree with another review that Id happily take this course repeatedly to really dig into the material. This class was good to gain breadth knowledge and exposure to AI topics and get the hands dirty in the implementation of some classic algorithms, however, it didnt ignite any passion in me to pursue these topics further, so bring your motivation from home. You will be implementing. I do have a full time job and a family. An interesting application, for which we had to solve a mini-version of, is multiprocessor scheduling. This class is rough. It cover most of the algorithms, though it is harder to grasp. class 11 education notes. From that point on, the players, alternate turns moving both the pieces like a Queen in chess (any number of open squares vertically, horizontally, or, diagonally). Additionally, I can assure you that no one who knows me would consider me any where near a genius. These projects weed a lot of people out of the class. Let's address some problems of k-means: what if some of the clusters are overlapping? . Both Midterm and Final are a 30-50 pages PDF with open questions/exercises to do at home in a week. The lectures were meh. game playing agents for a variant of the game Isolation. As for workload, is quite heavy, so start the assignments as soon as they are released or even earlier, and assume that your weekends are going to be busy for the entire semester. The first 2 assignments are extremely time consuming, and the midterm and final exams are beasts. The next four assignments required more math and stats and less coding, but conceptually very challenging. The assignment medians are also very high. I mostly did not read the textbook and instead relied on the lectures. They are take-home exams, you have a week, and you can use materials from the class. Office hours are mostly useless, I did not watch any of them. The book is a classic and consider this course an aid to navigate through the book and discover/get exposed to fundamental AI techniques. The rest of the assignments I found to be about the same level of difficulty with varying amounts of code. part_2_a() Part 2b: Improving the Viterbi Trellis [39 Points] I was genuinely excited to take this class, having heard that a lot of people loved it. they dont actually care, or want to help, and why would they? Content-wise, the course is basically a survey of some basic AI and ML algorithms, you may actually have heard of implemented some of them in other classes, but still, it gives you an wholistic view of whats in your toolbox, and sometimes they framed it in a way that uses different algorithms to solve the same problem. This course will give you the best overview of the field. Its meant as a proxy to trade secrets in industry, but its nonsensical, especially given the poor resources of the class lectures. It means you will have to spend the proper time to take on the workload, but you wont get absolutely lost while doing it. I didnt take any time off work as some others mentioned, but it was absolutely among the busiest weeks Ive had in OMSCS. Assignments are super interesting and intense I spend almost over 20 hours on each assignment, but they are really helping me understand the materials. HOUSE State 1 State 2 State 3 The hardest part of the course is that the assignment might fully occupy your free time and therefore you never find time to read the book; by reading early you are going to do your future self a huge favor. Hidden markov models (13 hours) - Relatively straightforward. Please check the official documentation for more information. Assignment 1 was a bit of a pain, and it was kind of just luck in getting hyperparameters right to beat the RNG auto-grader. Now, A and B are conditionally independent. Sometimes its a really quick True/False quiz. Even with this small issues I have really enjoyed this course. The algorithm we use is incredibly clear and straight forward. The difficult material is front-loaded through the midterm. Have fun! I had my doubts, and I had an engineering degree, I work in data science field, and thought I could hack it. Wikipedia pages, YouTube videos these poorly-curated resources account for a significant proportion of the assignment difficulty. 47, 39, 32 34, 36, 42 42, 42, 34, 25 Really well structured class with clear goals and deadlines for each week. That is not the case for this class. The Assignment Classification is used widely in machine learning to figure out how to sort new data that comes through. Modify the Viterbi trellis function to allow multiple observed values (Y location of right and left hands) for a state. The White Knight by Eric Nichol Once upon a time, How you can implement priority queue class in python, for CS6601 assignment on search? Assignments: There were 6 assignments with the grade composed of your 5 highest homework grades. The 4th is definitely a more relevant edition. The clarifications thread was longer that Rapunzels hair. My advice: If you want to take this course, definitely go for it! Advanced Python recommended. The TAs create a separate thread for exam clarification with a lot of points and sub-points which makes it difficult to discover and find if there were any changes. and our As for topics, midterm topics were straight from the lectures. Hated the exams. Try to get a study group for exam prep, we did this for the final and i learnt some stuff i probably would not have otherwise. This branch is up to date with ace0fsp8z/CS6601:master. They both felt like problem sets aimed at helping your understanding on the topics. View So for the subject matters, this course gets a 5 from me. It is hard to get partial credit as the final answer is what counts. Problem 1 (Random Walk on the hypercube) The hypercube is the graph with vertex set V = {0, 1}" (Le: all nuples of zeros and ones.) 35, 35, 43, 46, 52, 52, 56, 49, 45 Very little of guideline on the projects, you need to do a lot ( I mean a lot ) external research to be able to figure out what going on. You need to be able to reason from first principles; dont expect a nice stackover flow post to help you get thru it. The midterm was 30-something pages. I am glad i took this course. Menards 3 Tier Fountain, I'm trying to get ahead of this class since it'll be tight during the summer semester but I've already spent 25 hours on assignment 1 and literally can't get the first function working. books was good (as much as i could keep up with reading it) but also there were a lot of resources online to help, TAs were great help during office hours and on piazza, love coding in python and this was all in python. Even though some of them are shallow, you do get deeper knowledge on the topics used for assignments, e.g. Viterbi algorithm - Wikipedia.pdf Genetic algorithms are a global optimization technique, best known as a method to solve NP-Hard problems like the travelling salesman problem. 10 So you can spend more time learning than dealing with people. HOUSE 16 With this condition, we can guarantee that any more connected paths will be more expensive than the existing one. There are 6 projects in total ( will drop the lowest one ). November 3, 2022; Posted by: Good at recursive algorithms? NOPE. Really, theres more than enough content in this class to fill a semester. That square can not be used for, the remainder of the game. I think the format is great and I actually learned lots of things during the exam. The other projects were not as bad but that is relative. I had taken KBAI the summer before which had given me some good experience in Python and some Numpy. 36, 44 Of the 8 courses Ive taken in the program, this was either my first or second favorite. Now, A and B are conditionally independent. Requires python programming. Although each course Ive taken in OMSCS (Im about to graduate) has provided a learning experience in different ways, this one was one of the best. I didnt get to do all of them due to life stuff, but I had a lot of fun with the couple I did work through. If no sequence can be found, the algorithm should return one of the following tuples: (None, 0) (null), (, 0) (empty Course Hero uses AI to attempt to automatically extract content from documents to surface to you and others so you can study better, e.g., in search results, to enrich docs, and more. tiles hop: magic tiles / are canals in venice salt water / are canals in venice salt water Even if it was briefly covered in the lecture/book, it will be there on the exam. It also helps to take an undergrad level AI class, but is not strictly required. Be prepared to make sure your job isnt going to have any overnight emergencies or anything. However, with enough effort, it is more straightforward to achieve full marks with these (but dont start too late!). The final was similar to the midterm in format but even more challenging and comprehensive. I do not think that is the case here. This course will not teach you those techniques - you need to know them. I am comfortable with Python & NumPy after taking CS6475: Computational Photography the previous semester. I found this to be a much better approach to exams. Gradescope: Similar to what a number of other posts have covered. observations. Covering Lawn With Plastic, Theres also plenty of extra credit to make up for poor exam grades. My favorite editor is, Relatively straightforward Midterm & Final Exams, make sure you do your best for assignments (1 out of 6 can be dropped), attempt the bonuses and collect as many points as you can from them. The exams are open book, but are brutal. So much content is covered, it felt a bit rushed. Youll make it! Spring 2022 syllabus The environment of the class is, hostile. Assignment 5 was skipped for the summer session. There were complaints about absence of TAs, so Id suggest them hold daily mentoring sessions instead of just 3 times a week for summer terms (perhaps less frequent for spring/fall since its less intense). 77 Many of the polls stated people spent well over 20 hours on the midterm. I learnt most about HMMs , Random Forest , Search algorithm only because of the assignments. Failed to load latest commit information. Excellent course design and good tutorial management! Advice: This class is a beast, but its enjoyable. It was an open-book take home exam that covered all the modules. Lone-r Pianist Moonlight Sonata, If you plan to take this course, bare in mind that it will require you to keep a rigorous schedule for studying, which must also be flexible enough to postpone other priorities to allow for more study time. Dont believe me? don't have to use gaussian_prob this time, but the return format should be identical to Part 1b. If one has less programming background, consider preparing by learning Python/Numpy, a bit of search algorithms and probability before starting the course. Here is my advice: Prepare for heavy self-learning. assignment_2. I am sure all of that is going on. If we use an admissible heuristic, we are guaranteed to find an optimal solution. requirements.txt The course is pretty loaded (especially if you are working fulltime). If not, are you comfortable in learning a language within the first week of class? Assignment 4 was the easiest for me. The mid term is 15%, final is 20%, and projects are most of the other 65%. Pros: I preferred the lectures taught by the professor (vs the ones taught by the guest lecturers). Its because they are just reading off a teleprompter. Sometimes it is trying to optimize code from the assignment to perform even better (sometimes competitively against other classmates). I dont have a CS undergrad so I was probably slower than the average student in terms of figuring out the assignments. README.md This is my 7th course in the program, and I work full-time. The first project (search) is the most demanding that I have witnessed so far in the entire program. I withdrew mid assignment 2. For most of the assignments, there is limited number of submissions and provided local tests are not adequate. As the course advertises in its description, it is intended for those who have some background in AI or are ready to jump into the deep end (true statement) The description asks for 9 hrs per week and it should be modified to reflect the true effort required in this class. Students are passing this course without basic understanding of the concepts. I would recommend reviewing linear algebra a bit before jumping in, and a statistics background would be helpful; I did fine (A in the course) without a strong background in either, but I felt that several of the assignments would have been much easier and taken less time if I wasnt also trying to learn the basic math at the same time. The rest of the class followed similar themes. Not surprised they disliked the course. So, prepare before the semester begins; you will see the course lecture when the semester begins but for early preparation go through: Now when you see the course material, it wont be first time. So my advice is just not to worry so much about the score but rather, enjoy and focus on the knowledge you will gain from this great course. There is a free one online but you can also buy it. assignment_3. It can be true if you do not have a good understanding of foundational topics in algebra and statistics. Therere 6 programming assignments about each every 2 weeks, plus two exams each takes one week to finish. For example, when Gradescope went down the night of one assignments deadline, no clear answer was given to the many students, including myself, who were trying to submit. Oh and the exams (mid-term and final) were take home. The flipside here is that if you are taking this as a first course, with no experience in AI, and you want to get the max out of it, youll have a daunting journey ahead of you. If youre looking to take two classes and have taken ML4T and AI4R already, it is 100% doable as long as you find a way to manage your time on exam weeks. Very comprehensive coverage of traditional AI techniques, so it sort of lacks a coherent thread through the course (just a lot of material to cover). You are allowed to drop your worst grade, so if it's minimax, there you go. It was very frustrating when on Day 2 of an assignment, some students asked questions about the labs final section, and I knew I was about ten days behind them. There are plenty of comments about the projects; theyre all hard, but the first 2 you will fight with a lot more than the others. Course Hero is not sponsored or endorsed by any college or university. Better yet, do it both ways to check yourself. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. Initial They dont do a good job explaining subsequent assignments, and much of my time was wasted trying to figure out the assignment instead of understanding the lectures and reading the book. At last, dont waste your time attending office hours. This is not a learn how to code class, you need to come in with strong fundamentals. Out of 6 assignments, only the top 5 scores are used. {6} TAs and instructor are present and very active on Piazza. There was a lot of self-learning, and learning from peers and TAs on both the Slack channel and Piazza. Now here is the other problem. The assignments were very front loaded with the first two assignments being the most interesting and time consuming while the later assignments took less time but were not as interesting.
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