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Gregory Bush

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  • 9 reviews
  • 7 completed
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This class has been a disappointment so far. I was hoping we would get some interesting information about origins of life, but it looks like the entire OOL content of the course is about 5 minutes of vague, grade-school level explanation with no supporting evidence. You'd learn a hundred times more just from reading Wikipedia for a bit, which is sad. Worse, the initial lectures are full of factual errors and the quizzes are the worst I've seen on Coursera in terms of grading errors and ambiguous questions. The course seems to have been created to glorify Carl Woese and get him name recognition, and it verges on propaganda. It's interesting that he developed a phylogenetic technique and discovered Archaea, but statements like "before Woese, Biology wasn't even a science" seem ridiculous. The lectures do get better as the course progresses, but it wasn't really what I was looking for.
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The events of 9/11 have had a major impact on today's world. This class explores the fundamentals of modern terrorism and counterterrorism in order to give a deeper context to help understand 9/11. (Part II will explore the response to 9/11, including the wars in Afghanistan and Iraq, drone strikes, changes in law like the USA PATRIOT act and more.) It's a challenging subject, since it is still deeply emotional to many people around the world, and most of us simply don't have enough world perspective to understand things like religious extremist violence in context. The class attempts to address that by covering the details of 9/11, the difficulty of defining terrorism, the basic principles of Islam, the ideology of al-Qai'da, how people can be transformed from peaceful citizens to terrorists and how counterterrorism has changed as a result of 9/11. The lectures and student discussions are good, but the real stars are the reading material and the Google hangouts. Prof. Schanzer guides you through exploring primary source material like bin Laden's "Messages to the World" and Sayyid Qutb's "Milestones," and original research like Marc Sageman's "Leaderless Jihad" and Martin Miller's "The Foundations of Modern Terrorism." Amazingly, he has also made it possible for students to question experts like Peter Bergen who has interviewed bin Laden, Jessica Stern who has interviewed mujahideen and other religious extremists, as well as Imam Abdullah Antepli, historian Martin Miller and 9/11 memorial museum director Jan Ramirez. This class may be disappointing if you're looking for exploration of alternative theories about 9/11 like how it was a hoax carried out by the CIA or Mossad agents, etc. Analyzing these conspiracy theories and the groups promoting them could potentially make an interesting class in itself, but it is not addressed here. If your background is anything like mine, I think you'll find a large amount of new and interesting material here that can deepen your understanding of this important event and broaden your perspective on today's world.
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I'll try to be brief, since others have talked in detail about the course in their reviews. But in short, if you have some prior calculus experience and you're looking for a refresher or to go a bit further, TAKE THIS CLASS! There is no other calculus class like it, and there probably never will be. It is as unique and fascinating as Prof Ghrist himself seems to be. Even if you've got a good math background, I think you're sure to find some material you've never seen before hiding somewhere in this course material. And the lectures are worth auditing just to admire the wildly colored animations and humorous references to nerd culture. Check it out!
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This class is based on a deep principle: the structure of your data determines the structure of your program (at least at the lowest level). This insight allows you to think more systematically and understand what code you will need to write before you start writing it: what a function does, what data types it should consume and produce, test cases to verify it works correctly and a structural template that defines the skeleton of the function -- all before you write any code. The course teaches these principles using a small subset of the Racket language called Beginning Student Language (and Intermediate Student Language in later assignments). Due to this and the emphasis on recursion, this class would make a good prerequisite course before taking something like Dan Grossman's "Programming Languages" or Martin Odersky's "Functional Programming Principles in Scala." On a minor critical note, the pacing of the first offering of the course felt awkward to me at times. For example, the first weeks are deceptively easy and can make the design method seem very pointless and tedious. By the time you get to a topic like mutual recursion, it's obvious that the design recipes are much more interesting and valuable, but some students may not have had the patience to reach that point and others that found the first weeks about right may feel totally overwhelmed. If you do have the patience to make it through the course (to either slog through the slower material or stick with the tougher bits), I think you'll find it rewarding. Overall, this is a great addition to Coursera's computer science landscape, which I think will continue to improve with further iterations. It's worth checking out if you are a new programmer who would like to start off with a good feeling for how programs are structured instead of just how they are written in a particular popular language or if you're more experienced and want to get a gentle introduction to some deeper concepts beyond the syntax of your favorite language.
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If you're interested in programming but are worried because it seems complicated, this may be the class for you.  Dr. Chuck's there to walk you through the process and let you know that it's going to be ok even if you don't understand everything at first. The forums are very friendly and helpful (at least this session).  If you're stuck on an assignment, it's fine to post your malfunctioning code and get some suggestions how you might fix it to complete the assignment. If you are a more experienced programmer but you'd like some motivation to get more familiar with Python, this is a good class too.  You might skim the lectures a bit and wish there were a few more assignments to work on, but you'll learn the basics.  This class is not primarily for you, but it won't take much of your time and you'll probably get something out of it. I give this course 5 stars because it is the friendliest introduction to programming I've seen.
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This course is an introduction to the Simplex method of solving linear programming problems and methods of extending Simplex to solve integer programming problems using branch-and-bound and Gomory cuts. An interior point method for solving LPs is demonstrated in the optional material at the end of the class. The material is clearly explained with many examples, focusing on calculations over theory. Various programming assignments throughout the class culminate in building a simple ILP solver in the language of your choice. Several applications including de-noising and building a Sudoku solver are also covered. The level of instructor involvement on the forums was the highest I've seen in any Coursera class. Practically every student's question was quickly answered by one of the professors. Overall, this is a very practical introduction to LP and ILP.
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This is a challenging but rewarding class that provides an overview of quantum mechanical concepts with a focus on simplified "spherical cow" models of leading edge research topics in solid state physics. Even though it does cover the basics, I would not consider it an introductory quantum physics course. The pace is just too fast. That being said, the lectures are rated by difficulty and the class is set up with the intent that people with less physics / math background can still learn something and have a shot at passing the course even if some lectures are too much. There are three lecturers for the course: Prof Victor Galitsky focuses on the basics of the Schrodinger and Feynman path integral formulations as well as the fascinating topics of superconductivity and phonons. His presentations are very focused and consist mostly of clear but fast mathematical derivations. Hopefully your calculus is up to par! Prof Charles Clark introduces atomic spectra and the theory of angular momentum and spin in quantum mechanics necessary to explain much of the hydrogen atom's dynamics. His presentation is often more conceptual and broad, with more focus on the history of quantum mechanics, but don't relax too much. Once he gets going, the material is at least as tough as Victor's. Prof Ian Applebaum gives a guest lecture focusing on electron spin and his research on spintronics. These lectures made it clear once again why I was not a physics major. I would have to use the pause button extensively to keep up with his pace, and with no prior knowledge of spintronics, I found the description of his research to be nearly incomprehensible. As an amateur who has done a fair amount of self-study on quantum mechanics up to a little quantum field theory but who is not at the level of a physics post-grad, I was capable of passing the course with distinction, but it was challenging. I am sure I could re-take the course several more times and learn more every time. I give this class high marks for the following reasons: * It is quantum physics. Coursera needs more quantum physics and every bit at every level is welcome. * It is a relatively advanced presentation. Not every free online course need be at the lowest introductory level, so it's nice to see some more intermediate level ones out there. (Although given that over 20,000 students signed up for the first session, there is clearly a need for a real introductory QM class out there.) * The incorporation of current research topics at a level that is simplified enough to understand in a single lecture, but not purely qualitative. * The instructors, especially Dr. Clark, were very active in discussions on the forum. This is a class from guys who clearly love the subject and love sharing it with the world. It starts up again in October, so you have the chance to check it out if it sounds interesting!
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This class is full of good information and has a lot of potential to be even better. The lecture component in particular is very good. Prof Kutz is excellent at quickly and clearly explaining concepts and tries hard to be entertaining (often successfully!). The major weaknesses of the class are the frequent errata in the programming assignment graders and a complete absence of any staff attention. The assignment errata are particularly frustrating because your program gets three attempts at a pass/fail evaluation based on a single numeric output, accurate to, for example, 5 decimal places. If you get a "fail", then you have very little information to go on. Is there a subtle error in your program, or was the answer key created using bad rounding, etc.? It is frequently enough the latter to where you are never quite sure where the problem lies. Fortunately, generations of prior students have catalogued most of the errata on the wiki, which is a fantastic help once you discover it. But it's unfortunate that these errors have persisted so long and that the course seems to be running on autopilot, with the staff oblivious to issues that could have been fixed by now. The University of Washington does advertise a paid version of the same class where you have access to course staff, additional materials and some form of certification for completing the course, but given the current state of the free version, I'm skeptical that it would be worth spending the money on. Regardless, I'm grateful that the class exists and think it's worth signing up for if you want to learn the material. Just be prepared for some frustration!
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This was one of the most fun and most challenging classes I've taken in any format. There are other classes that cover aspects of DO like linear and integer programming and deeply delve into the theory of how and why these techniques work. But it is much harder to find a class that discusses local search heuristics, and this class may be unique in its focus on actually solving very tough examples of classic DO problems "by any means necessary." The difficulty of the hardest problems combined with the smorgasbord of usable techniques and the open collaboration policy on the forums makes it feel almost like you are part of a research team instead of a student doing coursework. And in some sense you are, since not all of the best known solutions for these problems have been proved optimal and areas like the vehicle routing problem continue to be very actively researched. Considering the entire complexity class of these NP-Complete problems is not deeply understood, this should perhaps not be too surprising. Combining this collaborative "research" aspect of the course with the competition aspect of the leaderboards yields a really memorable experience. It is also a class that can scale to the level of effort you're willing to throw at it. For example, graduating with a certificate is a significant accomplishment, but should be manageable for most people with enough programming background to be comfortable implementing algorithms from informal descriptions. Getting distinction is significantly more difficult and time consuming and will often require many iterations of work improving your first solutions. And if you really aspire to produce the best solution on the leaderboard for the toughest problems, prepare for a lot of sleepless nights! Whatever level you want to approach the class at, I think you are sure to learn something!