We can consider that algorithmic thinking is an important aspect of computational thinking. Receive weekly news about MOOC and online learning ressources. This is an outstanding and engaging course. The slides provide all the information that is needed. So many interesting things to think about, thoughtfully explained by brilliant instructors. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. I highly recommend it to anyone who wants to learn data structures and algorithms thoroughly. Please have a basic of Python to finish the course as per deadlines. If you take a course in audit mode, you will be able to see most course materials for free. �p�7�=N>ݐ�.U!n��u���tu��I�GBS���R]�$b,�3/4uP�rJZ台��8J�0��bE��,a�\. I loved this course! Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. Mathematics can be really simple when they are directly related to real world concepts and problems. It was really a great and fun experience. This is, to my knowledge, the only Discrete Math course on Coursera or EdX, so it's important that it gets an honest review. The python bits needed more explanation and direction in my opinion. Make sure that you have basic knowledge of Python before taking this course. One more reason to recommend this course is that apart from learning material it has many puzzles which are really interesting. We will use these tools to answer typical programming questions like: How can we be certain a solution exists? One of the quizzes (the one on Induction) was difficult to understand, contained material that was not explained at all in the preceding videos, and the explanations in the feedback did nothing to illuminate what was going on. We assume only basic math (e.g., we expect you to know what is a square or how to add fractions), common sense and curiosity. 0000002774 00000 n The mathematical thinking process is the explanation and collaboration of mathematics through problem-solving, reasoning and proof, communication, connections, and … In particular, you will see them frequently in algorithms â for analysing correctness and running time of algorithms as well as for implementing efficient solutions. Thank you so much. Still, for those of you who are at that level is worth taking this specialization. It was of great delight to find that this course is integral in making the Data Structure and Algorithm Specialization easier to learn. Am I sure my program computes the optimal answer? 0000001754 00000 n You may not think this will get in the way too much of your learning, but it does. MATHEMATICAL THINKING IS AN IMPORTANT GOAL OF SCHOOLING The ability to think mathematically and to use mathematical thinking to solve problems is an important goal of schooling. 0000001089 00000 n Construction Engineering and Management Certificate, Machine Learning for Analytics Certificate, Innovation Management & Entrepreneurship Certificate, Sustainabaility and Development Certificate, Spatial Data Analysis and Visualization Certificate, Master's of Innovation & Entrepreneurship. This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. This course helped me develop an intuition for discrete mathematics. We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. Have to un-enroll. Quite chaotic and disarranged course (in both complexity and structure) although contains interesting topics. Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. I got a new perspective of seeing problems and approaching them in a new way. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. In this course, we will learn the most important tools used in discrete mathematics: induction, recursion, logic, invariants, examples, optimality. Access to lectures and assignments depends on your type of enrollment. They just read off a script, and they lose you along the way. startxref Love the quality of thought that goes into each lesson. The puzzles really get you thinking. Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. We will use these tools to answer typical programming questions like: How can we be certain a solution exists? 0 Math is one of the few subjects where students analyze their own work in this way. Topics are well-explained, and instructions are clear. Wherea… Do each of these objects meet the given requirements? I like this course as this course forced me to think for some existing challenges in a research oriented approach. Rather than re-record, they just paste dozens of error screens apologizing. I am right now wondering whether I should continue learning this or not. Such genius to put them before the lectures! trailer Absloutely Fantastic. I have learnt a lot during the 6 past weeks. Great quality. Construction Engineering and Management Certificate, Machine Learning for Analytics Certificate, Innovation Management & Entrepreneurship Certificate, Sustainabaility and Development Certificate, Spatial Data Analysis and Visualization Certificate, Master's of Innovation & Entrepreneurship. Again, the frustration has to do with the fact that the professor in charge of that section could not be troubled to think for a minute about how this would look to the student. We will discuss how to construct a negation to the statement, and you will see how to win an argument by showing your opponent is wrong with just one example called counterexample!. Decent material but a lot of the assignments were vague. What makes an argument convincing? This course is part of the Introduction to Discrete Mathematics for Computer Science Specialization. %%EOF 0000001224 00000 n Dismiss Join GitHub today. :). In this module, we will learn various techniques for showing that an object exists and that an object is optimal among all other objects. course is poorly explained. But as a standalone course it feels lacking. You can try a Free Trial instead, or apply for Financial Aid. Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California. 0000005547 00000 n At any stage of the problem solving and modelling stage you will require numerical and computational tools. The course was a wonderful learning experience to me. Anyone who wants to grasp good basic over discrete mathematics for computer science to get stronger in Data Structures & Algorithms. Learn more. I have come to know how mathematical proof is fun thing to do, this course transformed me, i highly recommend it to every one. Discrete Mathematics is the language of Computer Science. All ideas are presented so that they are connected in a sequential manner rather than in a random. I haven't finished the bonus track yet, but it sounds like an interesting exercise for 15 puzzle. Now looking forward to the second course of this specialisation. I really liked this course, it's a good introduction to mathematical thinking, with plenty of examples and exercises, I also liked the use of other external graphical tools as exercises. The puzzles and exercises were kind of fun and well-implemented, even if it wasn't always clear why we were doing them. We will see tricky and seemingly counterintuitive, but yet (an unintentional pun) logical aspects of mathematical logic. Thank you for letting me have this experience. xref Am I sure my program computes the optimal answer? In a day's worth of programming, any computer scientist is guaranteed to make a mistake. Back to Mathematical Thinking in Computer Science, Learner Reviews & Feedback for Mathematical Thinking in Computer Science by University of California San Diego. Check with your institution to learn more. such a bad course. 0000016306 00000 n The scripts these professors read off of are riddled with errors. I am looking forward for the rest courses in this specialization. This course is helpful for those who tend to start coding in an efficient way as the base for many algorithms in discrete mathematics. Department of Computer Science and Engineering, Making Fun in Real Life: Tensegrities (Optional), Nobody Can Win All The Time: Nonexisting Examples, Rules on the academic integrity in the course, Tiles, dominos, black and white, even and odd, Number of Solutions for the 8 Queens Puzzle, Introduction, Lines and Triangles Problem, Largest Amount that Cannot Be Paid with 5- and 7-Coins, Number of Moves to Solve the Hanoi Towers Puzzle, Quiz Hint: Why Every Even Permutation Is Solvable, Bonus Track: Finding The Sequence of Moves, Introduction to Discrete Mathematics for Computer Science Specialization, National Research University Higher School of Economics, MATHEMATICAL THINKING IN COMPUTER SCIENCE, About the Introduction to Discrete Mathematics for Computer Science Specialization.
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