I'm happy to rate this course 5 stars. It's challenging, and designed learner-friendly: The abstract concept of constraint optimization is framed by a story that provides real-world context, helping memorization when taking in the problem. The workshops are exhaustive, and the assignments are staggered to lead the learner towards trying again, increasing the score with increasing difficulty. MiniZinc is a good learning platform, regardless of whether or not you'll be actually using it. Out of the 20 or so data science courses I've taken on Coursera over the years, this one ranks top.

This is an amazing introductory course to discrete optimization. All the learning materials are very high quality, and teachers are awesome. All concepts are introduced with very practical examples, and the assignments are incrementally difficult. You will learn MiniZinc that it is a declarative programming for discrete optimisation.

It is really enjoyable thanks to the background story. I love workshop videos where teachers solved a problem similar to the assignment before you tried. Definitely, I would recommend this course to anyone who wants to introduce in this area.

Thank you so much for the course. I had to fight my coding habits, programming CP models is quite different from the traditional programming I'm, and it could even be more fun!

First of all, coming from a functional programming background I really like Minizinc, it was natural and intuitive to me. Most of the assignments took me only a couple of hours.

Secondly, the class was recorded years ago, and the videos have desync'd a bit from the language now. It's still very workable but you should know.

Most of my difficulties in completing the assignments and workshops were in understanding the language in the problem statement. Sometimes it seemed like Hong Kong and Australian English might be a little bit different then american english, or maybe it's on purpose. I'm not sure. These were minor though, and eventually I figured it out each time, although twice I did need to search the forums for clarity.

It's obvious they put a lot of work in to make it more polished than the average class, with the Three Kingdoms theme especially. It was a great class and didn't waste my time much. I can do actual things with a solver now. I rate it 9/10 Yellow Turbans. Highly recommended.

This course is an excellent choice for anyone who is either new or partly familiar with optimization problems. The breadth of problems covered in the course is really helpful in understanding some of the structures behind many optimization problems - assignment, matching, sequencing etc. The style of the course is very engaging as well. Using analogies from a story instead of the usual production planning/ blending/factory materials examples etc makes each problem understandable. I'm so glad I signed up for this course and look forward to the next in this series!

This course was amazing! Far more interesting, entertaining, and educational than I was expecting to find. There's a trailer for this course, which indicates how well-produced it is and how much effort has been put in to make this more than just dry lecture material. The course-creators have done an amazing job with this one; if you are a beginner with any interest in optimization or constraint programming then this is the course for you.

Thank you very much for making this course available. The effort that must have been put into developing the material shines through. One down and two to go. Engaging course on modeling problems in combinatorial optimization. Each week has a challenging modeling assignment. Watching the solvers converge faster as I optimized my models was really satisfying. Looking forward to the challenges to come in the next course.

"Basic Modeling for Discrete Optimiation" is an excellent course for anyone interested in optimization models, improving their problem-solving skills and have a nice challenge.

The explanations and examples are fantastic and all these complemented with the utilization of MiniZinc, which make the course so much natural in comparison to other optimization tools.

Highly Recommended 5/5.

I am very thankful for every one making an effort to provide such great content to us learners. I had no clue about operations research and slowly I am getting ideas how to improve my professional life und bring data to use I never about before.

Take care dear Liu Bei Team. I am already hyped for the next course!

This is a great course. Pair programming by the instructors at the end of each week to solve problems is a very helpful way to learn. I really enjoyed the fabled-based learning. I'm definitely enrolling into the advanced course!

Excellent content. The instructors are very thorough in their explainations. The only fault I see is that there isn't many students doing the course, and such it is hard to get help, especially if your schedule is tight and you can only do online courses on Saturday and Sunday. Looking forward to taking the Advance course though.

Very unique and interesting course. Taught well and easy to understand step by step.

I wish the class covers more "real-world" like assignments. All examples and problem sets are described in terms of Chinese history. It was difficult to imagine what I can do with these techniques.

Very interesting, but I miss some theory explaining how the optimizations work behind.

Very interesting course. The lecturers and their staff did a great job.

Despite its name and description the course can actually be seen as a tutorial to the minizinc language. For me this is exactly what I wanted. I expected to gain more familiarity with minizinc and to learn some guiding principles to design a "good" model. My expectations have been satisfied.

In my opinion the lack of "real world problems" is no disadvantage. The background story generated enough (not unnecessarily huge) problems for learning the important concepts.

This was a challenging and beneficial course for me. I wanted to take this optimization course since I am a PhD candidate who have been working on matmematical models since my master's degree. I exploited ilog CPLEX when i was writing my master's thesis. When i was learning about iLog CPLEX i came across the terminology "Constraint Programming" and this drew my attention then. After that, I wanted to learn more about it and I found this course here on Coursera. Thanks for the contribution, I hope I will get a free tshirt as well :)

Challenging optimization puzzle with interesting background story setting. This course provides us some basic knowledge about discrete optimization and the usage of MiniZinc Modeling Language. However mentors focus too much on the modeling process, the program sometimes has a different behavior from our expect. How to locate the potential bug and to fix them, I though, is also important to us. Overall, this is really a good course, suitable for the one without much background knowledge. Recommend!

It's was a challenging course for me, but I enjoyed it very much! The format with an interesting story, a lecture with a solution and the workshop at the end of every week are quite informative. I had trouble interpreting the assignment text of the third week, but after getting some tips from the instructors, I managed to pass it. I am looking forward to applying the knowledge in the real world and will follow the advance course next. Thank you!

It is a great course structure wise and will thought. You will learn how to think about problems and how to formulate them in Minizinc to solve them. However it doesn't give any insight in to MIP formulations or what the whole idea of discrete optimization is about. That being said it is a good introduction to solving discrete problems from a pure application point of view. Thanks!

This course is an excellent introduction to the MiniZinc modeling language. I find myself confident in understanding a file written in MiniZinc, as well as how to model a certain set of problems with it. I hope to learn much more in the next course.

The underlying story of the Chinese Army is a bit too silly for such a serious topic. Maybe I'm reading too much into it, though.