Basic algorithms on tree data structures, binary search trees, self-balancing trees, graph data structures and basic traversal algorithms on graphs. This course also covers advanced topics such as kd-trees for spatial data and algorithms for spatial data. Trees and Graphs: Basics can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
Some typos are not acknowledged. The evaluations are disconnected from the lectures.
Excellent content. Lectures along with textbook provide student with working knowledge of trees and graphs.
This course is easy to understand and implement. It needs more programming exercises further!
I have grade 100% My mail id- freespace644@gmail.com
This course is definitely hard but for some good reason. It stretches the mind of the learner/student to achieve algorithmic nirvana.
very solid course - would love more programming assignments and tougher final
Great lecturer and course materials. Assignments were fun also
Good but some typo's in the quizzes and assignments. Would like to see more thorough exercises
The CLRS version for University of Colorado students to access online has some Chapter number changes leading to confusion about what chapter to read in weeks 3 and 4 of this course.
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This course is excellent. The instructor gives detailed, helpful lectures complete with clear examples that help solidify the concepts. The readings supplement the lectures nicely. The assignments are of appropriate difficulty and reinforce what we learn in the course material. I look forward to taking more courses with Sriram!
To me many things taught in the course are not clear enough. I had to guess what the instructor wanted to say frequently.
unclear and messy
This is probably the closest you can get to a univesity course in Data Structures and Algorithms.
The lectures are detailed yet concise. Not too mathy but also not the easiest.
The quizzes solidifies your understandings and corrects your misundertandings.
There seems to be inconcistencies in the quality in programming assignments but overall, for example the programming assignment in MST encourage the "bad" use of dictionaries, while in the Shortest Path programing assignment, it encourages more clever use of data structures (i.e. idx). Still, overall, the programming assignments are good and they make you appreciate more the lessons.
Detailed lectures and thoroughly taught!
Interesting programming assignments.
But the operations on tree/graph could have been better explained using animated videos rather than whiteboard scribblings.
I have grade 100% My mail id- freespace644@gmail.com
Some typos are not acknowledged. The evaluations are disconnected from the lectures.
very solid course - would love more programming assignments and tougher final
I have been very frustrated with the final lab assignment. The images appear to overload the memory and so it will not run properly. I often get the "dead kernel" message at the top. I have been asking for support for over a week and "Cora" does not help - just continues to reply that my issue has been "escalated to the support team". I would not recommend this course unless they fix their final lab assignment, grading of it, and support for it.
This course is a great source to learn the basics of graph data structures and algorithms, as the name of the course suggests. The only problem is last week's assignment in my opinion. The final assignment seems extremely daunting at first glance but using the pseudo-code provided, it becomes trivial. I felt like I didn't learn anything from the last week's assignment., and it kinda felt like cheating! Apart from that though, a really great course.
Pretty thorough. Lectures are great, and quizzes help test your understanding. The assignments do the job, and, are at times, a bit of a puzzle to figure out. I enjoyed the lectures and felt like I learned and was challanged. One will need more practice and study to achieve mastery following the course, but you'll defintiely come out of it with a far greater understanding of the trees and graphs.
Great course to review trees/graphs and their related algorithms. The second programming assignment was a bit unclear at times but the others were straightforward, with the final one being very interesting! Highly recommend to those looking to brush up on their algorithms knowledge.
Another marvelous course to join if someone finished the first course about indexing and sorting. This course really tought be to thnik in different ways while programming. Thank you all associated with the course.
The CLRS version for University of Colorado students to access online has some Chapter number changes leading to confusion about what chapter to read in weeks 3 and 4 of this course.
Very satisfying final assignment. The course is great as a whole too. (But my courseraplus will expire soon. So perhaps this is the last one I take from this specialization.)
Excellent explanation of complex topics. The coding exercise are also well thought out and the tips along the way help to reinforce key concepts.
This course is definitely hard but for some good reason. It stretches the mind of the learner/student to achieve algorithmic nirvana.
Excellent content. Lectures along with textbook provide student with working knowledge of trees and graphs.
A great course. The lectures are easy to follow and the assignments are not too difficult to finish.
This course is easy to understand and implement. It needs more programming exercises further!