Daniel Kane

Daniel is an assistant professor at UCSD with a joint appointment between the Department of Computer Science and Engineering and the Department of Mathematics. He holds B.S. from MIT and Ph.D. from Harvard.
Areas of Expertise:
- Theoretical computer science
- Combinatorics
- Number theory

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NP-Complete Problems (edX)

Learn about NP-complete problems, known as hard problems that can’t be solved efficiently, and practice solving them using algorithmic techniques. Step into the area of more complex problems and learn advanced algorithms to help solve them.
Average: 10 ( 3 votes )

Graph Algorithms (edX)

Learn how to use algorithms to explore graphs, compute shortest distance, min spanning tree, and connected components. If you have ever used a navigation service to find the optimal route and estimate time to destination, you've used algorithms on graphs.
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Data Structures Fundamentals (edX)

Learn about data structures that are used in computational thinking – both basic and advanced. A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently.
Average: 8 ( 3 votes )