What you will learn
- How to represent data in ways that allow you to access it efficiently in the ways you need to
- How to analyze the efficiency of algorithms
- How to bootstrap solutions on small inputs into algorithmic solutions on bigger inputs
- Solutions to several classic optimization problems
- How to critically analyze whether a locally optimal approach (greedy) can provide a globally optimal solution to a problem
How do you optimally encode a text file? How do you find shortest paths in a map? How do you design a communication network? How do you route data in a network? What are the limits of efficient computation?
This course, part of the Computer Science Essentials for Software Development Professional Certificate program, is an introduction to design and analysis of algorithms, and answers along the way these and many other interesting computational questions.
You will learn about algorithms that operate on common data structures, for instance sorting and searching; advanced design and analysis techniques such as dynamic programming and greedy algorithms; advanced graph algorithms such as minimum spanning trees and shortest paths; NP-completeness theory; and approximation algorithms.
After completing this course you will be able to design efficient and correct algorithms using sophisticated data structures for complex computational tasks.
Before you start
- Discrete Mathematics - sets, functions, relations; proofs, and proofs by induction; Boolean logic
- Basic probability
- Basic knowledge of Java
- Instructor-Led: course contains assignments and exams that have specific due dates, and you complete the course within a defined time period.
- Course ends: Feb 22, 2019