University of Colorado Boulder - Dynamic Programming, Greedy Algorithms
- Offered byCoursera
Dynamic Programming, Greedy Algorithms at Coursera Overview
Duration | 17 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Advanced |
Official Website | Explore Free Course  |
Credential | Certificate |
Dynamic Programming, Greedy Algorithms at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 3 of 3 in the Data Structures and Algorithms Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Advanced Level Completion of previous courses. Calculus, probability theory: distributions, expectations and moments. Some programming experience with Python.
- Approx. 17 hours to complete
- English Subtitles: English
Dynamic Programming, Greedy Algorithms at Coursera Course details
- This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) and using linear/integer programming solvers for solving optimization problems. We will also cover some advanced topics in data structures.
Dynamic Programming, Greedy Algorithms at Coursera Curriculum
Divide and Conquer Algorithms
What Are Divide and Conquer Algorithms?
Max Subarray Problem Using Divide and Conquer
Karatsuba?s Multiplication Algorithm
Master Method Revisited
FFT Part 1: Introduction and Complex Numbers
FFT Part 2: Definition and Interpretation of Discrete Fourier Transforms
FFT Part 3: Divide and Conquer Algorithm for FFT
Application # 1 : Fast Polynomial Multiplication using FFT
Application # 2: Data Analysis using FFT
Course Syllabus (completed by instructor)
Course Facilitation (completed by facilitator)
Quiz on max subarray problem
Quiz on Karatsuba's Multiplication Algorithm
Quiz on Master Method
Quiz on Complex Numbers and Roots of Unity
Quiz on FFT Algorithm and Applications
Dynamic Programming Algorithms
Introduction to Dynamic Programming + Rod Cutting Problem
Rod Cutting Problem: Memoization
Coin Changing Problem
Knapsack Problem
When Optimal Substructure Fails
Dynamic Programming: Longest Common Subsequence
Greedy Algorithms
Introduction to Greedy Algorithms
Greedy Interval Scheduling
Prefix Codes
Huffman Codes
Intractability and Supplement on Quantum Computing
Decision Problems and Languages
Polynomial Time Problems
NP Definition
NP Completeness and Reductions
Final Exam
About the Final Exam (completed by instructor)
Exam Proctoring, ProctorU Information, and Systems Test Links
Exam Tools (completed by instructor)
NOTE: Do Not Open Password Quiz Yourself
Practice Exam (Optional)
MS-DS Proctored Exam Password Quiz
DTSA 5503 Dynamic Programming, Greedy Algorithms, and Intractability Final Exam
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