Clemson University
Design and Analysis of Algorithms

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Clemson University

Design and Analysis of Algorithms

David Bassett
Brian Dean

Instructors: David Bassett

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Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
88 hours to complete
3 weeks at 29 hours a week
Flexible schedule
Learn at your own pace
Build toward a degree
Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
88 hours to complete
3 weeks at 29 hours a week
Flexible schedule
Learn at your own pace
Build toward a degree

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Recently updated!

August 2024

Assessments

12 assignments

Taught in English

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There are 11 modules in this course

This module covers how to analyze performance of algorithms, models of computation, basic data structures, algorithm design techniques, and common sorting algorithms. [Workload: 2 Weeks]

What's included

15 videos4 readings1 assignment1 programming assignment

This module covers methods for analyzing expected running time and average-case performance, randomized quicksort and quickselect, examples of randomized algorithms and data structures, and "high probability" bounds. [Workload: 1.5 Weeks]

What's included

10 videos1 reading1 assignment

This module covers techniques for analyzing recursive algorithms ("divide and conquer"), recursive thinking, and examples of recursion in algorithm design. [Workload: 1.5 Weeks]

What's included

7 videos1 reading1 assignment1 programming assignment

This module covers priority queues, binary search trees for representing sets, maps, and sequences, randomized and amortized tree balancing mechanisms, and sweep line methods. [Workload: 1.5 Weeks]

What's included

7 videos1 reading1 assignment

This module covers multi-dimensional search structures, amortization, memory-conscious structures (B-trees), and skip lists. [Workload: 2 Weeks]

What's included

15 videos1 reading1 assignment1 programming assignment

This module covers hash tables and distributed hash tables, universal hashing, polynomial hashing of large objects, and applications of hashing across different computing subfields. [Workload: 1.5 Weeks]

What's included

7 videos1 reading2 assignments

This module covers greedy algorithms, dynamic programming, heuristics based on iterative refinement, multi-scale methods, pruned exhaustive search, and hard problems and approximation algorithms. [Workload: 2 Weeks]

What's included

12 videos2 readings1 assignment1 programming assignment

This module covers gradient descent and Newton's method, stochastic gradient descent, gradient-free methods, continuous relaxations of discrete problems, convexity, optimization with constraints, and common types of optimization problems. [Workload: 1.5 Weeks]

What's included

13 videos1 reading2 assignments

This module covers connectivity and related problems, shortest paths, and matchings. [Workload: 1.5 Weeks]

What's included

1 reading1 assignment

This module contains the Final Exam for the Design and Analysis of Algorithms course. [Workload: 1 Week]

What's included

1 assignment

In this module, you will find recordings from Office Hours.

What's included

15 videos4 readings

Instructors

David Bassett
Clemson University
2 Courses86 learners
Brian Dean
Clemson University
1 Course69 learners

Offered by

Recommended if you're interested in Software Development

Build toward a degree

This course is part of the following degree program(s) offered by Clemson University. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹

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