Welcome to the self-paced course, Algorithms: Design and Analysis! Algorithms are the heart of computer science, and the subject has countless practical applications as well as the intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience. See More: https://bit.ly/2GhgSgL

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Algorithms Design and Analysis
Certi cate
( 9 REVIEWS ) 391 STUDENTS
Welcome to the self-paced course, Algorithms: Design and Analysis! Algorithms are the heart of
computer science, and the subject has …
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FREE
1 YEAR
LEVEL 2 - CERTIFICATE
COURSE BADGE
COURSE CERTIFICATE
77NUMBER OF UNITS
0NUMBER OF QUIZZES
19 HOURS, 53 MINUTES
HOME CURRICULUM REVIEWS
Welcome to the self-paced course, Algorithms: Design and Analysis! Algorithms are the heart of
computer science, and the subject has countless practical applications as well as the intellectual
depth. This specialization is an introduction to algorithms for learners with at least a little
programming experience. The specialization is rigorous but emphasizes the big picture and
conceptual understanding over low-level implementation and the mathematical details.
Assessment
This course does not involve any written exams. Students need to answer 5 assignment questions to
complete the course, the answers will be in the form of written work in pdf or word. Students can
write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers
are submitted, the tutor will check and assess the work.
Certification
Edukite courses are free to study. To successfully complete a course you must submit all the
assignment of the course as part of the assessment. Upon successful completion of a course, you can
choose to make your achievement formal by obtaining your Certi cate at a cost of £49.
Having an Of cial Edukite Certi cation is a great way to celebrate and share your success. You can:
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Course Credit: Stanford University
Why Study Algorithms? 00:04:00
Integer Multiplication 00:09:00
Karatsuba Multiplication 00:13:00
About the Course 00:17:00
Merge Sort: Motivation and Example 00:09:00
Merge Sort: Pseudocode 00:13:00
Merge Sort: Analysis – Part 1 00:09:00
Guiding Principles for Analysis of Algorithms 00:15:00
ASYMPTOTIC ANALYSIS 00:14:00
Big-Oh Notation 00:04:00
Basic Examples 00:07:00
Big Omega and Theta 00:07:00
Additional Examples (Optional) 00:08:00
Algorithm for Counting Inversions I 00:13:00
Algorithm for Counting Inversions II 00:17:00
Strassen’s Subcubic Matrix Multiplication Algorithm 00:22:00
COURSE CURRICULUM

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Algorithm for Closest Pair I 00:32:00
Algorithm for Closest Pair II 00:19:00
Motivation 00:08:00
Formal Statement 00:10:00
Examples 00:13:00
Proof I 00:10:00
Interpretation of the 3 Cases 00:11:00
Proof II 00:16:00
Quicksort: Overview 00:12:00
Partitioning Around a Pivot 00:25:00
Correctness of Quicksort [Review – Optional] 00:11:00
Choosing a Good Pivot 00:22:00
Analysis I: A Decomposition Principle 00:22:00
Analysis II: The Key Insight 00:12:00
Analysis III: Final Calculations 00:09:00
Probability Review I 00:26:00
Probability Review II 00:17:00
Randomized Select – Algorithm 00:22:00

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Randomized Selection – Analysis 00:21:00
Deterministic Selection – Algorithm 00:17:00
Deterministic Selection – Analysis I 00:22:00
Deterministic Selection – Analysis II 00:13:00
Omega(n log n) Lower Bound for Comparison-Based Sorting 00:14:00
Graphs and Minimum Cuts 00:16:00
Graph Representations 00:14:00
Random Contraction Algorithm 00:09:00
Analysis of Contraction Algorithm 00:30:00
Counting Minimum Cuts 00:07:00
Graph Search – Overview 00:23:00
Breadth-First Search (BFS): The Basics 00:14:00
BFS and Shortest Paths 00:08:00
BFS and Undirected Connectivity 00:13:00
Depth-First Search (DFS): The Basics 00:07:00
Topological Sort 00:22:00
Computing Strong Components: The Algorithm 00:29:00
Computing Strong Components: The Analysis 00:26:00

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Structure of the Web 00:19:00
Dijkstra’s Shortest-Path Algorithm 00:21:00
Dijkstra’s Algorithm: Examples 00:13:00
Correctness of Dijkstra’s Algorithm 00:19:00
Dijkstra’s Algorithm: Implementation and Running Time 00:26:00
Data Structures: Overview 00:05:00
Heaps: Operations and Applications 00:18:00
Heaps: Implementation Details 00:21:00
Balanced Search Trees: Operations and Applications 00:11:00
Binary Search Tree Basics I 00:13:00
Binary Search Tree Basics II 00:30:00
Red-Black Trees 00:21:00
Rotations 00:08:00
Insertion in a Red-Black Tree 00:15:00
Hash Tables: Operations and Applications 00:19:00
Hash Tables: Implementation Details I 00:19:00
Hash Tables: Implementation Details II 00:21:00
Pathological Data Sets and Universal Hashing Motivation 00:22:00

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Universal Hashing: De nition and Example 00:26:00
Universal Hashing: Analysis of Chaining 00:19:00
Hash Table Performance with Open Addressing 00:16:00
Bloom Filters: The Basics 00:15:00
Bloom Filters: Heuristic Analysis 00:13:00
Assessment
Submit Your Assignment 00:00:00
Certi cation 00:00:00
COURSE REVIEWS
4.7
9 ratings
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