Data Structures: An Active Learning Approach
University of California, San Diego via edX
Overview
This interactive text used in this course was written with the intention of teaching Computer Science students about various data structures as well as the applications in which each data structure would be appropriate to use. It is currently being taught at the University of California, San Diego (UCSD), the University of San Diego (USD), and the University of Puerto Rico (UPR).
This coursework utilizes the Active Learning approach to instruction, meaning it has various activities embedded throughout to help stimulate your learning and improve your understanding of the materials we will cover. You will encounter "STOP and Think" questions that will help you reflect on the material, "Exercise Breaks" that will test your knowledge and understanding of the concepts discussed, and "Code Challenges" that will allow you to actually implement some of the algorithms we will cover.
Currently, all code challenges are in C++ or Python, but the vast majority of the content is language-agnostic theory of complexity and algorithm analysis. In other words, even without C++ or Python knowledge, the key takeaways can still be obtained.
This coursework utilizes the Active Learning approach to instruction, meaning it has various activities embedded throughout to help stimulate your learning and improve your understanding of the materials we will cover. You will encounter "STOP and Think" questions that will help you reflect on the material, "Exercise Breaks" that will test your knowledge and understanding of the concepts discussed, and "Code Challenges" that will allow you to actually implement some of the algorithms we will cover.
Currently, all code challenges are in C++ or Python, but the vast majority of the content is language-agnostic theory of complexity and algorithm analysis. In other words, even without C++ or Python knowledge, the key takeaways can still be obtained.
Syllabus
Module 1: Introduction and Review
Module 2: Introductory Data Structures
Module 3: Tree Structures
Module 4: Introduction to Graphs
Module 5: Hashing
Module 6: Implementing a Lexicon
Module 7: Coding and Information Compression
Module 8: Conclusions
- 1.1 Welcome to Data Structures!
- 1.2 Tick Tock, Tick Tock
- 1.3 Classes of Computational Complexity
- 1.4 The Fuss of C++
- 1.5 Random Numbers
- 1.6 Bit-by-Bit
- 1.7 The Terminal-ator
- 1.8 Git: the "Undo" Button of Software Development
Module 2: Introductory Data Structures
- 2.1 Array Lists
- 2.2 Linked Lists
- 2.3 Skip Lists
- 2.4 Circular Arrays
- 2.5 Abstract Data Types
- 2.6 Deques
- 2.7 Queues
- 2.8 Stacks
- 2.9 And the Iterators Gonna Iterate-ate-ate
Module 3: Tree Structures
- 3.1 Lost in a Forest of Trees
- 3.2 Heaps
- 3.3 Binary Search Trees
- 3.4 BST Average-Case Time Complexity
- 3.5 Randomized Search Trees
- 3.6 AVL Trees
- 3.7 Red-Black Trees
- 3.8 B- Trees
- 3.9 B+ Trees
Module 4: Introduction to Graphs
- 4.1 Introduction to Graphs
- 4.2 Graph Representations
- 4.3 Algorithms on Graphs: Breadth-First Search
- 4.4 Algorithms on Graphs: Depth-First Search
- 4.5 Dijkstra's Algorithm
- 4.6 Minimum Spanning Trees: Prim's and Kruskal's Algorithms
- 4.7 Disjoint Sets
Module 5: Hashing
- 5.1 The Unquenched Need for Speed
- 5.2 Hash Functions
- 5.3 Introduction to Hash Tables
- 5.4 Probability of Collisions
- 5.5 Collision Resolution: Open Addressing
- 5.6 Collision Resolution: Closed Addressing (Separate Chaining)
- 5.7 Collision Resolution: Cuckoo Hashing
- 5.8 Hash Maps
Module 6: Implementing a Lexicon
- 6.1 Creating a Lexicon
- 6.2 Using Linked Lists
- 6.3 Using Arrays
- 6.4 Using Binary Search Trees
- 6.5 Using Hash Tables and Hash Maps
- 6.6 Using Multiway Tries
- 6.7 Using Ternary Search Trees
Module 7: Coding and Information Compression
- 7.1 Return of the (Coding) Trees
- 7.2 Entropy and Information Theory
- 7.3 Honey, I Shrunk the File
- 7.4 Bitwise I/O
Module 8: Conclusions
- 8.1 Summaries of Data Structures
Taught by
Niema Moshiri
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Reviews
5.0 rating, based on 5 reviews
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Estefania Cass.
25Estefania Cass. is taking this course right now, spending 7 hours a week on it and found the course difficulty to be medium.
This is the perfect data structures course for beginners. It is thorough, practical, fun, colorful, and it includes amazing diagrams and illustrations to help visualize data structures, their operations, and their elements. The explanations are extremely... -
Anonymous
Anonymous completed this course.
Very nice and well structured course about data structures. Highly recommended as an introduction to abstract data structures, graphs and hashing. Many thanks! -
Jay Movaliya3
Jay Movaliya completed this course, spending 15 hours a week on it and found the course difficulty to be medium.
It is very good course on Data Structure. I Personally recommend every computer science students to go through to this course at least one time before your graduation. it will change your thinking about computers.
This course will give detailed information about all data-structure. Thanks to authors -
Anonymous
Anonymous completed this course.
Great course on data structures! The learning materials, assignments, and quizzes are well-written. The summaries at the end are also nice as a reference. I highly recommend it! -
Anonymous
Anonymous completed this course.
Excellent and concise course on Data Structures. The course focuses on the theory behind the data structures, but it includes multiple coding problems throughout.
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