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Ordered Data Structures

Approx. 19 hours to complete

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Course Summary

Learn the fundamental concepts of computer science such as algorithms, data structures, and recursion in this course. Gain practical experience in implementing these concepts in Python programming language.

Key Learning Points

Gain a strong foundation in computer science concepts
Learn to implement algorithms and data structures in Python
Develop problem-solving skills through programming exercises

Learning Outcomes

Develop a strong foundation in computer science concepts
Implement algorithms and data structures in Python programming language
Improve problem-solving skills through programming exercises

Prerequisites or good to have knowledge before taking this course

Basic knowledge of Python programming language
Familiarity with programming concepts such as variables, loops, and functions

Course Difficulty Level

Intermediate

Course Format

Self-paced
Online
Video lectures
Programming exercises

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Algorithms, Part I
Data Structures and Algorithms

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Description

In this course, you will learn new data structures for efficiently storing and retrieving data that is structured in an ordered sequence. Such data includes an alphabetical list of names, a family tree, a calendar of events or an inventory organized by part numbers. The specific data structures covered by this course include arrays, linked lists, queues, stacks, trees, binary trees, AVL trees, B-trees and heaps. This course also shows, through algorithm complexity analysis, how these structures enable the fastest algorithms to search and sort data.

Outline

Orientation; Linear Structures
1.1 Arrays
1.2 Linked Memory
1.3 Run Time Analysis
1.4 Array and List Operations
1.5 Queue (Data Structure)
1.6 Stack (Data Structure)
Syllabus
Additional References for C++
Week 1 Overview
Downloading the Example C++ Source Code for Lecture with Git
Important Tips and Notes for All Challenge Problems
Guidelines for Asking for Help With Code
Orientation Quiz
Week 1 Quiz
Week 1 Challenge

Introduction to Tree Structures
2.1 Tree Terminology
2.2 Binary Trees
2.3 Tree Traversals
2.4 Binary Search Trees
2.5 BST Analysis
Week 2 Overview
Week 2 Quiz
Week 2 Challenge

Advanced Tree Structures
3.1.1 Balanced BST
3.1.2 AVL Analysis
3.2.1 B-Tree Introduction
3.2.2 B-Tree Insert
3.2.3 B-Tree Search
Week 3 Overview
Week 3 Quiz
Week 3 Challenge

Heap Structures
4.1 Heap Introduction
4.2 Heap Insert
4.3 Heap - RemoveMIN
4.4 Heap - buildHeap
4.5 Heap - Runtime Analysis
Week 4 Overview
Week 4 Quiz
Week 4 Challenge

Summary of User Reviews

CS Fundamentals 2 course on Coursera has received positive reviews from students. Users have appreciated the course for its comprehensive coverage of fundamental computer science concepts. The course is highly recommended for students who want to enhance their understanding of computer science concepts and algorithms.

Key Aspect Users Liked About This Course

Comprehensive coverage of fundamental computer science concepts

Pros from User Reviews

In-depth coverage of fundamental concepts
Well-structured course curriculum
Engaging and interactive course content
Highly knowledgeable and supportive instructors
Great learning platform for beginners and intermediate level students

Cons from User Reviews

Some users found the course to be too basic
Occasional technical glitches in the course content
Limited scope for advanced level students
Lack of hands-on coding projects
Some users found the course pace to be too slow

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