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Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues

edX, Online
Length
5 weeks
Price
149 USD
Next course start
Start anytime See details
Delivery
Self-paced Online
Length
5 weeks
Price
149 USD
Next course start
Start anytime See details
Delivery
Self-paced Online
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Course description

Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues

The Data Structures & Algorithms course begins with a review of some important Java techniques and nuances in programming. The course requires some prior knowledge of Java and object-oriented programming, but not in data structures or algorithms. This course introduces you to time complexity, and threads this concept throughout all data structures and algorithms presented in the course. You will work with the principles of data storage in Arrays and LinkedList nodes. You will program the low-level data structures: Singly, Circular and Doubly LinkedLists; and explore edge cases and efficiencies. LinkedLists and Arrays are used to implement Abstract Data Types, ADTs: Stacks, Queues and Deques. Harnessing the power of recursion to move through these data structures is necessary. As the size changes in your data structures, it becomes important to examine amortized analysis of the operations.

The course design has several components and is built around modules. A module consists of a series of short (3-5 minute) instructional videos. In between the videos, there are textual frames with additional content information for clarification, as well as video errata dropdown boxes. All modules include an Exploratory Lab that incorporates a Visualization Tool specifically designed for this course. The lab includes discovery questions that lead you towards delving deeper into the efficiency of the data structures and examining the edge cases.

Upcoming start dates

1 start date available

Start anytime

  • Self-paced Online
  • Online
  • English

Who should attend?

Prerequisites

Prerequisites for the course are basic knowledge of the Java programming language and object oriented principles.

Training content

Module 0: Introduction and Review

  • Review of important Java principles involved in object-oriented design
  • The Iterator & Iterable design patterns, and the Comparable & Comparator interfaces
  • Basic “Big-Oh” notation and asymptotic analysis

Module 1: Arrays, ArrayLists and Recursion

  • The array class, access vs. search of an array, static allocation and efficiency
  • The List abstract data type (ADT) which is backed by an array and uses dynamic resizing and amortized analysis
  • Recursive methods that are applied to the array and ArrayList data structures

Module 2: LinkedLists

  • The Singly LinkedList data structure, its implementation, methods and time complexity
  • The use of the iterable interface and recursive methods in LinkedLists
  • Creating variations of LinkedLists such as Doubly-Linked and Circularly-Linked

Module 3: Stacks, Queues, and Deques

  • The Stack ADT based on the last-in, first-out principle, and its implementations using Arrays and LinkedLists
  • The Queue ADT based on the first-in, first-out principle, and its implementations using Arrays and LinkedLists
  • Creating variations of Stacks and Queues such as Priority Queues and Deques

Course delivery details

This course is offered through The Georgia Institute of Technology, a partner institute of EdX.

9-10 hours per week

Costs

  • Verified Track -$149
  • Audit Track - Free

Certification / Credits

What you'll learn

  • Develop mature Java programming skills with the use of generics, references and interfaces
  • Understand the principles of data storage in Node objects
  • Program various low-level data structures like Singly, Doubly and Circular LinkedLists
  • Design and implement ADTs like Lists (backed by Arrays), Stacks and Queues
  • Examine the edge cases that occur in these linear data structures
  • Analyze the time complexity of linear data structures and their algorithms
  • Compute amortized analysis for Arrays, ArrayLists, Stacks and Queues
  • Implement recursive methods that operate on linear data structures
  • Extend knowledge of these concepts to other structures like PriorityQueues and Deques

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