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Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms

Massive Open Online Course
  • Overview
  • Course Content
  • Requirements & Materials
Overview

Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms

Course Description

This Data Structures & Algorithms course completes the data structures portion presented in the sequence of courses with self-balancing AVL and (2-4) trees. It also begins the algorithm portion in the sequence of courses as you will investigate and explore the two more complex data structures: AVL and (2-4) trees. Both of these data structures focus on self-balancing techniques that will ensure all operations are O(log n). Time complexity is threaded throughout the course within all the data structures and algorithms and a short Java review is presented on topics relevant to new data structures covered in this course. The course does require prior knowledge of Java, object-oriented programming, and linear and nonlinear data structures.

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Course Content

AVL TREES

(2-4) TREES

ITERATIVE SORTING ALGORITHMS

DIVIDE & CONQUER SORTING ALGORITHMS

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Requirements & Materials
Prerequisites

Recommended

  • Basic knowledge of the Java programming language, object-oriented principles, and the following abstract data types: Binary Search Trees, Heaps, and Hashmaps.
Materials

Required

  • Internet connection (DSL, LAN, or cable connection desirable)

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Who Should Attend

This course is designed for anyone who wants to learn more complex tree data structures, AVL and (2-4) trees; investigate the balancing techniques found in both tree types; implement these techniques in AVL operations; or explore sorting algorithms with simple iterative sorts, followed by Divide and Conquer algorithms. You will use the course visualizations to understand the performance. 

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What You Will Learn

  • Java programming skills by implementing AVLs and sorting algorithms
  • Study techniques for restoring balance in AVL and (2-4) trees
  • When to apply single and double rotations in AVLs
  • Complex (2-4) trees that exhibit underflow and overflow problems
  • The appropriate use of promotion, transfer, and fusion in (2-4) trees
  • The time complexity for the AVLs, (2-4) Trees, and sorting algorithms
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How You Will Benefit

  • Implement basic iterative sorting algorithms: Bubble, Insertion, and Selection.
  • Explore optimizations to improve efficiency, including Cocktail Shaker Sort.
  • Contemplate two Divide & Conquer comparison sorting algorithms Merge and Quick Sort.
  • Consider one non-comparison Divide & Conquer algorithm: LSD Radix Sort.
  • Analyze the stability, memory usage, and adaptations of all sorting algorithms presented.
  • Taught by Experts in the Field
  • Grow Your Professional Network
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The course schedule was well-structured with a mix of lectures, class discussions, and hands-on exercises led by knowledgeable and engaging instructors.

- Abe Kani
President

Frequently Asked Questions

Enrollment
How do MOOCs work?

Designed for an online audience, MOOCs are available to anyone with an internet connection and are free to enroll. Some MOOCs can be started any time – others at regular intervals – and range in length from a few weeks to a few months to complete. You’ll have access to a wide range of online media and interactive tools, including video lectures, class exercises, discussions, and assessments.

Who can enroll in MOOCs?

Anyone with an internet connection can enroll. Sme courses may be unavailable in a small number of countries because of trade restrictions or government policies.

How do you enroll in a MOOC?

Visit a MOOC provider platforms — edX, Coursera, or Udacity — to enroll in a MOOC. Then, watch the pre-recorded lectures, learn from the course readings, and complete related work, like quizzes and in some cases, final projects.

How much do MOOCs cost?

Most courses are free, though there is a small fee if you opt to work towards a certificate of completion. Some courses count toward university credit—and some, like our online master’s program in computer science, offer a full degree. These credit-bearing courses do have fees and applications associated with them.

MOOC Credentials
Can I receive CEUs from completed a MOOC?

Yes, Georgia Tech offers CEUs for some completed MOOC courses taken through Coursera and edX. You have the option of purchasing CEUs after earning a verified course certificate.

What is a digital badge?

A digital badge is an acknowledgement that you've successfully completed a MOOC course. You can display your digital badge on your online profiles so that colleagues and employers can see your achievements at a glance.

What other credentials are available after completing a MOOC?

You can earn CEUs, digital badges, and verified certificates of completion. You can also use MOOCs as an alternate pathway to enter Georgia Tech master's programs through The Analytics: Essential Tools and Methods MicroMasters and the Online Master's in Computer Science.

Who issues the transcript or completion certification?

Certificates of completion are issued by the online providers edX, Coursera, and Udacity. Although they are a great way to showcase your skills, they are not the same as official academic credit from Georgia Tech. However, if you purchase CEUs (which are denoted by a badge), then you can request an official GTPE transcript for free.

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