Course: Data Structures & Algorithms in Python

$269.00
$325.49 incl. vat

duration: 13 hours |

Language: English (US) |

access duration: 180 days |

Details

Are you a Python programmer, IT Professional or student who wants to learn more about implementing Data structures in Python? This course helps you to better understand the basic concepts of data structures and how algorithms are implemented in Python.

Explore Python data structures and delve into the details of some of the basic data structures, such as linked lists, stacks, and queues, and view the Python implementation of commonly used sorting algorithms and discover how they work. You will also work with binary search trees, various graphical representations and transversal operations on these data structures, and you will discover how to implement and research graph and tree data structures.

Result

After successful completion of this course:

  • You know the details of the basic Python data structures, such as linked lists, stacks, and queues.
  • You have studied the theory about graph and tree data structures in Python.
  • You have explored the various binary search trees, along with the graphical representations and transversal edits on these data structures.
  • You have become acquainted with the commonly used sorting algorithms and how to implement them in Python.

Prerequisites

No specific prior knowledge is required. We do, however, recommend that you have basic knowledge of Python.


Target audience

Software Developer, Web Developer

Content

Data Structures & Algorithms in Python

13 hours

Data Structures & Algorithms in Python: Fundamental Data Structures

Explore Python data structures and delve into the details of some of the basic data structures, such as linked lists, stacks, and queues.

Data Structures & Algorithms in Python: Implementing Data Structures

Begin by examining operations that have different values of time complexity. Then delve into the implementation of some of the basic data structures, such as linked lists, stacks, and queues in Python.

Data Structures & Algorithms in Python: Sorting Algorithms

Explore the workings of some of the most widely used sorting algorithms in Python and examine how their performance affects various measures.

Data Structures & Algorithms in Python: Implementing Sorting Algorithms

Examine the Python implementation of common sorting algorithms such as Selection Sort, Bubble Sort, and Insertion Sort, as well as divide and conquer sorts such as Shell Sort, Merge Sort, and Quicksort.

Data Structures & Algorithms in Python: Trees & Graphs

Examine the theory around graph and tree data structures in Python. Explore binary search trees, different graph representations, and traversal operations on these data structures.

Data Structures & Algorithms in Python: Implementing Trees & Graphs

Discover how to implement trees and graphs and examine with the associated functions used to build and maintain these data structures in Python. In addition, explore algorithms for data structure traversal.

Course options

We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.

Optional practice exam (trial exam)

To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam. 

Optional practice lab

To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediatelyThe lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience. 

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What is included?

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