این دوره طراحی ساختمان داده ها در Python را آموزش می دهد. در این آموزش تصویری نحوه کار با پایتون ، آرایه ها ، لیست های پیوندی، پشته ، صف و درخت ها، کار با ساختمان داده ها ، طراحی ساختمان داده ، کار با درختان دودویی و کار با برنامه های کاربردی در وب را می آموزید.
این دوره آموزشی محصول موسسه InfiniteSkills است.

سرفصل های دوره:

  • معرفی اصول Python
  • کار با انواع داده ها
  • کار با روشهای تجزیه و تحلیل داده ها
  • کار با انواع داده پایتون
  • اصول طراحی برای ساختمان داده
  • نحوه پیاده سازی پشته
  • کار با توابع
  • کار با اشاره گرها
  • نحوه ساخت لیست های پیوندی
  • کار با صف ها
  • ایجاد چرخه در لیست پیوندی
  • نحوه ساخت درخت
  • کار با ساختارهای بازگشتی
  • کار با درخت های دودویی
  • نحوه حذف درخت
  • نحوه جستجو در درخت های دودویی
  • نحوه پیمایش درخت ها
  • ساختارهای مبتنی بر heap
  • کار با درخت Heap
  • کار با نمودار ها
  • نحوه ساخت نمودار ها با ماتریس مجاورت
  • کار با اطلاعات مکانی در ساختارها
  • نحوه استفاده از درخت KD
  • و…

عنوان دوره: InfiniteSkills Designing Data Structures in Python
مدت زمان: 6 ساعت
نویسنده: George T. Heineman


InfiniteSkills Designing Data Structures in Python

6 hours
George T. Heineman

In this project-based Designing Data Structures in Python video tutorial series, you'll quickly have relevant skills for real-world applications.
Follow along with our expert instructor in this training course to get:
Concise, informative and broadcast-quality Designing Data Structures in Python training videos delivered to your desktop
The ability to learn at your own pace with our intuitive, easy-to-use interface
A quick grasp of even the most complex Designing Data Structures in Python subjects because they're broken into simple, easy to follow tutorial videos
When should you use Python's built-in data types, and when should you develop your own? In this video course, George Heineman introduces Python programmers to several important data structures and demonstrates their use with example algorithms. Generic data structures such as arrays, linked lists, and stacks can solve many problems, but to work through some specialized problems, you need to learn different ways to structure data appropriately.
Many Python programmers learned their skills through non-traditional routes, rather than through an undergraduate computer science degree. This video helps complete your education in fundamental data types step-by-step. For many of the data structures, you'll write sample code using a variety of existing modules, and define a process that will help you evaluate and assess these modules for use in your own software. All you need to get started is a working knowledge of Python's built-in data types.
Topics include:
Built-in Python data structures
Python standard library types
Design principles for data structures
Data structures and associated algorithm examples
Graph representations
Heaps, circular buffers, balanced binary trees, and their variants

01. Introduction
Welcome to the Course
02. Fundamentals
Built-in Data Types
API Operations
Analysis Techniques
Design Principles for Data Structures
03. Ubiquitous Lists
0301 Using lists to Implement Stack
0302 Principle: Separate Structure from Function
0303 Example: Circular Buffer
0304 Project: Moving Average / Stdev
04. Pointer Structures
0401 Linked Lists
0402 Queues
0403 Project: Detect Cycles in Linked List
0404 Prefix Tree
05. Recursive Structures
0501 Binary Tree
0502 Implementation of Remove
0503 Binary Tree Retrieval Methods
0504 Traversal
0505 Binary Tree Extension
0506 Balancing Binary Trees
06. Heap-based Structures
0601 Heaps and heapq
0602 Project: Huffman Encoded
0603 Binary Heap
07. Graph Representation
0701 Graphs with Adjacency Matrices
0702 Graphs with Adjacency Lists
0703 Third Party Python Libraries
08. Spatial Data Structures
0801 KD-Trees
0802 Quad-Trees