Data Structures and Algorithms: In-Depth using Python
Data Structures and Algorithms: In-Depth using Python, available at $84.99, has an average rating of 4.51, with 429 lectures, 1 quizzes, based on 3072 reviews, and has 22083 subscribers.
You will learn about Learn Data Structures, Abstract Data Types and their implementation in Python Implementation of Searching Algorithms in Python Implementation of Stacks, Queues, Linked List, Binary Trees, Heaps and Graphs in Python Implementation of Binary Tree Traversal Techniques in Python Graph traversals techniques ie Depth First Search and Breadth-First Search in Python Implementation of Sorting Algorithms in Python Enhance Analytical Skill and efficiently use searching and sorting algorithms in real applications This course is ideal for individuals who are Students who want to have better understanding of Data Structures or Python programmers curious about Data Structures or IT Professional experimenting implementation of Data Structures in Python It is particularly useful for Students who want to have better understanding of Data Structures or Python programmers curious about Data Structures or IT Professional experimenting implementation of Data Structures in Python.
Enroll now: Data Structures and Algorithms: In-Depth using Python
Summary
Title: Data Structures and Algorithms: In-Depth using Python
Price: $84.99
Average Rating: 4.51
Number of Lectures: 429
Number of Quizzes: 1
Number of Published Lectures: 429
Number of Published Quizzes: 1
Number of Curriculum Items: 430
Number of Published Curriculum Objects: 430
Original Price: $89.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn Data Structures, Abstract Data Types and their implementation in Python
- Implementation of Searching Algorithms in Python
- Implementation of Stacks, Queues, Linked List, Binary Trees, Heaps and Graphs in Python
- Implementation of Binary Tree Traversal Techniques in Python
- Graph traversals techniques ie Depth First Search and Breadth-First Search in Python
- Implementation of Sorting Algorithms in Python
- Enhance Analytical Skill and efficiently use searching and sorting algorithms in real applications
Who Should Attend
- Students who want to have better understanding of Data Structures
- Python programmers curious about Data Structures
- IT Professional experimenting implementation of Data Structures in Python
Target Audiences
- Students who want to have better understanding of Data Structures
- Python programmers curious about Data Structures
- IT Professional experimenting implementation of Data Structures in Python
This course will help you in better understanding of the basics of Data Structures and how algorithms are implemented in high-level programming language. This course consists of lectures on data structures and algorithms which covers the computer science theory + implementation of data structures in python language. This course will also help students to face interviews at the top technology companies. This course is like having personal tutors to teach you about data structures and algorithms.
There’s tons of concepts and content in this course. To begin the course:
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We have a discussion of why we need data structures.
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Then we move on to discuss Analysis of Algorithms ie Time and Space complexity, though the Asymptotic Notation ie Big O, Omega and Theta are taken up at the end of this course so that you do not get confused and concentrate on understanding the concepts of data structures.
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We have a programming environment setup to make sure you have all the software you need in order to get the hands-on experience in implementing Data structures and algorithms.
Then we get to the essence of the course; algorithms and data structures. Each of the specific algorithms and data structures is divided into two sections. Theory lectures and implementation of those concepts in Python. We then move on to learn:
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Recursion
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Stacks, Queues, Deques
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Linked List
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Trees & Binary Trees
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Binary Search Trees
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Priority Queues and Heaps
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Graphs & Graph Traversal Algorithms
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Searching and Sorting algorithms
Again, each of these sections includes theory lectures covering data structures & their Abstract Data Types and/or algorithms. Plus the implementation of these topics in Python.
Course Curriculum
Chapter 1: Course Overview
Lecture 1: Course Introduction
Lecture 2: Get the most out of this course
Lecture 3: Why we need Data Structure ?
Lecture 4: Why Learn Algorithms ?
Lecture 5: Abstract Data Type (ADT)
Lecture 6: Python Installation on Windows
Lecture 7: PyCharm (IDE) Installation on Windows
Chapter 2: Bonus: Python Crash Course (Basics and Fundamentals)
Lecture 1: First Python Program, Data Types and Variables
Lecture 2: Integers & Float Data Types
Lecture 3: Strings Data Types
Lecture 4: Boolean & None Data Types
Lecture 5: Arithmetic Operators & Integer Division
Lecture 6: Relational or Comparison Operators
Lecture 7: Logical Operators
Lecture 8: input() Function
Lecture 9: print() Function
Lecture 10: if, if-else and elif Statements
Lecture 11: range() Function
Lecture 12: while() & for() Loops
Lecture 13: break & continue Statements
Lecture 14: What are Lists?
Lecture 15: Using Lists and List Indexing
Lecture 16: What are Tuples ?
Lecture 17: Tuple Indexing
Lecture 18: Membership & Identity Operators
Lecture 19: What are Dictionaries?
Lecture 20: Using Dictionaries
Lecture 21: What are Functions?
Lecture 22: Writing Functions in Python?
Lecture 23: Importing Modules in Python
Lecture 24: Creating Your Own Modules
Lecture 25: Fundamentals of Object Oriented Programming
Lecture 26: Defining Classes & Creating Objects
Lecture 27: More on __init__ Method (Constructor)
Lecture 28: Understanding self Parameter
Lecture 29: Static and Local Variables
Chapter 3: Analysis of Algorithms
Lecture 1: Time Complexity
Lecture 2: Order of Growth
Lecture 3: Asymptotic Analysis
Lecture 4: Big-Oh Notation
Lecture 5: Big Omega Notation
Lecture 6: Big Theta Notation
Lecture 7: Performance Summary
Lecture 8: Space Complexity
Chapter 4: Recursion and Analysis of Recursive Functions
Lecture 1: How Recursion Works ?
Lecture 2: Iteration vs recursion lets Implement
Lecture 3: Time Complexity of Recursion – Recurrence Relation
Lecture 4: Recurrence Relation – Another example
Lecture 5: Types of Recursion – Tail and Head Recursion
Lecture 6: Types of Recursion – Tree Recursion
Lecture 7: Types of Recursion – Indirect Recursion
Lecture 8: Sum of N Natural Numbers
Lecture 9: Lets Implement Sum of N Numbers
Lecture 10: Factorial
Lecture 11: Lets Implement Factorial
Chapter 5: Searching Algorithms
Lecture 1: Linear Search Algorithm
Lecture 2: Lets Implement Linear Search
Lecture 3: Binary Search Iterative Algorithm
Lecture 4: Lets Implement Binary Search using Iterations
Lecture 5: Binary Search Recursive Algorithm
Lecture 6: Lets Implement Binary Search using Recursion
Chapter 6: Sorting Algorithms
Lecture 1: Sorting Introduction
Lecture 2: Stable and Unstable Sorting
Lecture 3: Selection Sort – Explanation, Algorithm and Analysis
Lecture 4: Selection Sort – Implementation
Lecture 5: Insertion Sort – Explanation, Algorithm and Analysis
Lecture 6: Insertion Sort – Implementation
Lecture 7: Bubble Sort – Explanation, Algorithm and Analysis
Lecture 8: Bubble Sort – Implementation
Lecture 9: Shell Sort – Explanation, Algorithm and Analysis
Lecture 10: Shell Sort – Implementation
Lecture 11: Merge Sort
Lecture 12: Merge Sort – Algorithm
Lecture 13: Merging – Algorithm
Lecture 14: Merge Sort – Complexity Analysis
Lecture 15: Merge Sort – Implementation
Lecture 16: Quick Sort
Lecture 17: Quick Sort – Algorithm
Lecture 18: Quick Sort – Complexity Analysis
Lecture 19: Quick Sort – Implementation
Lecture 20: Count Sort – Explanation, Algorithm and Analysis
Lecture 21: Count Sort – Implementation
Lecture 22: Radix Sort – Explanation, Algorithm and Analysis
Lecture 23: Radix Sort – Implementation
Lecture 24: Python's Built-in Sorting Functions
Lecture 25: Sorting Algorithms – Summary of Complexities
Chapter 7: Linked List
Lecture 1: Why do we use Linked List
Lecture 2: Creating Node of Linked List
Lecture 3: Playing with the links of Linked List
Lecture 4: How to Create Linked List
Lecture 5: Displaying or Traversing Linked List
Lecture 6: Lets Implement Creating and Displaying Linked List
Instructors
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Syed Mohiuddin
Instructor
Rating Distribution
- 1 stars: 22 votes
- 2 stars: 48 votes
- 3 stars: 335 votes
- 4 stars: 1207 votes
- 5 stars: 1460 votes
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