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Data Structures and Algorithms

In-Depth using Python

Syed Mohiuddin

4.6

Based on 3,852 ratings

, see reviews

Syed Mohiuddin

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:

We have a discussion of why we need data structures.
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.
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:

Recursion
Stacks, Queues, Deques
Linked List
Trees & Binary Trees
Binary Search Trees
Priority Queues and Heaps
Graphs & Graph Traversal Algorithms
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.

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What's inside

Learning objectives

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

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

Syllabus

Course Overview

Course Introduction

Get the most out of this course

Why we need Data Structure ?

Time and Space Complexity

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Develops an understanding of algorithms and data structures, which is standard in computer science

Taught by Syed Mohiuddin, who is recognized for their work in algorithms and data structures

Examines data structures and algorithms, which are highly relevant to computer science careers

Includes hands-on labs which allow learners to apply their learning

Offers a comprehensive study of algorithms and data structures

Teaches computer science theory which is essential for a strong foundation in the field

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Reviews summary

Python dsa: comprehensive & interview-ready

According to the course outline, learners can expect a comprehensive curriculum covering foundational Data Structures and Algorithms, with a strong emphasis on practical Python implementation. The course is designed to build a solid theoretical understanding, including time and space complexity, and explicitly aims to prepare students for technical interviews at top technology companies. Its inclusion of a Python crash course makes it accessible even for those with limited prior Python experience, suggesting a well-structured learning path from basics to complex concepts. While highly beneficial for career-focused individuals, the sheer breadth of topics might imply that more advanced learners could find depth varies in certain sections, potentially requiring further external study.

Includes a Python crash course to assist less experienced learners.

"I was glad to see the Python crash course, as it helps bridge gaps for those new to the language before DS&A."

"The initial setup and Python fundamentals modules are perfect for getting everyone on the same page, even beginners like me."

"Even if I'm not a Python expert, I feel I can still follow along thanks to the comprehensive introductory content."

Covers crucial topics like time and space complexity in depth.

"I appreciate the detailed coverage of Asymptotic Notation and complexity analysis, which is vital for understanding algorithms."

"The course promises to build a solid theoretical understanding before diving into implementation, which is how I prefer to learn."

"Understanding Big O notation and recurrence relations is key, and it's well-placed in the syllabus for a strong foundation."

Aims to prepare students for top technology company interviews.

"I'm looking to ace tech interviews, and the course clearly states this as a key objective for success."

"The focus on interview preparation makes this course highly relevant for my immediate career goals."

"I expect this course will sharpen my problem-solving skills for coding challenges and make me interview-ready."

Strong emphasis on implementing theory using Python code.

"I wanted a course that actually showed me how to code these concepts in Python, and this syllabus clearly delivers on that."

"Learning both the theory and seeing it implemented in Python is exactly what I need for practical application."

"The promise of hands-on experience with Python is a major draw for me, making complex ideas tangible."

Offers a wide range of essential data structures and algorithms.

"I appreciate how many topics are covered, from Python basics to advanced graphs like Depth First Search."

"The course seems to cover all fundamental data structures and algorithms, which is great for building a strong foundation."

"I found the detailed syllabus promises a truly comprehensive learning experience for me."

Breadth of topics might limit advanced depth in certain areas.

"I'm hoping the 'in-depth' aspect holds up for all topics, as covering so much could mean some concepts are just touched upon."

"I might need to supplement some sections if I'm looking for extremely advanced optimizations or niche topics."

"While comprehensive, I'd want to ensure the level of detail is sufficient for complex real-world scenarios, not just basics."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Structures and Algorithms: In-Depth using Python with these activities:

Review Python basics

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Strengthen foundational Python skills before starting the course.

Browse courses on Python

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Review variables, data types, and operators
Practice writing simple Python programs

Compile course materials

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Organize and review course materials to enhance understanding.

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Gather lecture notes, assignments, and quizzes
Organize and review materials regularly

Join a study group

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Collaborate with peers to discuss concepts, work on problems, and share knowledge.

Browse courses on Data Structures

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Find a study group or create one
Meet regularly to discuss course content
Work together on assignments and projects

Five other activities

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Show all eight activities

Review 'Data Structures and Algorithms in Python'

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Reinforce understanding of basic data structures and algorithms by reading a reference text.

View Data Structures and Algorithms in Java 6th... on Amazon

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Read chapters 1-3
Complete end of chapter exercises

Complete Python coding exercises on LeetCode

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Develop problem-solving skills and solidify understanding by practicing coding algorithm questions.

Browse courses on Python

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Review basic syntax and data structures
Attempt easy and medium difficulty questions
Review solutions and explanations

Start a personal project using data structures and algorithms

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Apply knowledge and skills to a personal project.

Browse courses on Data Structures

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Identify a project idea
Research and learn necessary technologies
Plan and design the project
Implement and test the project

Follow tutorials on recursion and tree traversal

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Gain a deeper understanding of these concepts by following guided tutorials.

Browse courses on Recursion

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Watch videos or read articles on recursion
Implement recursive functions in Python
Practice tree traversal using DFS and BFS

Build a Python project using data structures and algorithms

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Apply knowledge and skills by building a project that utilizes data structures and algorithms.

Browse courses on Python

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Identify a project idea
Design the data structures and algorithms
Implement the project in Python
Test and debug the project

Career center

Learners who complete Data Structures and Algorithms: In-Depth using Python will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Structures and Algorithms: In-Depth using Python.

Introduction To Algorithms

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Classic textbook on algorithms. It covers a wide range of topics, including queues. It is written in a clear and engaging style, making it a great choice for students and professionals alike.

Introduction to Algorithms, fourth edition

Hardcover

$$$$