Data Structures with Python from Udemy

Data structure provides the right way to organize information in the digital space. The data structure is a key component of Computer Science and is largely used in the areas of Artificial Intelligence, operating systems, graphics.

The right selection of data structure can enhance the efficiency of computer programs or algorithms in a better way.

Learn Data Structures in Python all the way from Built-in to User-Defined.

Methods on Data structures are also covered so that we can use them efficiently.

The data structure and algorithm provide a set of techniques to the programmer for handling the data efficiently. The programmer should understand the core concepts of data handling.

Necessary OOPS is also covered so, that there won't be a problem understanding further concepts.

It's Beginner Friendly with intuition followed by code tutorials, So It's Easy to Understand and Visualise a Data Structure.

So, Solving Problems would be easier after learning the Data Structure as you have better intuition.

Course Design: Intuition of the concept + Code walkthrough in Python + Time and Space Complexity + Application of that Data Structure in real Life.

Data Structures Include:

Lists
Tuples
Sets
Dictionaries
2-D Arrays
OOP For understanding data structures
Stacks
Queues
Deque
Linked-Lists
Doubly Linked Lists
Circular Linked Lists
Trees
Binary Trees
Binary Search Trees + Traversals
AVL Trees
Heaps + Heap sort
Priority Queue
HashMaps/HashTables
Graphs + Properties
Graph Traversals
Spanning Trees + MST
Prims + Kruskals Algorithms for MST
Tries (Keyword Trees)
Misc Section( Has important concepts )
Take Away Section( Download the whole source code in this Section)

What's inside

Learning objectives

Data structures in python
All the way from the built-in to user defined data structures intuition with implementation
Understand oops concept required to build user-defined data structures
How to solve and approach a data-structure problem
Understand applications of data structures

Know and determine time-complexities of operations over data-structures
Discover methods on data-structures
Solved problems so that it's easy to start off practicing
Download the whole code

Data structures in python
All the way from the built-in to user defined data structures intuition with implementation
Understand oops concept required to build user-defined data structures
How to solve and approach a data-structure problem
Understand applications of data structures
Know and determine time-complexities of operations over data-structures
Discover methods on data-structures
Solved problems so that it's easy to start off practicing
Download the whole code

Syllabus

Introduction to the course

What is this Course About?

How to get most of it?

Understand how to practice

This Test is to Examine your performance Till Now.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Begins with built-in data structures like lists and dictionaries, providing a gentle introduction to more complex, user-defined structures

Covers data structures, which are fundamental to computer science and widely used in fields like artificial intelligence and operating systems

Includes a section on object-oriented programming (OOP) to help learners understand the principles behind user-defined data structures

Emphasizes intuition and visualization, followed by code tutorials, making it easier to understand and apply data structures

Focuses on understanding time and space complexity, which is essential for efficient algorithm design and problem-solving

Offers downloadable source code, allowing learners to experiment and build upon the examples provided in the course

Reviews summary

Beginner-friendly data structures in python

According to learners, this course provides a solid foundation in data structures using Python, suitable for beginners. Students praise the clear explanations and the practical coding approach, finding the combination of intuition followed by code walkthroughs particularly helpful. Many appreciate the comprehensive coverage of various data structures, from built-in Python types to more complex user-defined structures like trees and graphs. The practical application sections and solved problems are highlighted as valuable for understanding how to approach data structure problems. While largely positive, some reviewers note that for those seeking advanced topics or rigorous interview preparation, the course might serve best as a starting point requiring further study.

Includes solved problems for practice.

"The solved problems section is really beneficial for seeing how to apply the concepts."

"Walking through solved problems helped me understand the thought process."

"Appreciated the inclusion of solved questions to practice."

"The examples provided were practical and helped reinforce learning."

Covers a wide range of data structures.

"Covers all the major data structures I needed to learn, from lists to graphs."

"The breadth of topics covered is impressive for a single course."

"Good overview of both built-in and user-defined data structures."

"It felt like a very complete introduction to the world of data structures."

Pace and content are suitable for novices.

"Perfect course for beginners looking to understand data structures from scratch."

"As someone relatively new to programming, I found this course very accessible."

"The beginner-friendly approach made learning data structures less intimidating."

"It's a great starting point if you're new to data structures or Python."

Hands-on coding examples reinforce learning.

"The coding examples after the intuition make the concepts really stick."

"Loved the hands-on coding and walkthroughs, it's very practical."

"Coding up the data structures step-by-step was the best way for me to learn."

"The practical implementation in Python helps solidify understanding."

Concepts are explained clearly, good for beginners.

"The explanations are crystal clear and easy to grasp, even for someone new to data structures."

"I really liked how the instructor broke down complex topics into understandable parts."

"The intuition part before coding was super helpful in visualizing the concepts."

"Everything was explained very well, making it easy to follow along and understand."

May not be enough for advanced learners.

"While great for basics, it might not be deep enough for advanced interview prep."

"Could use more challenging problems or discussions on optimization techniques."

"Intermediate learners might find some sections too basic."

"It's a solid intro, but don't expect to become an expert solely from this course."

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 with Python with these activities:

Review Python Fundamentals

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Strengthen your understanding of Python basics to better grasp data structure implementations.

Browse courses on Python Syntax

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Review basic Python syntax and data types (lists, dictionaries, etc.).
Practice writing simple Python functions and control flow statements.
Work through online Python tutorials or exercises.

Read 'Grokking Algorithms'

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Gain a visual and intuitive understanding of algorithms to complement the data structures covered in the course.

View Grokking Algorithms, Second Edition on Amazon

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Read the chapters related to fundamental data structures like arrays, linked lists, and hash tables.
Work through the examples and exercises in the book.

Implement Data Structures from Scratch

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Reinforce your understanding by implementing data structures like linked lists, stacks, and queues in Python without using built-in libraries.

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Choose a data structure (e.g., linked list).
Implement the basic operations (insert, delete, search).
Test your implementation thoroughly.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Pair Programming on Data Structure Problems

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Collaborate with peers to solve data structure problems and learn from each other's approaches.

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Find a partner taking the same course.
Choose a data structure problem to solve together.
Take turns coding and explaining your reasoning.

Build a Simple Application Using Data Structures

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Apply your knowledge by building a project like a to-do list application using linked lists or a simple calculator using stacks.

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Choose a project that utilizes data structures.
Design the application's architecture.
Implement the data structures and application logic.
Test and debug your application.

Create a Data Structure Visualization

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Solidify your understanding by creating a visual representation of how a specific data structure works, such as a binary search tree or a hash table.

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Choose a data structure to visualize.
Use a drawing tool or animation software.
Illustrate the key operations and concepts.
Share your visualization with others.

Read 'Introduction to Algorithms' (CLRS)

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Deepen your understanding of the theoretical underpinnings of data structures with a comprehensive algorithms textbook.

View Introduction to Algorithms, fourth edition on Amazon

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Select chapters related to the data structures covered in the course.
Work through the proofs and exercises.

Career center

Learners who complete Data Structures with Python will develop knowledge and skills that may be useful to these careers:

Software Engineer

A software engineer designs, develops, and tests software applications. This course addresses the organization of information in the digital space, which is directly relevant to a software engineer. The course explores data structure, a key component of computer science that is used in Artificial Intelligence, operating systems, and graphics. A software engineer should take this course to learn data structures in Python, all the way from built-in to user-defined. The course also covers methods on data structures. It also discusses OOPS, which is necessary to understand further concepts.

See salaries and explore the career path for Software Engineer

Algorithm Developer

An algorithm developer designs and implements algorithms for various applications. The core of that work is addressed in this course. With its focus on data structures, this course can drastically improve the performance of an algorithm developer. This course will show them how the right selection of data structure can enhance the efficiency of computer programs or algorithms. They should take this course to learn data structures in Python, all the way from built-in to user-defined. The course also covers methods on data structures and OOPS.

See salaries and explore the career path for Algorithm Developer

Computer Science Teacher

A computer science teacher educates students on computer science principles and programming. This course is an excellent refresher for a computer science teacher who teaches data structures. The course covers data structures in Python, all the way from built-in to user-defined. The course also covers methods on data structures, so that you can teach those concepts effectively. It also covers OOPS, which is necessary to explain more advanced topics. Solving problems becomes easier with the intuition this course will provide.

See salaries and explore the career path for Computer Science Teacher

Full-Stack Developer

A full stack developer works on both the front-end and back-end of web applications. This course is beneficial to a full stack developer because it addresses the organization of information in the digital space, a relevant topic in programming. The course covers data structures in Python, from built-in to user-defined. The course also covers methods on data structures and OOPS. The programmer who takes this course will understand the core concepts of data handling. A full stack developer should consider this course to learn more about data structures.

See salaries and explore the career path for Full-Stack Developer

Backend Developer

A backend developer focuses on the server-side logic and databases of applications. This course will benefit a backend developer because it discusses the organization of information in the digital space, which is directly relevant to programming. As a backend developer your programs will be more efficient with this course's lessons on selecting the right data structure for your application. You will learn data structures in Python, from built-in to user-defined. The course also covers methods on data structures and OOPS.

See salaries and explore the career path for Backend Developer

Data Engineer

Data Engineers are in charge of finding trends in data sets and developing algorithms to help make raw information more useful for companies. This course may be useful because it goes over using the right data structure to enhance computer programs. It covers data structures in Python, from built-in to user-defined. Methods on data structures are also covered. A data engineer may find this course useful for the concepts of storing data. It also covers OOPS, which is necessary to understand further concepts.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

A machine learning engineer develops and implements machine learning algorithms and systems. This course may be helpful to a machine learning engineer because it addresses the organization of information in the digital space, which is directly relevant to machine learning. The course covers data structures, which are largely used in the area of Artificial Intelligence. A machine learning engineer should consider this course to learn data structures in Python, all the way from built-in to user-defined. The course also covers methods on data structures. It also covers OOPS, which is necessary to understand further concepts.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A data scientist analyzes and interprets complex data to identify trends and insights. This course may be helpful to a data scientist because it covers how to organize information in the digital space. The course covers data structures, a key component of computer science that is largely used in the areas of Artificial Intelligence. A data scientist should consider this course to enhance the efficiency of computer programs or algorithms in a better way by understanding how to select data structures. The course covers data structures in Python and methods on data structures.

See salaries and explore the career path for Data Scientist

AI Developer

Artificial intelligence developers create intelligent systems. This course may be helpful for AI development, as the course covers data structures, a key component of computer science that is largely used in Artificial Intelligence. An artificial intelligence developer may find it useful to learn how to select data structures to enhance the efficiency of computer programs or algorithms. This course covers data structures in Python and methods on data structures. It also covers OOPS, which is necessary to understand further concepts.

See salaries and explore the career path for AI Developer

Database Administrator

A database administrator is responsible for managing and maintaining databases. This course may be useful to a database administrator because the course addresses the right way to organize information in the digital space, which is directly relevant to databases. The course covers data structures and how their selection can enhance the efficiency of computer programs or algorithms. As a database administrator, you will want to know how to use data structures in Python. The course also covers OOPS, which is necessary to understand further concepts.

See salaries and explore the career path for Database Administrator

Game Developer

A game developer creates video games for computers and consoles. This course may be helpful to a game developer because the course discusses data structures, a key component of computer science that is largely used in graphics. A game developer may find it useful to learn how to select data structures to enhance the efficiency of computer programs or algorithms. This course covers data structures in Python and methods on data structures. It also covers OOPS, which is necessary to understand further concepts.

See salaries and explore the career path for Game Developer

Data Analyst

A data analyst collects, processes, and performs statistical analyses of data. This course may be useful for a data analyst because it discusses the right way to organize information in the digital space. The course covers data structures and how the right selection of data structure can enhance the efficiency of computer programs or algorithms. A data analyst should take this course to learn data structures in Python from built-in to user-defined. Methods on data structures are also covered. The course also covers OOPS, which is necessary to understand further concepts.

See salaries and explore the career path for Data Analyst

Software Architect

A software architect is responsible for designing the structure of software systems. This course could be useful to a software architect because it discusses data structures, which is a key component of computer science and software design. A software architect may find it useful to learn how to select data structures to enhance the efficiency of computer programs or algorithms. This course covers data structures in Python and methods on data structures. It also covers OOPS, which is necessary to understand further concepts.

See salaries and explore the career path for Software Architect

Research Scientist

A research scientist conducts research to advance scientific knowledge. Research scientists often need to organize information in the digital space. Because of that, this course may be useful, as it explores data structures, a key component of computer science. Selecting the proper data structure can enhance the efficiency of computer programs or algorithms. A research scientist may find it very helpful to learn data structures in Python. The course also covers related methods, along with OOPS, which is necessary to understand other concepts.

See salaries and explore the career path for Research Scientist

Quantitative Analyst

A quantitative analyst uses mathematical and statistical methods to solve financial problems. Although this role typically requires a master's degree, this course may be useful because it covers data structures, which is a key component of computer science. The course covers data structures in Python and methods on data structures. A quantitative analyst may find it useful to learn how to select data structures to enhance the efficiency of computer programs or algorithms. It also covers OOPS, which is necessary to understand further concepts.

See salaries and explore the career path for Quantitative Analyst

Data Structures with Python

What's inside

Learning objectives

Syllabus

Traffic lights

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Reviews summary

Beginner-friendly data structures in python

Activities

Career center

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