Data Structure - Part I from Udemy

What's inside

Syllabus

Introduction to Data Structure

Introduction

List

Arrary Basics

Execute.java file is the main file from where you can execute and test the code. Execute file contains the main method. MyListTest.java is a unit test file. You would need junit jar dependencies to execute the test cases.

Execute.java file is the main file from where you can execute and test the code. Execute file contains the main method.

Execute.java file contains the main method.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers fundamental data structures like dynamic arrays, linked lists, stacks, and queues, which are essential for computer science and software engineering careers

Designed to be easily understood by absolute beginners, making it a good starting point for those new to data structures and computer science

Includes unit testing and code execution files, which allows learners to test and implement the data structures they learn in a practical coding environment

Explores time complexity analysis, which is a core concept in computer science curricula and algorithm design

Features the Josephus Problem, which can be a fun and engaging way to learn about data structures and algorithmic thinking

Teaches infix to postfix conversion and postfix evaluation, which are useful skills in compiler design and expression parsing

Reviews summary

Foundation in core data structures

According to learners, Data Structure - Part I is a solid introduction specifically for absolute beginners, offering a good pace. It covers fundamental DS like arrays, lists, stacks, and queues. Many found the lectures clear and easy to follow, praising the focus on practical coding and implementation. The course is seen as a great starting point for foundational understanding. However, some note its limited depth and scope, particularly regarding advanced topics like complex trees or graphs, making it better for building a basic foundation than comprehensive study.

Focuses on core, foundational data structures.

"This course covers arrays, linked lists, stacks, and queues well, plus some runtime analysis."

"Be aware it's Part I, so it sticks to the fundamental list-based and linear structures mostly."

"The syllabus accurately reflects the topics taught - primarily basic structures."

Hands-on implementation is helpful for learning.

"Building the arrays and lists myself in code was the most valuable part for me."

"The hands-on implementation exercises really reinforced the lecture concepts."

"Seeing the code run for stack operations made everything click."

Excellent foundation for newcomers to programming.

"As a complete novice, I finally understood linked lists after this course."

"The instructor breaks down complex ideas into simple, manageable pieces."

"This is exactly what I needed to get started with data structures; it didn't overwhelm me."

Practice problems could be improved upon.

"The assignments were a bit repetitive and didn't challenge me much after a while."

"Wish there were more varied problems to really test my understanding of the concepts."

"Some coding exercises felt too simple, others lacked clear instructions."

Doesn't cover advanced topics fully or in detail.

"I was hoping for more on advanced sorting or hash tables, but they weren't covered."

"The tree section was quite basic, mostly theory without diving into implementation details."

"If you already know the basics, this course might feel too slow or not challenging enough."

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 Structure - Part I with these activities:

Review Array Basics

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Refresh your understanding of array fundamentals to better grasp dynamic arrays and their implementation.

Browse courses on Arrays

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Review array concepts such as indexing and memory allocation.
Practice basic array operations like insertion and deletion.
Solve simple coding problems involving arrays.

Review 'Cracking the Coding Interview'

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Use this book to practice solving data structure problems and prepare for technical interviews.

View Cracking the Coding Interview: 189 Programming... on Amazon

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Read the chapters related to arrays, linked lists, stacks, and queues.
Solve the practice problems at the end of each chapter.
Compare your solutions with the book's solutions.

Implement Linked List Operations

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Practice implementing linked list operations to solidify your understanding of this fundamental data structure.

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Implement add, insertAt, and remove methods for linked lists.
Test your implementation with various test cases.
Analyze the time complexity of each operation.

Four other activities

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Create a Data Structure Comparison Chart

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Create a visual aid that compares and contrasts the different data structures covered in the course.

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Choose the data structures to compare (arrays, linked lists, stacks, queues).
Identify the key characteristics to compare (time complexity, memory usage, etc.).
Create a chart or table that summarizes the comparisons.
Share your chart with other students for feedback.

Review 'Introduction to Algorithms'

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Reference this book to gain a deeper understanding of the algorithms behind the data structures covered in the course.

View Introduction to Algorithms, fourth edition on Amazon

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Read the chapters related to arrays, linked lists, stacks, and queues.
Study the pseudocode implementations of the algorithms.
Compare the book's implementations with the course's implementations.

Build a Simple Stack-Based Calculator

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Apply your knowledge of stacks to build a practical application that evaluates mathematical expressions.

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Implement a stack data structure.
Implement infix to postfix conversion.
Implement postfix evaluation.
Create a user interface for input and output.

Contribute to a Data Structures Library

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Contribute to an open-source data structures library to gain practical experience and collaborate with other developers.

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Find an open-source data structures library on GitHub or GitLab.
Identify a bug or missing feature that you can contribute.
Implement the fix or feature and submit a pull request.
Respond to feedback from the maintainers and revise your code as needed.

Career center

Learners who complete Data Structure - Part I will develop knowledge and skills that may be useful to these careers:

Software Engineer

The role of a Software Engineer is centered around designing, developing, and testing software applications. This often requires a deep understanding of data structures and algorithms to create efficient and scalable solutions. This course in Data Structures builds a strong foundation in fundamental data structures like dynamic arrays, linked lists, stacks, and queues, which are essential for writing efficient code. The course's emphasis on implementation and unit testing aligns perfectly with the practical skills required for software engineering. Furthermore, the focus on time complexity analysis guides you in optimizing algorithms, a crucial aspect of developing high-performance software. Software Engineers who have taken this course will be well-prepared to tackle complex programming challenges.

See salaries and explore the career path for Software Engineer

Algorithm Developer

Algorithm Developers focus on creating and optimizing algorithms for various applications, often requiring in-depth knowledge of data structures. This course directly addresses the fundamental data structures such as dynamic arrays, linked lists, stacks, and queues, providing you with a strong understanding of how to implement and use them. The emphasis on time complexity analysis is particularly relevant since algorithm developers will be creating solutions that are efficient. The experience gained from implementing these data structures and analyzing their performance can be invaluable in developing effective algorithms. This course is essential for anyone aspiring to be an algorithm developer.

See salaries and explore the career path for Algorithm Developer

Game Developer

Game Developers create video games, often dealing with complex data structures to manage game objects, environments, and AI. This course's focus on data structures such as dynamic arrays, linked lists, stacks, and queues aligns perfectly with the needs of game development. Game developers will use these data structures to manage game entities, handle user input, and implement game logic. The emphasis on implementation and testing reinforces the practical skills necessary for building robust game systems. The time complexity analysis taught in this course is also crucial for optimizing game performance and ensuring a smooth player experience. Aspiring game developers should take this course to build a strong foundation in data structures.

See salaries and explore the career path for Game Developer

Embedded Systems Engineer

Embedded Systems Engineers design and develop software for embedded systems, which are often resource-constrained. Efficient data management is extremely important in this field, making a solid understanding of data structures essential. This course offers an in-depth exploration of data structures such as dynamic arrays and linked lists, building the foundation needed to manage data effectively in embedded systems. The emphasis on implementation allows to write optimized code that performs well on limited hardware. The time complexity analysis taught in this course is crucial for optimizing the performance of embedded software. Aspiring embedded systems engineers should take this course to gain hands-on experience in data structures.

See salaries and explore the career path for Embedded Systems Engineer

Firmware Engineer

Firmware Engineers develop low-level software that controls hardware devices. A strong understanding of data structures is essential for efficient resource management and real-time performance. This course directly addresses the need for in-depth data structure knowledge, covering topics such as dynamic arrays, linked lists, and stacks. The focus on implementation provides the practical skills needed to manage data in resource-constrained environments. The time complexity analysis covered in the course is incredibly important for optimizing the performance of firmware. Firmware engineers who take this course will be well-prepared to design and implement efficient and reliable firmware.

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Data Engineer

Data Engineers build and maintain the infrastructure required for data storage and processing. This requires a strong understanding of how data structures work. With its exploration of dynamic arrays, linked lists, and stacks, this course builds a strong foundation for understanding data structures. The emphasis on implementation provides the practical skills needed to optimize data pipelines. The time complexity analysis covered in the course is incredibly important for optimizing the performance of data processing systems. Data engineers who take this course will be well-prepared to design and manage efficient data infrastructure.

See salaries and explore the career path for Data Engineer

Data Scientist

A Data Scientist extracts knowledge and insights from data using various techniques, including data mining, statistical analysis, and machine learning. While data science involves many different tools, understanding data structures is an important piece in effectively structuring and manipulating your data. You will be well served by this course which will lead to a greater ability to select appropriate data structures for efficient data storage and retrieval. The work with time complexity analysis is relevant to ensuring that data processing algorithms scale effectively. The practical implementation of data structures such as lists and queues, as covered in this course, may be useful for organizing and manipulating data in data science workflows.

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Full-Stack Developer

Full Stack Developers work on both the front-end and back-end of web applications. A broad knowledge of computer science is required as tasks vary across all layers. The course's coverage of data structures such as dynamic arrays and linked lists provides a foundation for efficiently managing data on both the front-end and back-end. The hands-on implementation opportunities build confidence in writing efficient code. The time complexity analysis taught in this course is valuable for optimizing application performance across the entire stack. Full stack developers who have taken this course are more effective at building robust, high-performing web applications.

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Mobile Application Developer

Mobile Application Developers design and build applications for mobile devices. Efficient data management is vital in mobile development due to resource constraints. This course builds a solid understanding of data structures, like dynamic arrays and linked lists, which are essential for efficiently handling data in mobile apps. The emphasis on implementation helps you write optimized code that performs well on mobile devices. The principles of time complexity analysis, taught in this course, are particularly relevant for ensuring that mobile apps remain responsive and efficient. Mobile application developers who have taken this course are well-positioned to create high-performing mobile applications.

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Machine Learning Engineer

Machine Learning Engineers develop and deploy machine learning models. These engineers frequently work with vast datasets and algorithms, and understanding data structures is critical for efficiency. This course can help with how data is organized and manipulated. The principles of dynamic allocations, stacks, and queues as presented in this course may inform decisions about how data is preprocessed, stored, and accessed. The practical implementation using Java in this course leads to valuable insights when constructing machine learning pipelines. This course may be helpful to machine learning engineers.

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Database Administrator

Database Administrators are responsible for managing and maintaining databases, which involves ensuring data integrity, performance, and security. Understanding data structures is important because databases rely on these principles to organize and store data efficiently. This course helps build a solid understanding of fundamental data structures, which may be useful in working with different types of databases. The concepts of linked lists, stacks, and queues from the course may assist in managing database operations and optimizing query performance. While database administration involves a broader range of skills, this course may be helpful in providing a foundation in the underlying data structures.

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Site Reliability Engineer

Site Reliability Engineers focus on ensuring the reliability, performance, and scalability of systems. While they do not directly implement data structures, understanding data structures may assist in optimizing system performance. This course may be useful in understanding how data is organized and manipulated within the systems they manage. The concepts of queues and stacks from the course may be useful in understanding system behavior and troubleshooting issues. Site reliability engineers who have some familiarity with data structures may be better equipped to analyze and optimize system performance.

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Quality Assurance Engineer

Quality Assurance Engineers are responsible for testing software to identify and resolve defects. While they may not directly implement data structures, understanding how they work helps in creating effective test cases. This course may be useful in gaining a deeper understanding of the underlying data structures used in software. By understanding concepts like linked lists, stacks, and queues, QA engineers are better equipped to test the functionality and performance of applications. The course's focus on unit testing may be beneficial in learning how to write effective tests. Quality assurance engineers who have some familiarity with data structures may be better prepared to identify potential issues in software.

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DevOps Engineer

DevOps Engineers are responsible for automating and streamlining the software development lifecycle. While DevOps engineers may not directly implement data structures, understanding them may assist when optimizing infrastructure and deployment processes. This course may be useful as it provides insight into how data is organized and manipulated within applications. The concepts of lists, arrays, and queues from the course may be useful in scripting and automation tasks. DevOps engineers who have some familiarity with data structures may be better equipped to optimize software deployment and infrastructure management.

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Web Developer

Web Developers create websites and web applications, and while modern frameworks handle many data structure implementations, understanding the underlying principles is valuable. This course may be helpful in understanding how data is organized and manipulated in web applications. The concepts of lists, arrays, and stacks covered in the course may inform decisions on how to manage data on the client-side or server-side. The course's focus on implementation may be useful in understanding how web frameworks handle data structures. While this course may not be directly applicable to all aspects of web development, the underlying concepts of data structures may be useful.

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Data Structure - Part I

What's inside

Syllabus

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Reviews summary

Foundation in core data structures

Activities

Career center

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