The Complete Data Structures and Algorithms Course in Java from Udemy

Welcome to "Data Structures and Algorithms for Coding Interview" course.

Want to land a job at a great tech industry like Google, Microsoft, Facebook, Netflix, Amazon, or other industries but you are intimidated by the foundation of data structures and algorithms skills for the job?

Many programmers who are "self taught", feel that one of the main disadvantages they face compared to college educated graduates in computer science is the fact that they don't have knowledge about algorithms, data structures and the notorious Big-O Notation. Get on the same level as someone with computer science degree by learning the fundamental building blocks of computer science which will give you a big boost during interviews.

Here is what you will learn in this course:

>> Algorithm Run Time Analysis - Big O - O(n) Notation

>> Array (1D, 2D Array)

>> Linked List (All Types of Linked List)

>> Stack Data Structure

>> Queue Data Structure

>> Binary Tree (Array, Linked List Implementation, BFS/DFS Traversal and more)

>> Binary Search Tree

>> Binary Heap

>> AVL Tree

>> Trie Data Structure

>> Searching Algorithms

>> Recursion

>> Sorting Algorithms

>> Dynamic Programming

>> Hashing

>> Graph*

Unlike most instructors, I am not a marketer or a salesperson. I am a self taught programmer(I studied statistics not computer science) who has worked and managed teams of engineers and have been in these interviews both as an interviewee as well as the interviewer.

Taking his experience in educational statistics and coding, Barik's courses will take you on an understanding of complex subjects that you never thought.

We have 30 days money back guarantee, so nothing to lose here.

See you inside the courses.

What's inside

Learning objectives

Fundamentals of data structures and algorithms
Become confident in data structures and algorithms
Learn, implement and use different data structure

Learn popular data structures and their algorithms
Master algorithms including 7 sorting algorithms
Become confident in algorithms coding interview

Fundamentals of data structures and algorithms
Become confident in data structures and algorithms
Learn, implement and use different data structure
Learn popular data structures and their algorithms
Master algorithms including 7 sorting algorithms
Become confident in algorithms coding interview

Syllabus

Introduction

Time Complexity Analysis Example #1

Algorithm Run Time Analysis (Big O Notation)

What is Algorithm Runtime Analysis

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers data structures and algorithms, which are essential for coding interviews at major tech companies

Includes algorithm runtime analysis using Big O notation, a fundamental concept for efficient coding

Explores a wide range of data structures, including arrays, linked lists, stacks, queues, trees, and graphs

Features implementations in Java, which is a popular language for backend development and Android app development

Includes dynamic programming and hashing, which are advanced topics often encountered in coding challenges

Instructor is a self-taught programmer with experience as both an interviewee and interviewer, offering practical insights

Reviews summary

Comprehensive java dsa for interviews

According to learners, this course is a comprehensive resource for mastering Data Structures and Algorithms in Java, specifically designed for coding interview preparation. Students find the explanations clear and easy to follow, making complex topics accessible. While it covers a wide range of essential concepts, some reviewers noted that certain advanced topics could benefit from greater depth or more challenging problems. The course's focus on practical coding examples and implementations in Java is widely appreciated as a strong point.

Practical examples using Java.

"Implementations are done using Java, which was perfect for me."

"Good hands-on coding examples in Java."

"The Java code examples are helpful for understanding how to implement DSA."

"Focus on Java makes it practical for Java developers."

"Source code provided is useful for practice."

Concepts are explained clearly and simply.

"The instructor explains complex concepts in a very simple way."

"I found the explanations easy to understand, even for difficult topics."

"Great for beginners who are new to DSA."

"Explanations are concise and to the point."

"The concepts are broken down effectively."

Covers a broad array of DSA topics.

"It covers almost all fundamental data structures and algorithms."

"From arrays to graphs, everything is included."

"A good overview of the most common DSA topics."

"Wide range of topics covered, good starting point."

"The syllabus is very detailed and covers many areas."

Highly relevant for technical interviews.

"This course is amazing for anyone preparing for coding interviews. It covers all necessary topics."

"Exactly what I needed to brush up on DSA for my job search."

"I feel much more confident about my interview prospects after taking this course."

"Helped me ace the technical rounds for several companies."

"Covers standard interview problems and their solutions effectively."

Pace can be slow or inconsistent.

"Some initial lectures feel a bit slow."

"The pacing varies; some parts are slow, others move quickly."

"Felt a bit slow at the beginning, but picked up later."

"Pacing could be improved for certain modules."

"May be too slow for someone already familiar with basics."

Some advanced areas lack detail.

"Could use more in-depth coverage on complex topics or optimization techniques."

"Some sections feel a bit rushed or don't go deep enough."

"While broad, the depth isn't always sufficient for advanced learners."

"Wishing for more challenging problems beyond the basics."

"Some algorithms could be explained with more rigor."

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 The Complete Data Structures and Algorithms Course in Java with these activities:

Review Java Fundamentals

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Solidify your understanding of Java fundamentals to better grasp the implementation of data structures and algorithms in this course.

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Review basic syntax and data types.
Practice writing simple Java programs.
Study object-oriented programming concepts.

Review: Introduction to Algorithms

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Deepen your understanding of algorithms with a classic textbook that provides detailed explanations and mathematical analysis.

View Introduction to Algorithms, fourth edition on Amazon

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Read relevant chapters on data structures.
Work through examples and exercises.
Compare the book's approach to the course material.

LeetCode Data Structure Problems

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Reinforce your understanding of data structures by solving relevant problems on LeetCode.

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Select problems related to course topics.
Attempt to solve problems independently.
Review solutions and optimize your code.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Tutor Other Students

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Reinforce your understanding by helping other students with data structures and algorithms concepts.

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Offer assistance in online forums.
Organize study groups.
Explain concepts in your own words.

Create a Blog Post on Algorithm Analysis

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Improve your understanding of algorithm analysis by explaining Big O notation in a blog post.

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Research Big O notation and its applications.
Write a clear and concise explanation.
Include examples and diagrams.
Publish your blog post online.

Implement a Data Structure Library

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Solidify your knowledge by creating your own library of data structures and algorithms in Java.

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Choose data structures to implement.
Write code for each data structure.
Write unit tests to ensure correctness.
Document your library for future use.

Cracking the Coding Interview

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Prepare for coding interviews by studying common data structure and algorithm questions and solutions.

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

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Read chapters on relevant data structures.
Practice solving interview questions.
Analyze the provided solutions.

Career center

Learners who complete The Complete Data Structures and Algorithms Course in Java will develop knowledge and skills that may be useful to these careers:

Algorithm Developer

An algorithm developer designs and implements algorithms for various applications. This course helps the algorithm developer by providing in-depth knowledge of data structures and algorithms, including sorting, searching, and graph algorithms. It also covers algorithmic analysis, like Big O notation, which is essential for evaluating the efficiency of the algorithms. The broad array of topics, including recursion, dynamic programming, and hashing, gives the algorithm developer a wide toolkit. The algorithm developer works across a variety of fields.

See salaries and explore the career path for Algorithm Developer

Software Engineer

A software engineer designs, develops, tests, and maintains software applications. This course helps the software engineer build a strong foundation in data structures and algorithms, which are essential for efficient coding and problem-solving. By understanding Big O notation, array, linked lists, stacks, queues, trees, and searching and sorting algorithms, the software engineer writes optimized code. Furthermore, this course helps them perform code reviews, debug code, and optimize application performance.

See salaries and explore the career path for Software Engineer

Full-Stack Developer

A full stack developer works on both the frontend and backend of web applications. This course helps the full stack developer gain expertise in data structures and algorithms, which are essential for building efficient and scalable applications. Understanding data structures such as arrays, linked lists, and trees, as well as algorithms for searching and sorting, helps the developer optimize code for both the client and server sides. This course is helpful because it covers Big O notation.

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

Backend Developer

A backend developer is responsible for designing, developing, and maintaining the server-side logic and databases that power applications. This course helps the backend developer by providing a solid foundation in data structures and algorithms, enabling them to build efficient and scalable systems. The topics covered, such as linked lists, stacks, queues, and hashing, are essential for managing data and optimizing server performance. A backend developer benefits from understanding Big O notation.

See salaries and explore the career path for Backend Developer

Machine Learning Engineer

A machine learning engineer develops and deploys machine learning models. This course helps the machine learning engineer by providing the fundamental knowledge of data structures and algorithms that are crucial for optimizing model performance and scalability. The course's coverage of topics like trees, searching algorithms, and dynamic programming can be directly applied to improve the efficiency of machine learning algorithms and data processing pipelines. Understanding algorithm run time analysis helps the machine learning engineer choose the best algorithms.

See salaries and explore the career path for Machine Learning Engineer

Game Developer

A game developer creates video games for various platforms. This course helps the game developer because it provides knowledge of data structures and algorithms, which are crucial for optimizing game performance and creating engaging gameplay mechanics. The course's coverage of trees, graphs, and searching algorithms is relevant for implementing game logic, artificial intelligence, and pathfinding algorithms. The section on Big O notation is also helpful.

See salaries and explore the career path for Game Developer

Software Architect

A software architect designs the structure and high-level design of software systems. This course helps the software architect make informed decisions about data structures and algorithms to ensure the scalability and performance of the system. Knowledge of trees, graphs, and dynamic programming helps the architect design efficient and robust software architectures. This is a senior position. It is conceivable that one in this role has an advanced degree. Also knowing Big O notation would be useful.

See salaries and explore the career path for Software Architect

Firmware Engineer

A firmware engineer develops low-level software that controls hardware devices. This course helps the firmware engineer because expertise in data structures and algorithms is essential for optimizing code execution and managing memory resources in embedded systems. The course's coverage of linked lists, stacks, queues, and binary trees is particularly relevant for efficient data management. A firmware engineer is also concerned with Big O notation and program run time.

See salaries and explore the career path for Firmware Engineer

Database Administrator

A database administrator manages and maintains databases to ensure data integrity and availability. This course helps the database administrator improve skills by providing a comprehensive understanding of data structures and algorithms, which can be applied to optimize database performance and indexing strategies. The course's coverage of trees, hashing, and searching algorithms is particularly relevant for efficient data retrieval and storage. Furthermore, the Big O notation segment may be useful.

See salaries and explore the career path for Database Administrator

Data Engineer

A data engineer designs, builds, and maintains the infrastructure for data storage and processing. This course may be useful to the data engineer because data structures and algorithms are relevant for efficient data handling. The course's coverage of hashing, trees, and dynamic programming is applicable to optimizing data pipelines and storage solutions. A data engineer will also appreciate the sections of the course that review searching and sorting algorithms. They may also need to know Big O notation.

See salaries and explore the career path for Data Engineer

Data Scientist

A data scientist analyzes large datasets to extract meaningful insights and develop data-driven solutions. This course may be useful to a data scientist because it provides a strong understanding of data structures and algorithms, which helps them efficiently process and analyze data. The topics covered in this course, such as hashing and dynamic programming, are relevant to tasks such as building efficient data pipelines and optimizing machine learning models. A data scientist will also find the coverage of searching algorithms useful.

See salaries and explore the career path for Data Scientist

Robotics Engineer

A robotics engineer designs, develops, and tests robots and robotic systems. This course may be useful to the robotics engineer because data structures and algorithms are a part of robot control, path planning, and sensor data processing. The course's coverage of graphs, trees, and searching algorithms is relevant for robot navigation and decision-making. A robotics engineer will also benefit from understanding algorithm run time analysis using Big O notation.

See salaries and explore the career path for Robotics Engineer

Quantitative Analyst

A quantitative analyst develops and implements mathematical and statistical models for financial analysis and risk management. This course may be useful to the quantitative analyst because data structures and algorithms are a part of efficient data processing and model optimization. Topics covered in the course, such as dynamic programming and searching algorithms, can be applied to build efficient financial models. The quantitative analyst often requires an advanced degree.

See salaries and explore the career path for Quantitative Analyst

Frontend Developer

A frontend developer builds the user interface and ensures a smooth user experience. This course may be useful, indirectly, to the frontend developer by improving their overall problem-solving skills and ability to optimize code. While frontend development focuses more on user interface technologies, understanding data structures and algorithms can help the frontend developer write more efficient JavaScript code and improve application performance. For example, the course covers searching algorithms.

See salaries and explore the career path for Frontend Developer

DevOps Engineer

A DevOps engineer automates and streamlines software development and deployment processes. This course may be useful to the DevOps engineer because data structures and algorithms are relevant for optimizing infrastructure management and automating tasks. The course's coverage of hashing, searching algorithms, and dynamic programming, while not directly applicable, help build programming skills. A DevOps engineer automating tasks and streamlining pipelines may benefit from Big O notation.

See salaries and explore the career path for DevOps Engineer

The Complete Data Structures and Algorithms Course in Java

What's inside

Learning objectives

Syllabus

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Reviews summary

Comprehensive java dsa for interviews

Activities

Career center

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