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Data Structures & Algorithms Blueprint - Part 1 (of 2)

4.7 Filled star Filled star Filled star Filled star Half star
Based on 170 ratings
see reviews
Vignesh Sekar

Do you want to get a job in a product-based company?

Data Structures and Algorithms is one subject that can literally change your life as it has the true potential to fetch you a job in a dream product-based company.

But when you start to prepare for it, you have nobody to explain everything from scratch. Books are very complex to understand. Videos on the internet are incomplete. Videos in youtube offer cheap quality content which are very hard to understand.

Read more

Do you want to get a job in a product-based company?

Data Structures and Algorithms is one subject that can literally change your life as it has the true potential to fetch you a job in a dream product-based company.

But when you start to prepare for it, you have nobody to explain everything from scratch. Books are very complex to understand. Videos on the internet are incomplete. Videos in youtube offer cheap quality content which are very hard to understand.

Introducing Data Structures and Algorithms Blueprint, the only course you would want to learn every single concept of Data Structures and Algorithms to crack your interviews, and college exams.

This Course currently has 46+ hours of video content. And part 2 of this course covering all the remaining concepts will be released very shortly so you will have a complete resource using which you can prepare every single concept you need to crack your dream "IT JOB"

Excited to start your life-changing journey? Click the

And the best part is, This Course comes with a 30-day refund policy and if you are not happy with the course, then we dont deserve your money and you will get a full refund.

Enroll now

What's inside

Learning objectives

  • All the concepts you need to understand to master dsa so that you no longer need to scratch your head (the best part is you don't need any prerequisite)
  • Every model of problems you can expect in an interview or college exam or gate exam
  • Hundreds of problems has been discussed because of which you willnot only learn theoretical concepts but also the practical stuffs
  • This course also focussed on lot of interview questions which are asked in coding interviews

Syllabus

WEEK 0 : Introduction to Data Structures and Algorithms
Problem, Program and Algorithm Explained
Important : Data Structures - Explained From Scratch
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Covers asymptotic notations, recursion, and space complexity, which are fundamental concepts for analyzing algorithm performance and are essential for technical interviews
Includes numerous examples and problem-solving sessions, which provide practical experience in applying data structures and algorithms to real-world scenarios
Focuses on interview questions, which prepares learners for the types of questions commonly asked in coding interviews at product-based companies
Requires a part 2 to cover all remaining concepts, which may require learners to wait for the second part to be released to gain a complete understanding
Teaches C pointers, which are useful for low-level programming and memory management, but may not be as relevant for higher-level languages

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Create your own learning path. Save this course to your list so you can find it easily later.
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Reviews summary

Foundational dsa for interview prep

According to students, this course provides a solid and comprehensive foundation in core Data Structures and Algorithms concepts. Many found it particularly helpful for preparing for coding interviews, appreciating the detailed explanations and numerous examples. Learners highlight the clear structure and the extensive coverage of topics like Asymptotic Notations, Recursion, and Arrays in this first part. While many praise the beginner-friendly approach, a few reviewers noted that some parts could be challenging without a basic programming background or found the pacing inconsistent at times, suggesting it requires external practice to fully solidify understanding.
Needs practice outside the course for mastery.
"This course is a great theoretical base, but you absolutely need to practice problems on your own."
"To truly master DSA, supplementing with coding challenges is necessary."
"It lays out the concepts well, but applying them requires external effort."
"Learned the 'what' and 'how', but need to practice the 'doing' myself."
Includes numerous problems and illustrative examples.
"There are so many examples discussed, which really helps solidify the theory."
"The problem-solving sessions are a major plus; they show concepts in action."
"Lots of examples given help clarify how to apply the data structures."
"Working through the examples alongside the lectures was very beneficial."
Concepts are explained clearly and in depth.
"The explanations are incredibly detailed, leaving no stone unturned."
"I appreciate the step-by-step breakdown of complex topics like recursion."
"The instructor explains things in a way that is easy to grasp, even for tough concepts."
"The depth of the explanations makes it easier to build a strong understanding."
Directly helps in preparation for coding interviews.
"I feel much more prepared for my technical interviews after taking this course."
"The way concepts are explained is very relevant to how interview questions are framed."
"This blueprint is essential for anyone targeting product-based companies."
"It helped me understand the patterns behind many common interview problems."
Provides a comprehensive base for DSA concepts.
"This course gave me a very strong base in DSA, starting from the absolute basics."
"I finally feel like I understand the fundamentals thanks to the clear explanations."
"It's a great starting point for anyone new to data structures and algorithms."
"The course provides a solid foundation needed for tackling more complex problems."
Pace is sometimes inconsistent or challenging for some.
"Some sections felt a bit too slow, repeating points unnecessarily."
"I found the jump in difficulty in certain modules challenging without prior coding practice."
"The pace wasn't always consistent; some parts were rushed, others very slow."
"While beginner-friendly overall, some complex topics could feel overwhelming."

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 & Algorithms Blueprint - Part 1 (of 2) with these activities:
Review Basic Programming Concepts
Solidify your understanding of fundamental programming concepts to better grasp the complexities of data structures and algorithms.
Browse courses on Variables
Show steps
  • Review notes on variables and data types.
  • Practice writing simple programs using loops and conditional statements.
  • Familiarize yourself with function definitions and calls.
Review 'Cracking the Coding Interview'
Prepare for technical interviews by studying common data structures and algorithms questions.
View Cracking the Coding Interview: 189 Programming... on Amazon
Show steps
  • Read the chapters related to arrays, strings, and linked lists.
  • Practice solving the interview questions provided in the book.
Review 'Introduction to Algorithms'
Supplement your learning with a comprehensive textbook that covers algorithms and data structures in detail.
View Introduction to Algorithms, fourth edition on Amazon
Show steps
  • Read the chapters related to arrays, stacks, queues, and linked lists.
  • Work through the exercises and problems at the end of each chapter.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Implement Array Operations
Reinforce your understanding of arrays by implementing common operations like searching, sorting, insertion, and deletion.
Show steps
  • Implement linear and binary search algorithms.
  • Implement bubble sort, insertion sort, and selection sort.
  • Practice inserting and deleting elements from arrays.
Create a Blog Post on Time Complexity
Solidify your understanding of time complexity by explaining it in your own words.
Show steps
  • Research different time complexities (O(n), O(log n), etc.).
  • Write a blog post explaining time complexity with examples.
  • Publish your blog post on a platform like Medium or your own website.
Build a Simple Data Structures Library
Create a project to solidify your understanding of data structures by implementing them from scratch.
Show steps
  • Implement a dynamic array or linked list.
  • Implement a stack and a queue using arrays or linked lists.
  • Write unit tests to ensure the correctness of your implementations.
Solve Array-Based LeetCode Problems
Improve your problem-solving skills by tackling array-based coding challenges on LeetCode.
Show steps
  • Select a set of array-based problems on LeetCode.
  • Solve each problem and submit your solution.
  • Analyze the time and space complexity of your solutions.

Career center

Learners who complete Data Structures & Algorithms Blueprint - Part 1 (of 2) 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 emphasizing data structures and algorithms helps build a solid foundation for solving complex problems efficiently, a core skill for software engineers. The syllabus covers asymptotic notations, time complexity, recursion, space complexity, arrays, and pointers, which are fundamental to writing optimized code. Software engineers regularly use these concepts to design and implement high-performance applications. Knowledge of data structures and algorithms, as taught here, is often evaluated in technical interviews for software engineering positions.
See salaries and explore the career path for Software Engineer
Algorithm Developer
An algorithm developer focuses on designing and implementing efficient algorithms for various applications. This course, with its focus on data structures and algorithms, directly aligns with the responsibilities of an algorithm developer. The course covers a wide range of topics, including asymptotic notations, time complexity, recursion, and space complexity, all essential for designing optimized algorithms. The course's examples on time complexity and the Master's Theorem are particularly valuable. An algorithm developer benefits significantly from the problem-solving skills developed through understanding these concepts.
See salaries and explore the career path for Algorithm Developer
Embedded Systems Engineer
An embedded systems engineer develops software for embedded systems, such as those found in consumer electronics and industrial equipment. Embedded systems often have limited resources. This course helps build expertise in writing efficient code. Topics such as pointers, arrays, and time complexity are important to understand. The course's focus on writing optimized code is particularly relevant. A person who wishes to be an embedded systems engineer should consider this course.
See salaries and explore the career path for Embedded Systems Engineer
Mobile Application Developer
A mobile application developer designs and develops applications for mobile devices. Efficient code is crucial for mobile apps to ensure responsiveness and conserve battery life. This course, focusing on data structures and algorithms, helps build a base for writing optimized mobile applications. The concepts covered, such as time complexity, recursion, and arrays, are directly applicable to mobile app development. The course helps aspiring mobile application developers write efficient and performant mobile applications.
See salaries and explore the career path for Mobile Application Developer
Principal Engineer
A principal engineer is a senior technical leader responsible for guiding the technical vision and strategy of an organization. While principal engineers focus on high-level architecture and design, a deep understanding of data structures and algorithms is essential for making informed decisions about system scalability and performance. This course helps these engineers build expertise. The sections on time complexity, space complexity, and algorithm design are invaluable. This course will help future principal engineers.
See salaries and explore the career path for Principal Engineer
Game Developer
A game developer creates video games for various platforms. Game development requires efficient code for rendering graphics, handling user input, and managing game logic. This course emphasizing data structures and algorithms helps build a foundation for optimizing game performance. Concepts such as arrays and pointers are used to manage game data. The course helps aspiring game developers learn to write efficient game code.
See salaries and explore the career path for Game Developer
Technical Lead
A technical lead guides and mentors a team of engineers, providing technical direction and ensuring best practices. While technical leads often have extensive experience, a continued understanding of data structures and algorithms is crucial for making informed decisions about system design and code optimization. This course helps technical leads stay up-to-date with foundational concepts. The course focusing on time complexity, recursion, and algorithm design may be especially useful. Aspiring technical leads should consider this course.
See salaries and explore the career path for Technical Lead
Solutions Architect
A solutions architect designs and implements complex IT systems that meet specific business needs. While solutions architecture involves understanding various technologies and business requirements, a solid understanding of data structures and algorithms is crucial for designing efficient and scalable systems. This course helps build a strong foundation for making informed design decisions. The sections covering time complexity, space complexity, and algorithm design are particularly beneficial. Potential solutions architects should consider taking this course.
See salaries and explore the career path for Solutions Architect
Machine Learning Engineer
A machine learning engineer is responsible for developing and deploying machine learning models at scale. While machine learning focuses on model training, a solid understanding of data structures and algorithms is helpful for optimizing model performance and data handling. This course helps build a foundation for efficient data preprocessing and model deployment. The sections on time complexity, space complexity, and arrays are particularly relevant. Understanding data structures allows machine learning engineers to optimize data pipelines and improve the efficiency of their models. This course may be useful in shaping you into a machine learning engineer.
See salaries and explore the career path for Machine Learning Engineer
Security Engineer
A security engineer is responsible for protecting computer systems and networks from security threats. While security engineering involves understanding various security protocols and attack vectors, a solid understanding of data structures and algorithms is helpful for analyzing code vulnerabilities and designing secure systems. This course helps build a foundation for identifying and mitigating potential security risks. The focus on pointers is useful to security engineers.
See salaries and explore the career path for Security Engineer
Data Scientist
A data scientist analyzes large datasets to extract meaningful insights and build predictive models. While data science involves statistics and machine learning, a strong understanding of data structures and algorithms is crucial for efficient data processing. This course helps build a foundation for optimizing data manipulation and analysis tasks. The sections on arrays, time complexity, and space complexity are particularly relevant. Understanding data structures helps data scientists choose the right data storage and retrieval methods, ultimately improving the performance of their models and analyses. This course may be useful in preparing you as a data scientist.
See salaries and explore the career path for Data Scientist
Full-Stack Developer
A full stack developer works on both the front end and back end of web applications. While front-end development often involves user interface design, a strong understanding of data structures and algorithms is crucial for optimizing back-end performance and data management. This course helps build a foundation for writing efficient server-side code. The sections on arrays, pointers, and time complexity are particularly relevant. Understanding data structures allows full stack developers to design efficient databases and APIs, improving the overall user experience. This course may be useful in preparing you as a full stack developer.
See salaries and explore the career path for Full-Stack Developer
Database Administrator
A database administrator is responsible for managing and maintaining databases. While database administration involves configuring and monitoring database systems, a solid understanding of data structures is helpful for optimizing database performance and data storage. The topics on arrays are especially important. Understanding data structures and the organization of memory allows database administrators to design efficient database schemas. This course may be useful in shaping you into a database administrator.
See salaries and explore the career path for Database Administrator
DevOps Engineer
A devops engineer manages and automates the software development lifecycle, including building, testing, and deployment. While DevOps focuses on automation and infrastructure, a foundational knowledge of data structures and algorithms may be helpful for optimizing deployment processes and resource utilization. This course helps build a foundation for efficient scripting and automation. Understanding time complexity, space complexity, and arrays may be useful. The course may be helpful for future devops engineers.
See salaries and explore the career path for DevOps Engineer
Quality Assurance Engineer
A quality assurance engineer tests software to identify bugs and ensure quality. While QA primarily involves testing methodologies, a general understanding of data structures and algorithms may provide insights into potential performance bottlenecks and edge cases. This understanding may help in designing more effective test cases and identifying performance issues. This course may prove useful to a quality assurance engineer.
See salaries and explore the career path for Quality Assurance Engineer

Reading list

We've selected two 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 & Algorithms Blueprint - Part 1 (of 2).
Cover image
Introduction to Algorithms, fourth edition
Save
Comprehensive textbook on algorithms, covering a wide range of topics including data structures, sorting, searching, graph algorithms, and dynamic programming. It is widely used in universities and is considered a standard reference for algorithm design and analysis. It provides rigorous analysis and clear explanations, making it suitable for both beginners and experienced programmers. This book would be a valuable resource for anyone looking to deepen their understanding of algorithms beyond the scope of the course.
Introduction to Algorithms, fourth edition
Hardcover
$$$$
Introduction to Algorithms, fourth edition
Kindle Edition
$$$
Cracking the Coding Interview
Save
Popular resource for preparing for technical interviews at software companies. It covers a wide range of data structures and algorithms topics, as well as common interview questions and problem-solving techniques. The book includes detailed explanations and solutions to hundreds of problems, making it an excellent resource for anyone preparing for a coding interview. Given the course's focus on interview preparation, this book highly relevant and practical supplement.
Cracking the Coding Interview: 189 Programming...
Paperback
$$
Cracking the Coding Interview : 189 Programming...
Paperback
$$
Cracking the Coding Interview: 150 Programming...
Paperback
$$
Cracking the Coding Interview (Indian Edition)
Hardcover
$$

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Course image
Rating
4.7 Filled star Filled star Filled star Filled star Half star
Effort
45.5 total hours
Via
Udemy
Instructor
Vignesh Sekar
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Covers asymptotic notations, recursion, and space complexity, which are fundamental concepts for analyzing algorithm performance and are essential for technical interviews
Includes numerous examples and problem-solving sessions, which provide practical experience in applying data structures and algorithms to real-world scenarios
Focuses on interview questions, which prepares learners for the types of questions commonly asked in coding interviews at product-based companies
Requires a part 2 to cover all remaining concepts, which may require learners to wait for the second part to be released to gain a complete understanding
Teaches C pointers, which are useful for low-level programming and memory management, but may not be as relevant for higher-level languages
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