Algorithms in JavaScript : Design techniques from Udemy

Algorithm Design Techniques : Live problem solving in Java Script

Algorithms are everywhere. One great algorithm applied sensibly can result into a System like GOOGLE.

Larry Page, founder of google designed “Page Rank” algorithm that is behind the search in google. That is why when we search on google we generally find the most relevant result on the First Page itself.

Every Computer Programmer should learn how to design algorithms which are not only correct but also efficient in terms of

TIME and SPACE.

Completer scientists have worked from 100s of years . - (Put images of some of the scientists…)

And derived some of the techniques that can be applied to write and design algorithms.

So Why to reinvent the wheel ??

Let’s go through some of the most famous algorithm design techniques in this course.

Once you will come to know these design techniques It will become very easy for you to approach a problem by identifying which technique to apply to solve that correctly and efficiently.

We will start this course with some measurement techniques in algorithms that is called complexity analysis so that we can measure -

The time and space in an algorithm when we design that.

Then we will start with understanding recursion and deep dive into that.

Recursion is the base of any algorithm design … because most of the algorithms has to be solved using recursion.

Recursion is executed in computers in a very special way using stack frames… we will understand all that..

There are many types of recursion and we will have a look into that.

We will solve some classic problems like the Tower of Hanoi, Binary subtree… to understand the recursion deeply…

And. To make it very easy to understand and code…

Then we will move into another design technique backtracking .

Backtracking algorithms are enhanced recursion where we can revert our decision from inside a recursion…

We will understand how to Identify and approach this kind of problems..

Also, we will solve some classical problems

Rat In Maze, NQueens, KnightsTour problems… and Code them LINE by LINE …

Then, We will then move to the next section

Divide and Conquer… Greedy algorithms

And will take the same approach . To understand identify and Solve some problems… and code some classic problems.

Then there will be a very important section. Dynamic programming

That is not only important for Algorithms design but also, Interviews

This is a very favorite paradigm for the interviewer to ask questions from - We will solve a lot of problems in section along with code… and understand how to approach this kind of problem.

All in all.

By the end of this course -

1. You will understand how to design algorithms

2. A lot of coding practice and design live problems in Java

3. Algorithm Complexity analysis

AND

If you are preparing for your coding Interview or doing competitive programming

This course will be a Big help for you.

I think this is enough to create the THRILL . I welcome you to the course and I am sure this will be fun.

If it does not - It comes with a 30 Days money-back guarantee so don’t think twice to give it a shot…

Welcome Again . And See you in the course.

What's inside

Learning objective

Algorithm design in javascript

Syllabus

Course Introduction

Introduction

Course Resources

Introduction To Algorithms

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers dynamic programming, a paradigm favored in technical interviews, making it beneficial for job preparation

Explores algorithm design techniques like recursion, backtracking, divide and conquer, greedy algorithms, and dynamic programming

Includes live coding of classical problems such as Rat In Maze, NQueens, and KnightsTour, providing practical coding experience

Uses JavaScript, a widely used language for web development, making the learned skills directly applicable to real-world projects

Includes complexity analysis of algorithms, which is crucial for writing efficient code in terms of time and space

Requires familiarity with JavaScript, so learners without prior experience may need to acquire it before taking this course

Reviews summary

Algorithms in javascript: design techniques & interview prep

Based on learner feedback, this course is considered a solid resource for understanding fundamental algorithm design techniques like Recursion, Backtracking, Divide and Conquer, Greedy algorithms, and Dynamic Programming, implemented in JavaScript. Students highlight the value of the live coding examples and the course's relevance for coding interviews and competitive programming. While many find the explanations clear and the content comprehensive for its scope, a minority mention areas where more depth or clearer explanations would be beneficial, particularly for those new to algorithms. The course seems particularly beneficial for learners seeking a practical, code-focused approach to these essential concepts.

Instructor is knowledgeable and engaging.

"The instructor clearly knows the material and is passionate about teaching it."

"I enjoyed the instructor's style and found them easy to follow during the coding sessions."

"The explanations, when clear, were delivered effectively."

"Instructor was knowledgeable and provided good insights."

Comprehensive coverage of key algorithms.

"The course covers all the essential algorithm design paradigms needed for interviews."

"I found the sections on Dynamic Programming and Backtracking particularly well-structured and informative."

"From complexity analysis to greedy algorithms, the curriculum hits all the major points."

"This course provides a good overview of the most important techniques."

Live coding helps solidify understanding.

"The live coding in JavaScript was incredibly helpful. Seeing the algorithms built step-by-step made it much easier to grasp."

"I really appreciated the hands-on approach with concrete coding examples for each algorithm technique discussed."

"Coding along with the instructor during the live problem-solving sessions was a great way to practice."

"The implementation details in JavaScript were clear and practical."

Good preparation for technical interviews.

"This course significantly boosted my confidence for technical interviews requiring algorithm knowledge."

"The problems covered are highly relevant to those asked in coding interviews."

"If you're preparing for a software engineering interview, this course is a valuable resource."

"Helped me think through algorithm problems more effectively during practice interviews."

May require prior foundational knowledge.

"This course is probably best suited if you already have some basic understanding of data structures and algorithms."

"As a beginner, I found the pace quite fast and had to pause frequently to keep up."

"If you are completely new to algorithms, you might need to supplement this course."

"Assumes a certain level of comfort with coding and basic programming concepts."

Some concepts could be explained more clearly.

"While most explanations were good, a few topics felt rushed or not explained in enough detail for a beginner."

"Occasionally, I had to rewatch sections or look up external resources to fully understand a concept."

"I felt some of the theoretical explanations could have been clearer before diving into the code."

"Sometimes the logic behind choosing a specific technique wasn't fully elaborated."

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 Algorithms in JavaScript : Design techniques with these activities:

Review Recursion Fundamentals

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Strengthen your understanding of recursion before diving into more complex algorithm design techniques. A solid grasp of recursion is crucial for understanding backtracking and dynamic programming.

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Review the definition of recursion and its applications.
Practice writing simple recursive functions (e.g., factorial, Fibonacci).
Trace the execution of recursive functions using a call stack diagram.

Read 'Grokking Algorithms'

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Supplement your learning with a visually rich and intuitive guide to algorithms. This book will help you grasp the core concepts more easily.

View Grokking Algorithms, Second Edition on Amazon

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Read the chapters related to recursion, sorting, and graph algorithms.
Work through the examples and exercises in the book.
Compare the book's explanations with the course material.

Implement Sorting Algorithms

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Reinforce your understanding of divide and conquer by implementing classic sorting algorithms. This will help you internalize the logic and complexity analysis of these algorithms.

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Implement Merge Sort and Quick Sort in JavaScript.
Analyze the time and space complexity of each implementation.
Compare the performance of different sorting algorithms on various datasets.

Four other activities

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Create Algorithm Explanation Videos

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Solidify your understanding by creating short videos explaining different algorithm design techniques. Teaching others is a great way to reinforce your own knowledge.

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Choose an algorithm design technique (e.g., backtracking, dynamic programming).
Prepare a script and visuals to explain the technique clearly.
Record a short video explaining the technique and providing examples.
Share your video with other students and solicit feedback.

Build a Pathfinding Visualizer

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Apply your knowledge of graph algorithms and dynamic programming to create an interactive pathfinding visualizer. This project will solidify your understanding of Dijkstra's algorithm and other pathfinding techniques.

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Implement Dijkstra's algorithm in JavaScript.
Create a grid-based representation of a graph.
Visualize the algorithm's execution using HTML and CSS.
Allow users to interactively define start and end points, as well as obstacles.

Read 'Introduction to Algorithms' (CLRS)

Show steps

Deepen your understanding of algorithm design with a comprehensive textbook. This book provides rigorous analysis and detailed explanations of various techniques.

View Introduction to Algorithms, fourth edition on Amazon

Show steps

Read the sections related to the algorithm design techniques covered in the course.
Work through the exercises and problems in the book.
Compare the book's analysis with the course material.

Contribute to an Open Source Algorithm Library

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Apply your knowledge by contributing to an open-source algorithm library. This will give you practical experience in implementing and testing algorithms in a real-world setting.

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Find an open-source algorithm library on GitHub or GitLab.
Identify an algorithm that is missing or needs improvement.
Implement the algorithm in JavaScript and write unit tests.
Submit a pull request with your changes.

Career center

Learners who complete Algorithms in JavaScript : Design techniques will develop knowledge and skills that may be useful to these careers:

Algorithm Developer

An algorithm developer researches, designs, and implements algorithms for a variety of applications. This course in algorithm design techniques is directly relevant to the work of an algorithm developer. The course explores recursion, backtracking, divide and conquer, greedy algorithms, and dynamic programming, which are all essential tools for algorithm design. An algorithm developer who understands algorithm complexity analysis may be able to write high-performance algorithms. The focus on JavaScript in this course should be particularly beneficial for algorithm developers working with JavaScript-based systems.

See salaries and explore the career path for Algorithm Developer

Software Engineer

A software engineer designs, develops, and tests software applications. This course in algorithm design techniques helps the software engineer write efficient and effective code. By learning about recursion, backtracking, divide and conquer, greedy algorithms, and dynamic programming, you may approach problems with a deeper understanding of how to optimize solutions. The focus on JavaScript algorithm design in this course may be useful because JavaScript is commonly used in web development. A software engineer who has this background should be well-prepared to tackle complex coding challenges.

See salaries and explore the career path for Software Engineer

Full-Stack Developer

A full stack developer works on both the front-end and back-end of web applications. This course in algorithm design techniques provides a broader knowledge base for the full stack developer. Understanding recursion, backtracking, and greedy algorithms, as well as dynamic programming, may help optimize both front-end and back-end performance. Given the prevalence of JavaScript in full stack development, the focus on JavaScript algorithms in this course should be helpful to a full stack developer. Full stack developers may encounter numerous opportunities to make use of what they learn in the course.

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

Performance Engineer

A performance engineer analyzes and optimizes the performance of software systems. This course in algorithm design techniques helps the performance engineer identify and address performance bottlenecks. Knowledge of recursion, divide and conquer, dynamic programming, and algorithm complexity analysis is essential for optimizing code and algorithms. A performance engineer may find the JavaScript focus of this course useful when working with web applications. A performance engineer should be familiar with algorithm design.

See salaries and explore the career path for Performance Engineer

Web Developer

A web developer designs, codes, and modifies websites, from layout to function, according to a client's specifications. This course on algorithm design techniques may be useful for tackling complex problems in web application development. Knowledge of recursion, backtracking, and greedy algorithms, as well as dynamic programming should help optimize website performance and user experience. Since JavaScript is a core technology in web development, a web developer should find the focus on JavaScript algorithms in this course particularly beneficial. A web developer may solve problems more efficiently with training in algorithms.

See salaries and explore the career path for Web Developer

Machine Learning Engineer

A machine learning engineer develops and deploys machine learning models. This course in algorithm design techniques can help a machine learning engineer optimize the performance and scalability of machine learning algorithms. By learning about recursion, backtracking, divide and conquer, greedy algorithms, and dynamic programming, you may create more efficient machine learning pipelines. Understanding algorithm complexity is also important to a machine learning engineer, as this helps manage computational resources. The course may be useful for those who work with JavaScript-based machine learning frameworks. An understanding of algorithms can be helpful to a machine learning engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A data scientist analyzes large datasets to extract meaningful insights and develop data-driven solutions. This course in algorithm design techniques can assist the data scientist in optimizing data processing and analysis workflows. Understanding complexity analysis, recursion, divide and conquer, and dynamic programming should help in the development of efficient algorithms for data manipulation and modeling. The ability to design algorithms, along with coding practice using JavaScript, helps the data scientist implement solutions and improve the performance of data science pipelines. A background in algorithms, as provided by courses of this nature, should be valuable for a data scientist.

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Game Developer

A game developer creates and programs video games for various platforms. The study of algorithm design techniques helps a game developer write efficient and optimized game code. Understanding recursion, backtracking, divide and conquer, and dynamic programming should allow for the creation of complex game mechanics and artificial intelligence. With game development often involving performance-critical computations, a game developer who understands algorithm complexity analysis should be able to optimize algorithms for speed and resource usage. The focus on JavaScript algorithm design in this course could be helpful for those using JavaScript-based game engines.

See salaries and explore the career path for Game Developer

Software Architect

A software architect designs the overall structure of software systems. This course in algorithm design techniques helps the software architect make informed decisions about algorithm selection and system design. Understanding recursion, divide and conquer, and dynamic programming can help in designing scalable and maintainable systems. By understanding algorithm complexity analysis, a software architect may be able to identify potential performance bottlenecks and optimize the system architecture. This course provides a software architect with a deeper understanding of algorithm design principles.

See salaries and explore the career path for Software Architect

Data Engineer

A data engineer builds and maintains the infrastructure for data storage and processing. This course in algorithm design techniques may be useful for optimizing data pipelines and data processing workflows. Understanding recursion, divide and conquer, and dynamic programming could help a data engineer design efficient data processing algorithms. The algorithm complexity analysis segment of this course can also help the data engineer optimize data processing infrastructure. A data engineer who has an understanding of algorithms can be valuable to any organization.

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Quantitative Analyst

A quantitative analyst, often working in finance, develops and implements mathematical models for financial analysis and trading. An advanced degree is often required. This course on algorithm design techniques helps the quantitative analyst design and optimize algorithms for trading strategies and risk management. Knowledge of recursion, dynamic programming, and complexity analysis supports the development of efficient algorithms. Since speed is often critical in financial applications, a quantitative analyst who understands algorithm design may have a competitive advantage. A quant benefits from any training that teaches algorithm design.

See salaries and explore the career path for Quantitative Analyst

Technical Lead

A technical lead manages a team of software developers and guides the technical direction of projects. This course in algorithm design techniques may be useful to the technical lead because it provides a strong foundation for making informed decisions about algorithm selection and optimization. Knowledge of recursion, backtracking, divide and conquer, and dynamic programming may help the technical lead guide the team in designing efficient and scalable software solutions. A technical lead with knowledge of algorithm complexity analysis may be more capable of guiding their team.

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Robotics Engineer

A robotics engineer designs, builds, and programs robots for various applications. This course in algorithm design techniques helps the robotics engineer create efficient and robust robot control algorithms. Understanding recursion, backtracking, and dynamic programming can help in the creation of navigation and task-planning algorithms. By understanding algorithm complexity analysis, a robotics engineer can optimize algorithms for real-time performance on embedded systems. This course may be useful for robotics engineers who use JavaScript-based robotics platforms.

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Embedded Systems Engineer

An embedded systems engineer designs and develops software for embedded systems, such as those found in appliances and automobiles. This course in algorithm design techniques may be useful for optimizing code for resource-constrained devices. Knowledge of recursion, divide and conquer, and dynamic programming helps to create efficient algorithms. The algorithm complexity analysis segment of the course is useful to the embedded systems engineer, as this helps conserve limited processing power and memory. Embedded systems engineers may find training in algorithms beneficial.

See salaries and explore the career path for Embedded Systems Engineer

Database Administrator

A database administrator is responsible for maintaining and optimizing databases. This course in algorithm design techniques may be useful for optimizing database queries and data storage strategies. Knowledge of recursion, divide and conquer, and dynamic programming may help the database administrator design efficient data access algorithms. A database administrator who understands algorithm complexity analysis can optimize database performance. Database administrators often benefit from training in algorithms.

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Algorithms in JavaScript

Design techniques

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Algorithms in javascript: design techniques & interview prep

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