50Days of DSA JavaScript Data Structures Algorithms LEETCODE from Udemy

"Basically I'm a beginner to javascript but after listening the way of his teaching , i have no word for him he's fabulous person . and I recommend all to watch his course." - Mohd. Amir
"Excellent explanations and application of theory directly to practice. " -." - Emmanuel Apea
"Excellent Teaching" - Sarhan Sayyed Rasool Shaikh
"Excellent course. The teacher has mastery of what he explains and the content is of great value."-Vyctor Vieira Guimarães
"It's an amazing course the instructor is super amazing and the way of teaching it is super awesome clarify everything very well and the roadmap for learning DSA is superb. Go with this guy without a second thought you will love it for sure..." - Shashank Jaiswal
"Excellent, way of teaching" - Gauri Shankar Jangid

"Basically I'm a beginner to javascript but after listening the way of his teaching , i have no word for him he's fabulous person . and I recommend all to watch his course." - Mohd. Amir
"Excellent explanations and application of theory directly to practice. " -." - Emmanuel Apea
"Excellent Teaching" - Sarhan Sayyed Rasool Shaikh
"Excellent course. The teacher has mastery of what he explains and the content is of great value."-Vyctor Vieira Guimarães
"It's an amazing course the instructor is super amazing and the way of teaching it is super awesome clarify everything very well and the roadmap for learning DSA is superb. Go with this guy without a second thought you will love it for sure..." - Shashank Jaiswal
"Excellent, way of teaching" - Gauri Shankar Jangid

About the Course:

Welcome to the Data Structures and Algorithms Coding Interview Bootcamp with Javascript.

The primary goal of this course is to prepare you for coding interviews at top tech companies. By tackling one problem at a time and understanding its solution, you'll accumulate a variety of tools and techniques for conquering any coding interview.

Daily Data Structures and Algorithms Coding Challenges:

The course is structured around daily coding challenges. Consistent practice will equip you with the skills required to ace coding interviews. For the next 50 days commit to yourself to practice atleast 2 coding interview questions everyday. You don't need any setup for this as the daily coding problem challenges can be solved in the coding environment provided by Udemy. The course will automatically track your progress and you just need to spend your time making actual progress everyday.

Topics Covered:

We start from the basics with Big O analysis, then move on to very important algorithmic techniques such as Recursion, Backtracking and Dynamic Programming Patters. After this we move to cover common data structures, and discuss real problems asked in interviews at tech giants such as Google, Meta, Amazon, Netflix, Apple, and Microsoft.

For each question, we will:

Discuss the optimal approach
Explain time and space complexity
Code the solution in Javascript (you can follow along in your preferred language)

Additional Resources :

The course includes downloadable resources, motivational trackers, and cheat sheets.

Course Outline:

Day 1: Arrays, Big O, Sorted Squared Array, Monotonic Array
Day 2:Recursion,k-th symbol in Grammar,Josephus problem
Day 3:Recursion, Tower of Hanoi, Power Sum
Day 4:Backtracking, Permutations, Permutations 2
Day 5:Backtracking, Subsets, Subsets 2
Day 6:Backtracking, Combinations, Combinations Sum 1
Day 7:Backtracking,Combinations Sum 2,Combinations Sum 3
Day 8:Backtracking,Sudoku Solver, N Queens
Day 9:Dynamic Programming, Fibonacci, Climbing Stairs
Day 10:Dynamic Programming, Min Cost Climbing Stairs, Tribonacci
Day 11:Dynamic Programming, 01 Knapsack, Unbounded Knapsack
Day 12:Dynamic Programming, Target Sum, Partition Equal Subset Sum
Day 13:Dynamic Programming, LCS, Edit Distance
Day 14:Dynamic Programming, LIS, Max Length of Pair Chain, Russian Doll Envelopes
Day 15:Dynamic Programming, Palindromic Substrings, Longest Palindromic Substring, Longest Palindromic Subsequence
Day 16:Dynamic Programming, Palindrome Partitioning, Palindrome Partitioning 2
Day 17:Dynamic Programming, Word Break, Matrix Chain Multiplication
Day 18:Dynamic Programming, Kadane's algorithm - Max Subarray, Maximum Product Subarray
Day 19:Greedy Algorithms - Fractional Knpasack, Non overlapping Intervals
Day 20:Greedy Algorithms - Jump Game 1, Minimum # of arrows to burst baloons
Day 21:Greedy Algorithms - Two City Scheduling, Boats to Save people
Day 22:Greedy Algorithms - Task Scheduler, Largest Number
Day 23:Greedy Algorithms - Gas Stations, Jump Game 2
Day 24: Arrays, Rotate Array, Container with Most Water
Day 25: Hash Tables, Two Sum, Isomorphic Strings
Day 26: Strings, Non-Repeating Character, Palindrome
Day 27: Strings, Longest Unique Substring, Group Anagrams
Day 28: Searching, Binary Search, Search in Rotated Sorted Array
Day 29: Searching, Find First and Last Position, Search in 2D Array
Day 30: Sorting, Bubble Sort, Insertion Sort
Day 31: Sorting, Selection Sort, Merge Sort
Day 32: Sorting, Quick Sort, Radix Sort
Day 33: Singly Linked Lists, Construct SLL, Delete Duplicates
Day 34: Singly Linked Lists, Reverse SLL, Cycle Detection
Day 35: Singly Linked Lists, Find Duplicate, Add 2 Numbers
Day 36: Doubly Linked Lists, DLL Remove Insert, DLL Remove All
Day 37: Stacks, Construct Stack, Reverse Polish Notation
Day 38: Queues, Construct Queue, Implement Queue with Stack
Day 39: Binary Trees, Construct BST, Traversal Techniques
Day 40: Pre order and In order Traversal of Binary Tree - Iterative
Day 41: Post Order Traversal Iterative, Path Sum 2
Day 42: Construct Binary Tree from Pre and In order Traversal ^ In and Post order Traversal
Day 43: Binary Trees, Level Order Traversal, Left/Right View
Day 44: Level order Trav 2, ZigZag Traversal
Day 45: Vertical order Traversal, Sum root to leaf numbers
Day 46: Binary Trees, Invert Tree, Diameter of Tree
Day 47: Binary Trees, Convert Sorted Array to BST, Validate BST
Day 48: Lowest common Ancestor of BST, Unique BST 2
Day 49: Lowest common Ancestor of Binary Tree, Unique BST 1
Day 50: Serialize and Deserialize Binary Tree, N-ary Tree Level Order Traversal
Day 51: Heaps, Max Heap, Min Priority Queue
Day 52: Graphs Thus, it's a totally risk-free opportunity. Register today, facing ZERO risk and standing to gain
So what are you waiting for? Join the best Javascript Data Structures & Algorithms Bootcamp on Udemy.
I'm eager to see you in the course.
Let's kick things off. :-)
Jackson

What's inside

Learning objectives

Dynamic programming, backtracking techniques
Javascript coding interview problems and solutions
Common data structures such as arrays, hash table,linked list,binary trees,graphs etc.

Time and space complexity of algorithms, detailed discussion of logic to solve questions
Real coding interview questions from google, meta,amazon,netflix ,microsoft etc.
Boost your problem solving skills

Dynamic programming, backtracking techniques
Javascript coding interview problems and solutions
Common data structures such as arrays, hash table,linked list,binary trees,graphs etc.
Time and space complexity of algorithms, detailed discussion of logic to solve questions
Real coding interview questions from google, meta,amazon,netflix ,microsoft etc.
Boost your problem solving skills

Syllabus

Day 1: Arrays Data Structures and Algorithms

What you're going to get from this course

Welcome! How to make best use of this course (Please Watch)

Career center

Learners who complete 50Days of DSA JavaScript Data Structures Algorithms LEETCODE will develop knowledge and skills that may be useful to these careers:

Software Engineer

A Software Engineer designs, develops, and maintains software applications and systems, implementing solutions that are robust, efficient, and scalable. This course is an exceptional preparation for a career as a Software Engineer, as its primary goal is to equip learners for coding interviews at top tech companies. By mastering fundamental data structures like arrays, linked lists, hash tables, binary trees, and graphs, alongside critical algorithmic techniques such as dynamic programming, recursion, and backtracking, you build the core competencies needed to write high-quality code. The course's focus on real interview questions and JavaScript solutions directly translates into the practical skills highly sought after in this field.

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Algorithm Engineer

An Algorithm Engineer specializes in the design, analysis, and implementation of highly optimized algorithms for specific computational challenges, pushing the boundaries of efficiency and problem-solving. This course, "50Days of DSA JavaScript Data Structures Algorithms LEETCODE," is exceptionally well-suited for a career as an Algorithm Engineer. It delves deeply into techniques such as recursion, backtracking, dynamic programming, and greedy algorithms, alongside a comprehensive study of data structures like binary trees, graphs, and heaps. The explicit focus on time and space complexity analysis and solving real-world interview problems directly aligns with the core responsibilities of this specialized field, which often requires an advanced degree.

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Performance Engineer

A Performance Engineer focuses on optimizing the speed, scalability, and efficiency of software systems, ensuring they meet rigorous performance benchmarks. This course is highly beneficial for a Performance Engineer, as it provides a deep dive into crucial concepts like Big O analysis, efficient data structure selection, and advanced algorithmic techniques such as dynamic programming and greedy algorithms. The ability to solve complex coding problems and analyze their time and space complexity, reinforced through daily JavaScript coding challenges, is fundamental for identifying bottlenecks, improving code efficiency, and ensuring robust system performance across various applications.

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Backend Developer

A Backend Developer builds and maintains the server-side logic, databases, and APIs that power applications, focusing on data processing, storage, and security. The "50Days of DSA JavaScript Data Structures Algorithms LEETCODE" course is highly relevant for a Backend Developer, providing an in-depth understanding of crucial data structures and algorithms. Mastery of Big O analysis and efficient problem-solving techniques, taught through daily coding challenges and JavaScript solutions, is essential for optimizing server performance, handling large datasets effectively, and designing robust, scalable backend systems. This course specifically prepares you for the algorithmic challenges often encountered in backend development, crucial for any top tech company.

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Technical Interviewer

A Technical Interviewer evaluates candidates' problem-solving abilities, knowledge of data structures, and algorithmic thinking during the hiring process for engineering roles. This course, "50Days of DSA JavaScript Data Structures Algorithms LEETCODE," is exceptionally well-suited for a Technical Interviewer. It provides a deep dive into real coding interview questions from top tech companies and detailed discussions of optimal approaches, time and space complexity, and JavaScript solutions across various data structures and algorithms like dynamic programming, recursion, and graphs, ensuring a thorough understanding of interview pedagogy and effective candidate assessment.

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Full-Stack Developer

A Full Stack Developer possesses the versatility to work across both frontend and backend development, building complete applications and handling all layers of the software stack. The "50Days of DSA JavaScript Data Structures Algorithms LEETCODE" course is an ideal foundation for a Full Stack Developer, offering comprehensive training in essential data structures, such as arrays, linked lists, and graphs, combined with powerful algorithmic techniques including dynamic programming and backtracking. This broad knowledge enables the efficient development of both client-side and server-side components, ensuring optimal performance and robust problem-solving capabilities throughout the application stack.

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

Machine Learning Engineer

A Machine Learning Engineer designs, builds, and deploys machine learning models and systems, working with data and algorithms to create intelligent applications. While this role typically requires an advanced degree, the "50Days of DSA JavaScript Data Structures Algorithms LEETCODE" course provides a crucial foundational understanding for an aspiring Machine Learning Engineer. Mastery of data structures and algorithms, algorithmic complexity analysis, and problem-solving techniques like dynamic programming is fundamental for understanding, optimizing, and efficiently implementing various machine learning algorithms, as well as preprocessing and managing large datasets at scale.

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Data Engineer

A Data Engineer designs, constructs, installs, and maintains efficient data processing systems and pipelines, ensuring data is available, reliable, and usable. The problem-solving skills and deep understanding of data structures and algorithms, including arrays, hash tables, and graphs, gained from this course are critical for a Data Engineer. The ability to analyze time and space complexity, and to implement optimized solutions in JavaScript, directly translates into building high-performance data transformation jobs, efficient storage solutions, and scalable data architectures capable of handling vast datasets effectively for any organization.

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Frontend Developer with Data Visualization Focus

A Frontend Developer with a Data Visualization Focus builds interactive web interfaces that present complex data in an understandable and performant manner. This role demands not only strong design sense but also a deep understanding of how to efficiently process and render large datasets on the client-side. This course helps a Frontend Developer enhance their ability to write optimized JavaScript code, manage significant data volumes, and implement complex visualization algorithms with an understanding of time and space complexity, ensuring smooth interactions and responsive data displays, crucial for modern data-rich applications.

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Software Development Engineer in Test

A Software Development Engineer in Test (SDET) enhances software quality by designing, developing, and implementing automated testing frameworks and tools. This course is highly relevant for an SDET, as it builds strong problem-solving and coding skills in JavaScript, along with a deep understanding of data structures and algorithms. This expertise enables an SDET to write efficient and robust test code, effectively identify performance bottlenecks within the application under test, and design comprehensive test coverage by understanding the underlying algorithmic logic, which is crucial for ensuring product quality at top tech companies.

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Game Developer

A Game Developer creates the interactive logic, physics, and artificial intelligence within video games, bringing virtual worlds to life. This course may be quite helpful for a Game Developer, as it cultivates strong problem-solving abilities and a deep understanding of data structures and algorithms. These are fundamental for implementing efficient game mechanics, optimizing game performance, handling complex interactions between game entities, and designing sophisticated AI systems that rely on optimized search and pathfinding algorithms. The JavaScript focus could be particularly relevant for web-based games or certain game engine scripting, making this course a strong asset.

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Solutions Architect

A Solutions Architect designs high-level technical solutions and system architectures that meet business requirements, translating complex needs into actionable plans. The course may be helpful for a Solutions Architect by strengthening their foundational understanding of data structures and algorithms, which is essential for making informed decisions about system scalability, performance, and the efficient organization of data and logic within complex software solutions. A deep grasp of time and space complexity allows an architect to anticipate potential bottlenecks and design systems that are robust and maintainable, a critical skill for this often senior position.

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Research Engineer

A Research Engineer explores new technologies and methodologies, often bridging theoretical concepts with practical implementation in fields like artificial intelligence or advanced computing. This role typically requires an advanced degree, but the course may be helpful for a Research Engineer by reinforcing fundamental algorithmic and data structure knowledge. This foundation is critical for developing efficient experimental designs, optimizing computational processes for novel algorithms, and understanding the performance implications of new solutions, particularly when implementing prototypes or evaluating academic concepts to push the boundaries of technology.

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Quantitative Developer

A Quantitative Developer designs and implements complex mathematical and financial models, often in high-performance trading or risk management systems, where precision and speed are paramount. This role typically requires an advanced degree, but the course may be useful for a Quantitative Developer by providing a robust foundation in algorithmic problem-solving, efficient data structures, and complexity analysis. These skills are critical for building highly optimized computational solutions that process vast amounts of financial data quickly and accurately, even if the primary development language in finance is often different from JavaScript, as the core principles are transferable.

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Site Reliability Engineer

A Site Reliability Engineer applies software engineering principles to infrastructure and operations, focusing on building and maintaining highly reliable, scalable systems. While an SRE's primary focus often involves infrastructure as code and automation, this course may be useful by providing a solid grounding in algorithms and data structures. This knowledge helps an SRE to understand the performance characteristics of the services they manage, develop optimized automation scripts, diagnose system issues efficiently, and contribute to the design of more robust and performant services, ultimately enhancing the overall reliability of systems.

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