A Practical Guide to Algorithms with JavaScript

• Understand and apply key algorithmic concepts like time and space complexity, recursion, and divide-and-conquer strategies.
• Learn to analyze algorithms using Big O notation to evaluate performance.
• Gain practical experience in solving common algorithm problems, such as sorting and searching, with JavaScript.
• Explore optimization techniques, including caching and memoization, to improve algorithm efficiency.
• Discover dynamic programming and how to implement solutions for complex problems.

This course offers a practical approach to learning algorithms with JavaScript, focusing on real-world applications and common interview questions. Led by Bianca Gandolfo, it covers essential topics like space and time complexity, recursion, sorting algorithms (merge sort, quicksort), and dynamic programming. You'll gain hands-on experience in solving problems using techniques like divide-and-conquer and memoization, making you better prepared for both day-to-day development and coding interviews.

• JavaScript developers preparing for technical interviews.
• Developers looking to strengthen their understanding of algorithms and data structures.
• Anyone seeking to improve their problem-solving skills using JavaScript.

• Basic understanding of JavaScript.
• Familiarity with fundamental programming concepts like loops and functions.

Introduction to Algorithms
Understand the importance of algorithms and how to analyze their performance using Big O notation.

Optimization Techniques
Learn how to optimize algorithms through caching and memoization, improving both time and space complexity.

Recursion and Divide-and-Conquer
Explore recursive techniques and divide-and-conquer strategies, implementing algorithms like merge sort and quicksort.

Greedy Algorithms and Dynamic Programming
Get introduced to greedy algorithms and dynamic programming, learning how to solve complex problems with these techniques.