Explore systematic approaches to algorithmic problem-solving in JavaScript, including Divide and Conquer, Greedy Algorithms, Dynamic Programming, and Backtracking, with practical examples and flowcharts.
Explore the greedy algorithm paradigm, its characteristics, and applications in JavaScript. Learn when to use greedy solutions, compare them with dynamic programming, and understand their advantages and limitations.
Explore the Activity Selection Problem, a classic example of greedy algorithms, and learn how to implement it in JavaScript to select the maximum number of non-overlapping activities.
Explore Huffman coding, a greedy algorithm for lossless data compression, and learn to implement it in JavaScript. Understand how to construct Huffman trees, generate prefix codes, and analyze its efficiency.
Explore the Coin Change Problem using Greedy Algorithms in JavaScript, understand its applications, limitations, and implement solutions with practical examples.
Explore heuristic methods in JavaScript, including greedy algorithms, local search, simulated annealing, and genetic algorithms, to solve complex problems efficiently.
Learn how to effectively analyze problems to select the most suitable algorithm design techniques in JavaScript, focusing on problem characteristics, constraints, and systematic approaches.
Explore how combining algorithm design techniques can leverage their strengths to solve complex problems efficiently. Learn through examples and practical implementations in JavaScript.