This is a completely free, self-paced course that individuals can start at a time of their choice.

Algorithms: Design and Analysis, Part 2! Serving as the backbone of computer science, algorithms possess extensive practical applications and intellectual depth. This course serves as an entry point for learners with some programming experience, offering a rigorous yet accessible exploration of algorithms. The emphasis lies on fostering a holistic understanding and grasping the broader concepts rather than delving into intricate mathematical details or low-level implementation. 

Part 2 delves into specific topics such as greedy algorithms (covering scheduling, minimum spanning trees, clustering, and Huffman codes), dynamic programming (encompassing knapsack problems, sequence alignment, optimal search trees, and shortest paths), and NP-completeness, unraveling its implications for algorithm designers. The course also addresses the analysis of heuristics and local search. Mastery of algorithmic fundamentals is achieved through diverse assessments.

This self-paced course accommodates diverse learning styles, ensuring a comprehensive understanding of algorithmic principles. Embark on this educational adventure to deepen your algorithmic expertise and refine your problem-solving skills.