Algorithm design and analysis is an area where creativity and logic converge to solve complex problems efficiently. Besides correctness and efficiency, often elegance in the solution contributes to ease of implementation. Algorithms are the heart and soul of computer science, acting as the driving force behind every digital innovation we experience today. They power search engines, enable social media, optimize supply chains, and revolutionize healthcare, finance, and countless other domains.

Algorithms help us to transform abstract ideas into concrete solutions. They are the secret sauce that transforms raw data into valuable insights, paving the way for technological advancements and improving the quality of our lives. Beyond its practical applications, algorithm design challenges us to think critically, reason logically, and develop a keen intuition for problem-solving. It encourages us to embrace efficiency and elegance in our solutions, urging us to balance trade-offs and make strategic choices to optimize performance.

This is a tutorial-style course with a focus on problem-solving using efficient algorithms and data structures. The course will be useful for those preparing for software interviews since algorithms and data structure design often form a core part of such interviews. Moreover, students with a general interest in algorithms, data structures, and programming and interested in honing their problem-solving skills, will find this course useful.

Format of the course:

Each class will be 90 minutes long. There will be an introductory class, followed by 12 problem-solving classes. Each day a set of problems will be discussed. Solutions considering different algorithmic strategies and efficiency will be discussed. For sample problems, see https://www.youtube.com/@elahetech our YouTube channel.

Topics for the classes:

• Introduction
• Arrays -- Part I
• Arrays -- Part II
• Stacks and Queues -- Part I
• Stacks and Queues -- Part II
• Heaps
• Sorting and Searching -- Part I
• Sorting and Searching -- Part II
• Dynamic Programming -- Part I
• Dynamic Programming -- Part II
• Greedy Algorithms 
• Graph Algorithms and Shortest Paths
• Bitwise Algorithms