Problem Solving Using Backtracking Algorithm Design Paradigm

This course is designed to provide a comprehensive understanding of backtracking algorithms, an essential problem-solving technique in computer science and algorithm design and to learn fundamental techniques for designing and analyzing backtracking algorithms. Backtracking is particularly useful for solving problems that involve making a sequence of decisions to reach a solution, where each decision depends on the previous ones. Throughout the course, students will understand the basic principles and concepts behind backtracking algorithms and students will explore the recursive nature of backtracking and its connection to problem-solving along with theoretical foundations, practical applications, and implementation details of backtracking algorithms.  In this course, real-world applications where backtracking is employed is examined, such as in artificial intelligence, robotics, scheduling, and network design. The skills acquired in this course are valuable for anyone pursuing a career in computer science, data science, artificial intelligence, or algorithm design. Students can apply backtracking to solve problems involving combinatorial optimization, constraint satisfaction, and decision problems. By the end of this course, students will have a solid foundation in backtracking algorithms, enabling them to tackle complex problems, make informed design decisions, and apply this powerful technique across various domains in computer science and implement backtracking algorithms in popular programming languages, emphasizing code readability and efficiency.