KIET-LMS

The course on Algorithms introduces students to the fundamental principles of problem-solving and efficient computation. It covers the design and analysis of algorithms, including asymptotic complexity, sorting and searching techniques, graph algorithms, and advanced paradigms such as divide and conquer, greedy methods, dynamic programming, and backtracking. The course also explores hashing, string matching, and concepts of NP-completeness, emphasizing both theoretical understanding and practical applications. By the end of the course, students gain the ability to analyze problems, design optimized solutions, and apply algorithms effectively in real-world scenarios.

Objective - This course introduces the foundational concepts of Machine Learning and its integration into modern Generative AI systems. It emphasizes the application of supervised, unsupervised, and deep learning models – including transformers and LLMs – along with practical exposure to prompt engineering, generative models, and ethical AI practices.