Students learn to analyze algorithm efficiency and select appropriate abstract data types. The course covers data structure tradeoffs and the design of structures for operations like insertion and deletion. Advanced topics include combining structures for complex problem-solving and predicting algorithm behavior through code analysis. Students gain expertise in error detection and resolution, ensuring implementations align with intended outcomes. The course culminates in tailored designs of data structures and algorithms.

This college course immerses students in essential computer science topics such as C programming, data representation, assembly language programming, Boolean algebra, digital logic design, processor design, cache design, and main memory design. Students gain a strong foundation in these areas, allowing them to critically analyze developments in the field. Tailored projects prepare them for academia, software industry, or startups, ensuring a deep understanding of core principles and practical skills vital for diverse technology careers.

This course covers algorithm complexity, methods to express and compare algorithms' complexities in worst and average cases, and determining lower bounds on algorithm classes. Students learn to analyze and verify, applying these techniques to algorithms like search, sort, graph, and language problems. The course covers problems such as knapsack, satisfiability, and traveling salesman, exploring NP-complete classification and implications. Additionally, students study approximation algorithms, honing their skills in addressing complex computational challenges efficiently and accurately.

This course aims to equip students with foundational skills and knowledge in Python programming. The curriculum focuses on building a fundamental understanding of the Python language, covering essential functionalities such as working with lists, conditional statements, loops, and file management (opening/writing to files). Upon completion, students are expected to showcase a grasp of basic Python grammar, algorithms, data structures, computational thinking, and practical experience in developing a program from inception. The acquisition of these skills is facilitated through various course activities and assignments designed to reinforce hands-on learning.