Data Structures & Algorithms

Curriculum

• This course introduces the various data structures & algorithm techniques to be applied to the data to make it fit for further analysis. The course is divided into 7 modules which cover the important topics for data structures & algorithms:
• The first one is introduction & efficiency which talks about algorithm efficiency, complexity notation.
• Next one is list based on collections. This discusses how processes such as creation, insertion, deletion, and manipulation can be applied on a list, string, array, linked list, stack, and queues.
• The third module is searching & sorting. This module describes algorithms such as binary search, bubble sort, merge sort, quick sort, and recursion.
• The fourth module, maps & hashing, explores maps, hashing, and collision algorithms.
• The fifth module, trees, describes binary search tree, advanced tree, and their different operations.
• The sixth module, graphs, explores different operations of graphs.
• The seventh module, the case study, talks about the shortest path problem, dynamic programming, and traveling salesman problem.
• A Machine Learning engineer needs to preprocess the data as a part of EDA, write algorithms to build models. So, a good foundation in the DSA course is essential.