OzU Machine Learning in Finance and Bioinformatics Lab 
Teaching
CS 104 Introduction to Programming
Course Description: The course aims to introduce non-CS engineers to programming in Python.
CS 201 Data Structures and Algorithms
Course Description: This course provides an overview of fundamental data structures that are used frequently in computer science. It also introduces algorithm design and complexity analysis. Topics include singly and doubly linked lists, trees, graphs, queues, heaps, hash tables, and operations performed on these structures.
CS 333 Algorithms Analysis
Course Description: Topics include Greedy/Dynamic Programming/Divide and Conquer algorithm design paradigms, Graph algorithms (minimum path, spanning tree, max flow), and intractability (NP & NPcomplete problem classes)
CS 412/512 Bioinformatics Algorithms
Course Description: Introduce Bioinformatics concepts and algorithms to students. Inform students about the most recent algorithms and tools in computational biology.
CS 440/540 Machine Learning in Finance
Course Description: Introduce students fundamental finance knowledge. Teach machine and deep learning methods within financial domain.
CS 452/552 Data Science with Python
Course Description: Introduce students data science and practical machine learning knowledge. Practice algorithms with Python.