CSC 5120 - Software Development for Machine Learning

4 lecture hours 0 lab hours 4 credits

Course Description
The objective of this course is to develop practical software engineering skills combined with application of data structures and algorithms concepts to enable students to implement non-trivial software projects. This course is designed for students who have some programming experience but have not had comprehensive exposure to developing intermediate-sized programs composed of multiple modules; implementing and analyzing data structures and basic algorithms; and other related computing topics. Upon completion of the course, students will be able to use Python and related libraries to implement non-trivial software for data and computational challenges that will prepare them to succeed in data science and machine learning coursework as well as other programming classes.
Prereq: CSC 1110 or CSC 1310 or instructor consent
Note: This course is open to qualified undergraduate students.

Course Learning Outcomes
Upon successful completion of this course, the student will be able to:

Design and implement software that uses logic and looping to solve problems
Implement logic for reading, parsing, and writing common text file formats
Use data structures such as strings, lists, sets, dictionaries, and tuples to solve data processing and algorithmic problems
Write software organized into multiple classes and modules
Use a version control tool (i.e., Git) to share and collaborate on software development projects
Document the implementation of software systems
Write automated tests for pre-conditions and post-conditions using a testing framework
Use recursion to solve a given problem
Design and implement linked lists and trees to store and access data and state information
Implement and apply tree algorithms to solving search and planning problems
Use exact tracing to quantify and predict the runtime of a given algorithm
Apply the concepts of asymptotic complexity to accurately characterize the Big-O of a given algorithm

Prerequisites by Topic

Programming experience with a high-level language

Course Topics

Introduction to procedural and object-oriented Python
Python data types: strings, lists, sets, dictionaries, and tuples
Loading and manipulating data stored in tabular or semi-structured text files
Implementing and using classes in Python
Interactions with Git repositories
Writing tests with assertion statements and the Python unittest library
Linked lists and trees
Recursion
Search and planning problems in AI such as playing games
Applications of tree data structures and algorithms to solve search and planning problems

Coordinator
Dr. Jonathon Flynn

Add to Portfolio.

Close Window