Computer Science Comprehensive Major: Applied Machine Learning Emphasis

Machine learning/artificial intelligence is one of the fastest growing areas in the industry, driven by the demand for computer vision, self-driving cars, large language models, data analytics, fraud detection, and many other exciting applicationsIn the Applied Machine Learning Comprehensive Major, students will take a deep dive into data analytics, machine learning algorithms, deep learning models, large language models, and other cutting-edge algorithms.   

Western students have the option to pursue the 45-credit Standard Program or one of the following Comprehensive Majors: the 63-credit Software Engineering Major, the 60-credit Information Security Major, the 65-credit Scientific Computing Major, or the 63-credit Applied Machine Learning Major.  Course work in the Applied Machine Learning Major will cover modern tools and frameworks such as OpenCV, TensorFlow, Scikit, SpaCy, and NLTK.  Students will learn to build real-world applications related to deep learning, computer vision systems, and large language models. The Applied Machine Learning Major will require the 33-credit Computer Science Core, along with the 30-credit Applied Machine Learning Major emphasis courses.   

A minimum of 63 credits is required, including the 33-credit Computer Science Core and the following: 

Computer Science Core
CS 190Computer Science I3
CS 191Computer Science II3
CS 195Database Management Systems3
CS 250Web Applications Development I3
CS 280Data Structures3
CS 330Operating Systems and Architecture3
CS 370Systems Programming in C3
CS 412Software Engineering3
CS 470Algorithms3
CS 495Senior Project3
MATH 200Discrete Mathematics3
Total Credits33
 

 

CS 220Data Analytics3
CS 303Machine Learning3
CS 385Natural Language Processing3
CS 420Computer Vision3
CS 421Neural Network Engineering3
MATH 213Probability and Statistics (GT-MA1)3
MATH 260Applied Linear Algebra3
And 9 credits of upper-level CS courses outside of the Computer Science Core/Applied Learning emphasis courses, or any of the following: CS 235, ENG 302, MATH 251, MATH 252, MATH 313, MATH 314, MATH 358, MATH 360, MATH 380.9
Total Credits30

Plan of Study Grid
Year One
FallCredits
CS 190 Computer Science I 3
Elective Elective or minor course 3
ENG 102 Writing and Rhetoric I (GT-CO1) 3
Gen Ed Arts & Humanities 3
HWTR 100 First Year Seminar 1
MATH 141
Precalculus (GT-MA1)
or Calculus I (GT-MA1)
4
 Credits17
Spring
CS 191 Computer Science II 3
CS 195 Database Management Systems 3
Elective Elective or minor course 3
Gen Ed Arts & Humanities 3
Gen Ed Social Sciences 3
 Credits15
Year Two
Fall
CS 280 Data Structures 3
CS 330
Operating Systems and Architecture
or Web Applications Development I
3
MATH 213 Probability and Statistics (GT-MA1) 3
MATH 260 Applied Linear Algebra 3
Gen Ed Natural Sciences w/lab 4
 Credits16
Spring
ENG 103 Writing and Rhetoric II (GT-CO2) 3
CS 220 Data Analytics 3
CS 303 Machine Learning 3
Gen Ed Natural Sciences w/lab 4
MATH 200 Discrete Mathematics 3
 Credits16
Year Three
Fall
CS 250
Web Applications Development I
or Operating Systems and Architecture
3
CS 385
Natural Language Processing
or Neural Network Engineering
3
Elective Elective 3
Gen Ed Social Sciences 6
 Credits15
Spring
CS 370 Systems Programming in C 3
CS 412 Software Engineering 3
CS 420 Computer Vision 3
Elective Elective 3
Gen Ed Arts & Humanities 3
 Credits15
Year Four
Fall
CS 470 Algorithms 3
CS 385
Natural Language Processing
or Neural Network Engineering
3
CS Elective CS Elective (upper-division) 3
Elective Elective 6
 Credits15
Spring
CS 495 Senior Project 3
CS Elective CS Elective (upper-division) 6
Elective Elective 3
 Credits12
 Total Credits121