Advanced Computing and Machine Learning

Quarters
Winter Open
Location
Olympia
Class Standing
Sophomore
Junior
Senior
Richard Weiss
Paul Pham

The goal of this program is for you to learn the concepts and skills that are part of advanced work in computer science.  This program will explore both theory and practice. It is designed for advanced computer science and mathematics students and anyone with a strong interest in computer science and how to apply it to other disciplines.

This program will explore current themes in computer science. The program covers a selection of topics from machine learning, database systems and data analytics, Web applications, and formal language theory. These topics are offered in several 4-credit threads each quarter. We will explore these threads through lectures, programming labs, workshops, and seminars.

In winter, a thread on Machine  Learning (4 credits) will explore topics in the rapidly changing field of machine learning as they relate to modern AI and data. The topics will include decision trees, support vector machines, neural networks, and regression. A thread in Web Programming (4 credits) will cover topics such as: routing, models, views, controllers, entity framework. The thread on database systems (4 credits) will be about collecting, analyzing and visualizing data. Students who would like to take 16 credits of upper division computer science in winter can also take the course Network Security or work on a project.

In spring a thread in Reinforcement Learning (4 credits) will cover the theory and application of Monte Carlo methods, dynamic programming and temporal difference learning.  The thread on formal language theory (4 credits) is about models for computing and programming languages. The thread on data analytics (4 credits) is the intersection of database systems and data mining. It will apply theory learned in machine learning and database systems.

This full-time daytime program will have some components taught on the Olympia campus. Students who are interested in participating fully remotely should contact the faculty to discuss that option.

Anticipated Credit Equivalencies:

Winter

4 - Machine Learning

4 - Web Programming

4 - Database Systems

Spring

4 - Formal Language Theory

4 - Data Analytics

4 - Reinforcement Learning

Registration

Students are expected to have coursework in discrete math, computer architecture, data structures, and one year of computer programming. These prerequisites are covered by completion of Computer Science Foundations and Data Structures and Algorithms, or equivalent courses elsewhere. Please contact Richard Weiss (weissr@evergreen.edu) if you have some but not all of the prerequisites to see if there are parts of the program you can take, or if you are unsure if you meet the prerequisites.

Signature Required

Students should email the faculty member, Richard Weiss ( weissr@evergreen.edu ) with a brief statement describing how they have met the prerequisites.

Academic Details

Computer Science, including software development, Web development, data science, and IT.

12

variable credit options are available upon a space-available basis. For more information, contact Richard Weiss ( weissr@evergreen.edu ). In particular, students who are taking the cybersecurity certification can enroll for 8 credits in spring.

41
Sophomore
Junior
Senior

All 12 credits of the work in this program are designed to be upper-division math/science. Students who successfully complete the program requirements will earn upper-division credit in computer science.

Schedule

Winter
2025
Open
Spring
2025
Signature
Hybrid (W)
Hybrid (S)

See definition of Hybrid, Remote, and In-Person instruction

Day
Schedule Details
Evans Hall 2610 - Mac Lab
Olympia