Machine Learning Foundations and Practice

This course covers fundamental concepts, methods, and tools for machine learning using Python. We will emphasize a learn by doing approach with a heavy reliance upon exercises and assignments in Python and utilizing modern ML packages. Jupyter notebooks will be used as a framework for combining machine learning models with notes documenting the design and development of experiments. You will learn the basics of data representation and visualization, as well as common, well-established practices for characterizing and classifying data. You will also learn to develop and apply modern machine learning models and, most importantly, understand the process that underlies the design and conduct of effective machine learning experiments.

Important Note about Communication: Unless it is a sensitive matter, all emails regarding the class should be forwarded to the email id compsci_cs345@colostate.edu. This will be actively monitored by the TAs and the instructor. We will also have a teams channel for the class that will be monitored.

2026 Spring Semester Details

Instructor(s)

Instructor

Sarath Sreedharan

Office

CSB 466

Email

ssreedh3@colostate.edu

Office Hours

TR 12:30 – 1:30 (in-person and online via teams.

Class Schedule

Section

Schedule

Location

Instructor

001

TR 11:00a – 12:15p

TILT 221

Sreedharan

801

Async

Online

Sreedharan

TA Office Hours

Septia RaniTuesday 4 PM-5 PM (CSB 120)
Tuesday 8 PM-9 PM (CSB 120)
Thursday 4 PM-5 PM (CSB 120)
Sunday 7 PM-8 PM (Online)
Trisha GhaliTuesday 4 PM-5 PM (CSB 120)
Tuesday 8 PM-9 PM (CSB 120)
Thursday 4 PM-5 PM (CSB 120)
Sunday 7 PM-8 PM (Online)
ArtemioTuesday 4 PM-5 PM (CSB 120)
Tuesday 8 PM-9 PM (CSB 120)
Thursday 4 PM-5 PM (CSB 120)
Sunday 7 PM-8 PM (Online)
CoenTuesday, Thursday:9:30AM- 11:30AM( CSB 120)
Friday: 11:00 AM – 1:00 PM ( CSB 120)
ZiquiMonday 9 AM-11 PM (CSB 120) Wednesdays 2 PM-4 PM (CSB 120)