Syllabus CSE 4095 Spring 2025
Instructor: John A. Iacovacci
john.iacovacci@uconn.edu;
Cell Phone: 917-701-6177
Lectures Tuesdays - 6:35 PM - 7:45 PM Room DWTN 239
Office Hours Remote: Upon request
Our Class Website https://uconn-sa.blogspot.com/
CSE 4095 Special Topics in Computer Science and Engineering -
Sentiment Analysis
Description
This course explores sentiment analysis of English text.
The inputs can be from financial news, broader news, and other sources.
The systems we will use include a number of NLP sentiment analysis
libraries including
BERT (Bidirectional Encoder Representations from Transformers) systems.
Learning objectives
Get working knowledge of implementing sentiment analysis using NLP libraries.
Develop skills for understanding the workings of sentiment analysis systems.
Class work
Students will be required to provide weekly status reports and hit monthly
milestones.
Work will revolve around
1. Setting up sentiment analysis engines in Python
2. Getting data to validate sentiment analysis
3. Correlating sentiment to other actions or activities
4. Extending BERT or other NLP models
Each weekly report will correspond to a grade for the week.
Reports and monthly milestones will be discussed and agreed upon in class.
General Requirements & Expectations
1. Attendance: Students are expected to attend all lectures. Attendance will be taken.
2. Make sure you check your UCONN.EDU e-mail account regularly, or have it
forwarded to an account that you use regularly. Otherwise you may miss important
announcements.
Academic Honesty
Students should refer to the Student Code (see section on Academic Integrity -
http://www.dos.uconn.edu/student_code.html) for specific guidelines.
Students with Disabilities
Students with disabilities who believe they may need accommodations in this
class are encouraged
to contact the Center for Students with Disabilities (486-2020) as soon as
possible to better ensure that such accommodations are implemented in a
timely fashion.
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