Special Topics in Information Science: Introduction to Machine Learning

Program: MSIS/PhD
Course Areas
Data Science/Engineering/Analytics

Catalog Description

Cutting edge concepts employed in machine learning to solve artificial intelligence problems. Students will learn the theory behind a range of machine learning tools and practice applying the tools to, for example, textual data (natural language processing), visual data (computer vision), and the combination of both textual and visual data.

Instructor Description

This course will cover fundamental concepts in Machine Learning (ML). The course will provide conceptual and practical knowledge on a wide range of modern machine learning algorithms; including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), reinforcement learning & deep learning models (CNN, RNN, Autoencoders & Transformers) and also introduce the importance of Prompt Engineering and Retrieval Augmented Generation. The goal is for students to be comfortable and confident in machine learning concepts and have the ablity to build machine learning model solution to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, this is a great place to start.

Prerequisites

Graduate standing.
Skills and Knowledge
Python Programming
Large Language Models And Its Application
Machine Learning Packages Like Tensorflow And Scikit-learn
Topics and Concepts
Classic Machine Learning & Deep Machine Learning Algorithms
ML Evaluation & Prompt Engineering
Ethics In AI

Scheduled and Upcoming Classes for this Course

Class Name Semester Day(s) Start Time(s) End Time(s) Building Room
INF 385T: Special Topics in Information Science: Introduction to Machine Learning

Jyothi Vinjumur

Fall Term 2025
  • Monday
  • Wednesday
  • 6:00 pm
  • 6:00 pm
  • 7:30 pm
  • 7:30 pm
  • UTA
  • WEB
  • 1.212

Past Classes for this Course

Class Name Semester Day(s) Start Time(s) End Time(s) Building Room
INF 385T: Special Topics in Information Science: Introduction to Machine Learning

Spring Term 2024
  • Tuesday
  • Thursday
  • 05:00 PM
  • 05:00 PM
  • 06:30 PM
  • 06:30 PM
  • UTA
  • WEB
  • 1.210A
INF 385T: Special Topics in Information Science: Introduction to Machine Learning

Jyothi Vinjumur Syllabus

Fall Term 2024
  • Tuesday
  • Thursday
  • 05:00 PM
  • 05:00 PM
  • 06:30 PM
  • 06:30 PM
  • UTA
  • WEB
  • 1.210A
INF 385T: Special Topics in Information Science: Introduction to Machine Learning

Jyothi Vinjumur Syllabus

Spring Term 2023
  • Monday
  • Tuesday
  • 04:30 PM
  • 06:30 PM
  • 06:00 PM
  • 08:00 PM
  • UTA
  • WEB
  • 1.210A
INF 385T: Special Topics in Information Science: Introduction to Machine Learning

Jyothi Vinjumur Syllabus

Spring Term 2022
  • Tuesday
  • 6:30 PM
  • 9:30 PM
  • UTA
  • 1.210A
INF 385T: Special Topics in Information Science: Introduction to Machine Learning

Jyothi Vinjumur Syllabus

Fall Term 2022
  • Tuesday
  • Thursday
  • 06:30 PM
  • 06:30 PM
  • 08:00 PM
  • 08:00 PM
  • UTA
  • WEB
  • 1.210A