CNIT 483: Applied Machine Learning

0 or 3 credits

Fall 2025 Lecture Laboratory Upper Division
Data from
Fall 2025
last updated 8/18/2025

In the past decade, we have observed the expeditious evolution and tremendous applications of machine learning, such as unmanned vehicle, autonomous language translation, and smart healthcare. This course will introduce both the fundamental knowledge and design/application insights of machine learning techniques via a series of hands-on real-world examples. The overall aim is to provide the students with a good understanding of machine learning technologies, building machine learning models, and applying machine-learning technologies to address real-world problems. In this course, students will also have an opportunity to explore the cutting-edge machine learning technologies, such as deep learning, adversarial attacks, and meta learning, and develop their own machine learning-based solutions.

Learning Outcomes

1Demonstrate both the fundamental knowledge and design/application insights of the state-of-the-art machine learning techniques.

2Implement machine learning models.

3Apply machine learning techniques to solve real-world problems.

Course CNIT 483 from Purdue University - West Lafayette.

Prerequisites

Restrictions

Program Comp Info Tech-BS

GPA by professor

3.7Other terms
Su Sun(Spring 2022)

No grades available

Hong...(Fall 2022)

No grades available

Go E...(Fall 2023)

No grades available

Mutu...(Spring 2024)

No grades available

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Jin Kocsis

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3:30 pm
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Jin Kocsis

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9:30 am
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Jin Kocsis

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11:30 am
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Jin Kocsis

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3:30 pm
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Jin Kocsis

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1:30 pm
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Jin Kocsis

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3:30 pm
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CNIT 483: Applied Machine Learning