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Machine Learning Fundamentals: Principles and Applications
Microcredential
COURSE DESCRIPTION
Description:
Pay just $99 with discount code AI99
This select promotional offer is available for a limited time only and is subject to eligibility and availability. Additional terms may apply.
Course Description: This course provides in-depth conceptual explanation of supervised and unsupervised machine learning algorithms and how to implement them to address real-world problems.
Prerequisites: None
Learning Outcome:
– Assess and understand the core principles, applications, and limitations of machine learning, distinguishing its role from traditional programming
– Analyze a variety of supervised and unsupervised machine learning algorithms using prominent frameworks
– Integrate machine learning knowledge to address real-world challenges by choosing appropriate algorithms and techniques
| Module |
Topic & Readings |
| Module 1 |
Intro to Machine Learning
Understand and Build Machine Learning Models |
| Module 2 |
Supervised Machine Learning Algorithms
Logistic and Linear Regression |
| Module 3 |
Understand Machine Learning Algorithms
Applications of Clustering |
| Module 4 |
Capstone Project |
Faculty: Jin Kocsis
Registration in this course is subject to the Purdue University Online Non-Credit Policies.
SECTION DETAILS
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Course Section
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Add to Cart
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Course:
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POL 439-00
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Term:
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26FY
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Section Number:
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2
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Schedule Number:
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29237
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Instructor(s):
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Staff
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Notes:
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Pay just $99 with discount code AI99
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