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Course Description

In this course, students use Python to apply unsupervised Machine Learning algorithms to unlabeled data to ascertain if anomalies are present in real-time streaming data being generated by a piece of industrial machinery. Students also query and analyze a Neo4J Graph Database to ascertain hidden relationships among a large set of chatbot data to better understand how chatbots and Natural Language Processing are used in AI.

Course Outline

This course will cover the following topics:

  • Unsupervised Learning Concepts
  • Clustering
    • K-Means Clustering
    • Hierarchical Clustering
    • Probabilistic Clustering
  • Data Compression
    • Principal Component Analysis (PCA)
    • Singular-Value Decomposition (SVD)

Learner Outcomes

This is a comprehensive course in understanding the key concepts and application in unsupervised learning such as clustering and dimension reductions. In addition, learners will apply these skills to relevant industry business situations.

Successful completion of this course entitles the student to The Intelligence Factory Skillset Certification in the following areas:

  • Unsupervised Machine Learning

This course also provides you the skills and concepts needed to complete the TIF Certification One for a Machine Learning Engineer.

Prerequisites

Basic knowledge of Python programming skills.

Duration

30 Hours | 5 days or 10 nights

Applies Towards the Following Certificates

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Thank you for your interest in this course. Unfortunately, the course you have selected is currently not open for enrollment. Please complete a Course Inquiry or call 314-977-3226 so that we may promptly notify you when enrollment opens.