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Quickly Build and Train Machine Learning Models with IBM AutoAI
Course Description
Overview
Quickly build and train machine learning models with Watson AutoAI aims to familiarize data science and analytics professionals with the fundamentals of theWatson Studio's AutoAI tool. The course walks users through the process of creatingIBM Cloud projects, and building and evaluating AutoAI experiments for various supervised machine learning use cases.
The lab environment for this course uses IBM Cloud.
Objectives
- Set up an IBM Cloud Account and project and add and manage associated resources
- Identify potential machine learning use cases applicable to AutoAI
- Differentiate problem types relevant for AutoAI experiments (Classification, Regression, Time Series)
- Configure settings for various AutoAI experiments
- Evaluate pipelines and models that are produced by AutoAI experiments
- Recognize deployment strategies for AutoAI models
Audience
This course is designed for data analysts, data scientists, and machine learning specialists.
Prerequisites
- IBM Cloud access
- Knowledge of supervised machine learning use cases
- Knowledge of Python code in notebook environments
- Basic knowledge of machine learning evaluation metrics
Topics
- Course introduction
- Introducing IBM Cloud
- What is AutoAI?
- Machine learning with AutoAI: Classification
- Machine learning with AutoAI: Regression
- AutoAI deployments at a glance
- Machine learning with AutoAI: Time series
- Fairness evaluation in AutoAI machine learning models
Recognition
When you complete the Instructor-Led version of this course, you will be eligible to earn a Training Badge that can be displayed on your website, business cards, and social media channels to demonstrate your mastery of the skills you learned here.
Learn more about our Badge Program →Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
- Learn more about e-Learning
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