Machine Learning Rapid Prototyping with IBM Watson Studio
Master AutoAI in IBM Watson Studio. Learn automated ML pipelines for rapid model prototyping and deployment.
Master AutoAI in IBM Watson Studio. Learn automated ML pipelines for rapid model prototyping and deployment.
Explore the cutting-edge of AutoAI with IBM Watson Studio in this intermediate-level course. Learn to create end-to-end automated machine learning pipelines, focusing on rapid prototyping of models. Discover automated techniques for data preparation, model selection, feature engineering, and hyperparameter optimization. Gain hands-on experience with AutoAI-generated Python notebooks, working on real-world datasets. Ideal for practicing Data Scientists, this course bridges the gap between traditional ML workflows and automated AI technologies, enabling you to leverage Watson Studio's capabilities for efficient, high-performance model development.
3.9
(11 ratings)
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What you'll learn
Understand the landscape of AutoAI technologies and their applications
Master the use of Watson Studio's AutoAI experiment tool for rapid prototyping
Learn automated techniques for data preparation and model selection
Explore advanced feature engineering methods using the Cognito algorithm
Gain proficiency in automated hyperparameter optimization techniques
Develop skills in evaluating and deploying AutoAI-generated solutions
Skills you'll gain
This course includes:
111 Minutes PreRecorded video
13 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 4 modules in this course
This course focuses on Machine Learning rapid prototyping using IBM Watson Studio's AutoAI capabilities. Learners will explore automated techniques for data preparation, model selection, feature engineering, and hyperparameter optimization. The course covers the creation of end-to-end automated pipelines, working with AutoAI-generated Python notebooks, and hands-on experience with real-world datasets. Participants will learn to evaluate and deploy AutoAI-generated solutions, gaining practical skills in leveraging automated AI technologies for efficient model development and deployment.
Building a Rapid Prototype with Watson Studio AutoAI
Module 1 · 2 Hours to complete
Automated Data Preparation and Model Selection
Module 2 · 2 Hours to complete
Automated Feature Engineering and Hyperparameter Optimization
Module 3 · 2 Hours to complete
Evaluation and Deployment of AutoAI-generated Solutions
Module 4 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructors
Digital Content Delivery Lead at IBM with Extensive Experience in Information Technology Education
Mark J. Grover is a Digital Content Delivery Lead at IBM, specializing in the creation and delivery of online educational content. Before joining IBM, he was a full-time professor of computer technology at Cape Fear Community College in Wilmington, NC, where he coordinated the Information Security program and taught various courses including Computer Security and Network Administration. Grover has over 25 years of experience in information technology and has received accolades such as the Cisco Instructor of Excellence award and the Award for Excellence in Innovation from the University of North Carolina Wilmington. He is passionate about outdoor activities like camping and mountain biking, and enjoys spending time with his family.
Data Scientist at IBM Specializing in Machine Learning and Rapid Prototyping
Meredith Mante is a Data Scientist at IBM, specializing in machine learning and data analysis. She teaches the course Machine Learning Rapid Prototyping with IBM Watson Studio, which focuses on creating end-to-end automated pipelines using IBM's AutoAI technology. This course guides learners through the process of rapid prototyping, allowing them to build and optimize machine learning models efficiently. With a hands-on approach, participants gain practical experience in utilizing IBM Watson Studio to automate model selection, feature engineering, and hyperparameter tuning. Meredith's expertise in data science and her commitment to education help equip students with the skills necessary to excel in the rapidly evolving field of AI and machine learning.
Testimonials
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3.9 course rating
11 ratings
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