Overview
Want to know about Vertex AI Feature Store? Want to know how you can improve the accuracy of your ML models? What about how to find which data columns make the most useful features? Welcome to the Feature Engineering course offered by Coursera in partnership with Google Cloud, where we discuss good versus bad features and how you can preprocess and transform them for optimal use in your models.
What you will learn
Use the Vertex AI Feature Store
Describe how to move from raw data to features
Perform Feature Engineering in BigQuery ML and Keras
Preprocess features using Apache Beam and Cloud DataFlow
Use tf.Transform
Get more details
Visit programme websiteProgramme Structure
Courses include:
- Vertex AI Feature Store
- Raw Data to Features
- Feature Engineering
- Preprocessing and Feature Creation
- Feature Crosses - TensorFlow Playground
- TensorFlow Transform
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
- Self-paced
Disciplines
Industrial & Systems Engineering Electronics & Embedded Technology Machine Learning View 18 other Short Courses in Industrial & Systems Engineering in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Intermediate Level
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.