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Professional Machine Learning Engineer Study Guide
01
Professional Machine Learning Engineer Study Guide
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This course helps learners create a study plan for the PMLE (Professional Machine Learning Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
Course Info
Objectives
- List the domains covered on the Professional Machine Learning Engineer (PMLE) certification exam.
- Identify gaps in your knowledge and skills for each domain.
- Identify resources and learning assets available to develop your knowledge and skills.
- Create a study plan to prepare for the PMLE certification exam.
Prerequisites
Working proficiency with Python on topics covered in the Google Crash Course on Python.
Prior experience with foundational machine learning concepts and deep learning models, as well as familiarity with model evaluation, bias-variance tradeoff, overfitting, and regularization techniques are recommended.
Audience
This course is intended for individuals with a strong technical background and hands-on experience in machine learning (ML) who want to demonstrate their expertise in designing, building, and deploying machine learning solutions on Google Cloud.
Available languages
English