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Professional Machine Learning Engineer Study Guide
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Professional Machine Learning Engineer Study Guide
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.
Información del curso
Objetivos
- 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.
Requisitos previos
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.
Público
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.
Idiomas disponibles
English
¿Qué debo hacer cuando finalice este curso?
Después de finalizar el curso, puede consultar contenido adicional en su ruta de aprendizaje o explorar el catálogo de aprendizaje.
¿Qué insignias puedo obtener?
Cuando complete un curso, obtendrá una insignia de finalización. Puede ver las insignias en su perfil y compartirlas en sus redes sociales.
¿Le interesa realizar este curso con uno de nuestros socios a pedido?
Explore el contenido de Google Cloud en Coursera y Pluralsight.
¿Prefiere aprender con un instructor?