Become a Machine Learning Engineer

Description

In this course, you will :

• AWS SageMaker teaches high-level concepts about machine learning.
• Create machine learning workflows that begin with data cleaning and feature engineering and progress to evaluation and hyperparameter tuning.
• You will create new ML workflows using advanced models such as XGBoost and AutoGluon.
• Discover how to build general machine learning workflows on AWS.
• The course will begin with an overview of the general principles of machine learning engineering.
• Learn how to use SageMaker to train, deploy, and evaluate a model.
• Discover how to build a machine learning workflow on AWS using tools such as Lambda and Step Functions.
• Learn how to use Amazon SageMaker to train, fine-tune, and deploy deep learning models.
• Discover advanced neural network architectures such as Convolutional Neural Networks and BERT, as well as how to tune them for specific tasks.
• Learn about Amazon SageMaker, and then apply what you've learned in SageMaker Studio.

Syllabus :

• Introduction to Machine Learning
• Developing Your First ML Workflow
• Deep Learning Topics within Computer Vision and NLP
• Operationalizing Machine Learning Projects on SageMaker