AWS Certified Machine Learning - Specialty
AWS Certified Machine Learning - Specialty
ISBN: 0138283133 | .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 4h 26m | 603 MB
Instructor: Milecia McGregor
ISBN: 0138283133 | .MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 4h 26m | 603 MB
Instructor: Milecia McGregor
Video description
Learn the techniques and approaches to successfully pass the AWS Certified Machine Learning - Specialty Exam with hands-on exercises.
Getting the AWS Certified Machine Learning - certification highlights your versatility as an ML engineer. Usually, ML engineers focus on handling data and building models, so if you know can use cloud tools, it makes you an even more valuable as an MLOps engineer. You’ll be able to ingest your own data, get through the feature engineering process, train and evaluate models, and deploy them to where they will be consumed. This certification shows that you know how to do full-stack ML development.
In this series of videos, author Milecia McGregor shares a mix of slides and demonstrations in AWS, along with some examples in Visual Studio with Python. It’s just what you need to learn to pass the exam. It includes an overview of concepts with hands-on work using AWS tools like Kinesis and EMR.
Skill Level:
Intermediate
Learn How To:
- Learn effective tips and techniques for passing the AWS Certified Machine Learning - Specialty exam
- Identify and implement data ingestion solutions with Kinesis
- Evaluate ML models
- Deploy ML models with AWS tools
Course requirement:
- Prerequisites: Knowledge of how to use various AWS tools to deploy ML models into different environments
- Knowledge of.data engineering principles and model training and evaluatio
Who Should Take This Course:
Job titles: ML engineer, DevOps engineer, Aspiring ML engineer
AWS Certified Machine Learning - Specialty
