AWS Certified Machine Learning – Speciality

Course Overview:

This course is for individuals who seek an overall understanding of the Amazon Web Services (AWS) Cloud, independent of specific technical roles. You will learn about AWS Cloud concepts, AWS services, security, architecture, pricing, and support to build your AWS Cloud knowledge. This course also helps you prepare for the AWS Certified Cloud Practitioner exam.

Prerequisite:

• • Associate-level knowledge of AWS services such as EC2
  • Some existing familiarity with machine learning
  • An AWS account is needed to perform the hands-on lab exercises

Audience:

Individuals who perform a development or data science role and have more than one year of experience developing, architecting, or running machine learning/deep learning workloads in the AWS Cloud

Topic 1: Data Engineering

• Create data repositories for ML
• Identify and implement a data ingestion solution
• Identify and implement a data transformation solution

Topic 2: Exploratory Data Analysis 

• Sanitize and prepare data for modeling
• Perform feature engineering
• Analyze and visualize data for ML

Topic 3: Modeling

• Frame business problems as ML problems
• Select the appropriate model(s) for a given ML problem
• Train ML models
• Perform hyperparameter optimization
• Evaluate ML models

Topic 4: Machine Learning Implementation and Operations

• Build ML solutions for performance, availability, scalability, resiliency, and fault tolerance
• Recommend and implement the appropriate ML services and features for a given problem
• Apply basic AWS security practices to ML solutions
• Deploy and operationalize ML solutions