AWS Healthcare Data Analytics For Beginners

By completing this course, you will learn about:

• Data Security and Privacy, including some of the key standards and regulations.

• Exploratory data analysis allowing you to gain a deeper understanding of your datasets, including:

  • Dataset schemas

  • Value distributions

  • Missing values

  • Cardinality of categorical features

• Demographic dataset analysis

• Data Analytics

• Machine Learning

  • Understand what Machine Learning is and what it offers

  • Understand the benefits of using the Machine Learning

  • Understand business use cases and scenarios that can benefit from using the Machine Learning

  • Understand the different Machine Learning training techniques

  • Understand the difference between Supervised and Unsupervised training

  • Gain full visibility into your AWS application code performance with end-to-end tracing, profiling, and App Analytics

  • Identify critical issues quickly with real-time service maps and alerts on code-level + service-level performance issues

  • Test hypotheses in seconds by overlaying events onto time-synchronized graphs

    
    

  
  

  We will start with an overview of Data Science and Analytics concepts to give beginners the context they need to be successful in the course. The second part of the course will focus on the AWS offering for Analytics, this means, how AWS structures its portfolio in the different processes and steps of big data and data processing.

  • In this course, we will also explore the Analytics tools provided by AWS, including Elastic Map Reduce (EMR), Data Pipeline, Elasticsearch, Kinesis, Amazon Machine Learning.

Who This Course Is For:

• Data Scientists

• Data Engineers

• Machine Learning Engineers

• Big Data Architects

• Healthcare Professionals

• Solutions Architects

• Cloud Engineers

• DevOps Engineers

• Cybersecurity Analysts

• Network Security Engineers

• System Administrators

• Programmers