AWS Healthcare Data Analytics For Beginners

Introduction to AWS Healthcare Data Analytics
Rating: 3.9 out of 5 (18 ratings)
685 students
English
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Healthcare Data Security
Important elements of Health Insurance Portability and Accountability Act Rules (HIPAA)
EHR Data Security and Privacy
Machine Learning
Data Analytics
Administrative, physical, and technical safeguards to ensure the confidentiality, integrity, and availability of electronic protected health information
Exploratory data analysis
Demographic dataset analysis
AI and Electronic Healthcare Data (EHR)
Importance of Data Privacy and Security From a Patient, Provider and Data User Perspective
Storing and Accessing PHI Data
Importance of EDA
Dataset Schema Analysis
Value Distributions
Missing Values and Outliers
Data Analytics tools provided by AWS
Elastic Map Reduce (EMR)
Data Pipeline
Elasticsearch
Kinesis
Amazon Machine Learning
QuickSight
Data Science and Analytics concepts
Steps of Big Data and Data Processing
Databases

Requirements

  • Basic Computer Knowledge

Description

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

Who this course is for:

  • Beginners

Course content

10 sections56 lectures41m total length
  • Introduction
    00:37

Instructor

AWS DevSecOps Engineer
Charles Smith
  • 3.7 Instructor Rating
  • 224 Reviews
  • 15,828 Students
  • 10 Courses

Charles Smith, AWS DevSecOps Engineer, Chief Cybersecurity Content Creator, Cyber Coastal

- AWS Certified Solutions Architect

- AWS Certified DevOps Engineer

- AWS Certified Machine Learning Specialist

- AWS Certified Security Specialist

- AWS Certified Advanced Networking Specialist

- AWS Certified Big Data Specialist

- Cisco Certified Network Professional

- Cisco Certified Network Professional, Security

- Palo Alto Networks Certified Security Engineer

- Juniper Networks Certified Professional, Security

- Juniper Networks DevOps & Automation Specialist

- CompTIA Advanced Security Practitioner

- CompTIA Cybersecurity Analyst