Health Informatics
Offered By: Yale University via Coursera
Course Description
Overview
Health informatics (HI) is an in demand field comprising applied research and the practice of informatics across clinical and public health domains. Informatics researchers develop, introduce, and evaluate new biomedically motivated methods in areas as diverse as data mining, natural language or text processing, cognitive science, human-computer interaction, decision support, databases and algorithms for analyzing large amounts of data generated in public health, clinical research and genomics/proteomics.
In this online program, you will develop the skills and knowledge around data, health and informatics needed to attract attention from recruiters and hiring managers in the fast growing healthcare industry.
You will gain a thorough understanding of the field of health informatics and its various subfields, including research, laboratory/precision medicine, imaging, and artificial intelligence. You will also explore the themes that serve as the foundation for different areas of biomedical informatics, including clinical and neuro-informatics.
Throughout four courses and hands-on projects, you will leverage the expertise of faculty from the Division of Health Informatics at the Yale School of Public Health, learning from real-world projects and live sessions with groups of high-caliber peers.
By committing 6-8 hours of online study per week for about 7 months, you can earn a Yale-issued Health Informatics MasterTrack Certificate that can help you in your future graduate studies or professional pursuits in both public health departments (e.g. CDC, local government) and the private sector (e.g. organizations that employ computer scientists and mathematicians/statisticians). After successfully completing the MasterTrack, you will also be eligible for conditional credit if accepted into the Yale School of Public Health’s Master of Public Health (MPH) graduate degree program.
Upon successful completion of this MasterTrack Certificate, you will be eligible to earn 2 conditional credits counting towards the Yale School of Public Health’s MPH program if accepted.
Want to learn more about this program? [Visit the Yale University website](https://publichealth.yale.edu/education/continuing_ed/coursera/health-informatics/).
In this online program, you will develop the skills and knowledge around data, health and informatics needed to attract attention from recruiters and hiring managers in the fast growing healthcare industry.
You will gain a thorough understanding of the field of health informatics and its various subfields, including research, laboratory/precision medicine, imaging, and artificial intelligence. You will also explore the themes that serve as the foundation for different areas of biomedical informatics, including clinical and neuro-informatics.
Throughout four courses and hands-on projects, you will leverage the expertise of faculty from the Division of Health Informatics at the Yale School of Public Health, learning from real-world projects and live sessions with groups of high-caliber peers.
By committing 6-8 hours of online study per week for about 7 months, you can earn a Yale-issued Health Informatics MasterTrack Certificate that can help you in your future graduate studies or professional pursuits in both public health departments (e.g. CDC, local government) and the private sector (e.g. organizations that employ computer scientists and mathematicians/statisticians). After successfully completing the MasterTrack, you will also be eligible for conditional credit if accepted into the Yale School of Public Health’s Master of Public Health (MPH) graduate degree program.
Upon successful completion of this MasterTrack Certificate, you will be eligible to earn 2 conditional credits counting towards the Yale School of Public Health’s MPH program if accepted.
Want to learn more about this program? [Visit the Yale University website](https://publichealth.yale.edu/education/continuing_ed/coursera/health-informatics/).
Syllabus
Course 1: Introduction to Health Informatics, Part One
- In this course, you will receive an introduction to informatics topics pertinent to healthcare. Through lectures, discussions, and real-world applications, you will gain foundational knowledge in clinical information systems, biomedical data, health data standards, electronic health records, clinical decision support, health data security and telemedicine.
Course 2: Introduction to Health Informatics, Part Two
- This course picks up where the previouse course leaves off, and introduces additional key informatics topics pertinent to healthcare. Through lectures, discussions, and real-world applications, you will survey a variety of informatics subfields including artificial intelligence, bioinformatics and precision medicine, data warehouses and registries, research informatics, electronic quality metrics and IT evaluation, software tools, and open science.
Course 3: Clinical Database and Ontology
- In this course, you’ll be introduced to the common unifying themes that serve as the foundation for different areas of biomedical informatics, including clinical and neuro-informatics. This course requires coding knowledge and an advanced level of biomedical software experience.
Course 4: Introduction to Natural Language Processing and Data Mining
- In this course, you’ll take a deeper dive into biomedical informatics and data science. Through lectures, tutorials, discussions, and applied practice, you will explore biomedical natural language processing, data mining, machine learning, modeling of biological systems, and high performance computation in biomedicine. This course requires coding knowledge and an advanced level of biomedical software experience.
- In this course, you will receive an introduction to informatics topics pertinent to healthcare. Through lectures, discussions, and real-world applications, you will gain foundational knowledge in clinical information systems, biomedical data, health data standards, electronic health records, clinical decision support, health data security and telemedicine.
Course 2: Introduction to Health Informatics, Part Two
- This course picks up where the previouse course leaves off, and introduces additional key informatics topics pertinent to healthcare. Through lectures, discussions, and real-world applications, you will survey a variety of informatics subfields including artificial intelligence, bioinformatics and precision medicine, data warehouses and registries, research informatics, electronic quality metrics and IT evaluation, software tools, and open science.
Course 3: Clinical Database and Ontology
- In this course, you’ll be introduced to the common unifying themes that serve as the foundation for different areas of biomedical informatics, including clinical and neuro-informatics. This course requires coding knowledge and an advanced level of biomedical software experience.
Course 4: Introduction to Natural Language Processing and Data Mining
- In this course, you’ll take a deeper dive into biomedical informatics and data science. Through lectures, tutorials, discussions, and applied practice, you will explore biomedical natural language processing, data mining, machine learning, modeling of biological systems, and high performance computation in biomedicine. This course requires coding knowledge and an advanced level of biomedical software experience.
Tags
Related Courses
Business Considerations for 5G with Edge, IoT, and AILinux Foundation via edX FinTech for Finance and Business Leaders
ACCA via edX AI-900: Microsoft Certified Azure AI Fundamentals
A Cloud Guru AWS Certified Machine Learning - Specialty (LA)
A Cloud Guru Azure AI Components and Services
A Cloud Guru