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Jimeng Sun
This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios.
Read more
This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios.
Read more
This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios.
We cover deep learning (DL) methods, healthcare data and applications using DL methods. The courses include activities such as video lectures, self guided programming labs, homework assignments (both written and programming), and a large project.
The first phase of the course will include video lectures on different DL and health applications topics, self-guided labs and multiple homework assignments. In this phase, you will build up your knowledge and experience in developing practical deep learning models on healthcare data. The second phase of the course will be a large project that can lead to a technical report and functioning demo of the deep learning models for addressing some specific healthcare problems. We expect the best projects can potentially lead to scientific publications.
Register for this course and see more details by visiting:
OpenCourser.com/course/4634gi/health
What's inside
Syllabus
Week 1 - Introduction
In the introduction we will introduce the topic of the course and present the background information.
Week 2 - Health Data
Read more
Syllabus
Week 1 - Introduction
In the introduction we will introduce the topic of the course and present the background information.
Week 2 - Health Data
Read more
Health Data are generated in many different categories of medical services. We'll take a closer look at these, and what this means for Health Data standards.
Week 3 - Machine Learning Basics
The topic of this week is Machine Learning. We'll look at
Week 4 - Deep Neural Networks (DNN)
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores a modern and relevant topic that offers many real-world medical use cases to its learners to develop models and solutions
Teaches important methodologies and skills for getting started with machine learning in medicine
Covers fundamental concepts and techniques which are essential for building and training deep neural models on medical data
Offers a hands-on approach and project-based approach through guided labs and a final project which allows learners to gain practical experience
Taught by Jimeng Sun who is recognized for their work in deep learning and its application to healthcare
This course may be considered a dealbreaker for learners who are not interested in the intersection of machine learning and medical applications
Save this course
Save Health Data Science Foundation to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Health Data Science Foundation with these
activities:
Review basic coding skills
Show steps
Refresh your coding skills in the language(s) utilized throughout the course to smooth the learning process.
Browse courses on
Python
Show steps
-
Go over variables, data types, and expressions.
-
Review loops (while and for) and conditionals (if-else).
-
Practice writing simple functions.
Read 'Deep Learning' by Ian Goodfellow
Show steps
Gain a comprehensive understanding of deep learning concepts and techniques from a highly regarded textbook.
View
Deep Learning
on Amazon
Show steps
-
Read each chapter thoroughly and take notes.
-
Work through the exercises and examples provided in the book.
-
Discuss the concepts with classmates or peers.
CodinGame coding challenges
Show steps
Practice your coding skills and prepare for the course's programming assignments.
Browse courses on
Python
Show steps
-
Solve easy and medium level puzzles.
-
Focus on puzzles which involve data manipulation, object-oriented programming, and algorithms.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Follow online tutorials on deep learning
Show steps
Supplement your course learning with practical hands-on experience through online tutorials.
Browse courses on
Deep Learning
Show steps
-
Identify reputable sources for deep learning tutorials.
-
Select tutorials that cover specific topics you want to improve your understanding of.
-
Follow the tutorials step-by-step and implement the code examples.
Join a machine learning study group
Show steps
Learn from and collaborate with your peers to reinforce your understanding of course concepts.
Browse courses on
Machine Learning
Show steps
-
Form or join a study group with classmates or other learners.
-
Set regular meeting times and stick to them.
-
Take turns presenting concepts, leading discussions, and solving problems.
Attend deep learning workshops
Show steps
Learn from experts and network with other professionals in the field to enhance your understanding of deep learning.
Browse courses on
Deep Learning
Show steps
-
Research upcoming workshops in your area or online.
-
Select workshops that align with your interests and career goals.
-
Attend the workshops and actively participate in discussions.
Write blog posts on machine learning topics
Show steps
Solidify your understanding of course concepts by teaching them to others through writing.
Browse courses on
Machine Learning
Show steps
-
Choose a specific machine learning topic to focus on.
-
Research the topic thoroughly and gather relevant information.
-
Organize your thoughts and write a clear and concise blog post.
Develop a machine learning project
Show steps
Apply the concepts learned in the course to a real-world problem and showcase your skills.
Browse courses on
Machine Learning
Show steps
-
Define the project scope and objectives.
-
Gather and preprocess the necessary data.
-
Select and train a machine learning model.
-
Evaluate the model's performance and tune it as needed.
-
Deploy the model and make it usable by others.
Attend machine learning meetups and conferences
Show steps
Stay up-to-date with the latest trends and connect with professionals in the field.
Browse courses on
Machine Learning
Show steps
-
Identify upcoming machine learning meetups and conferences in your area.
-
Attend the events and actively participate in discussions.
-
Network with other attendees and exchange ideas.
Review basic coding skills
Show steps
Refresh your coding skills in the language(s) utilized throughout the course to smooth the learning process.
Browse courses on
Python
Show steps
Show steps
Show steps
- Go over variables, data types, and expressions.
- Review loops (while and for) and conditionals (if-else).
- Practice writing simple functions.
Read 'Deep Learning' by Ian Goodfellow
Show steps
Gain a comprehensive understanding of deep learning concepts and techniques from a highly regarded textbook.
View
Deep Learning
on Amazon
Show steps
Show steps
Show steps
- Read each chapter thoroughly and take notes.
- Work through the exercises and examples provided in the book.
- Discuss the concepts with classmates or peers.
CodinGame coding challenges
Show steps
Practice your coding skills and prepare for the course's programming assignments.
Browse courses on
Python
Show steps
Show steps
Show steps
- Solve easy and medium level puzzles.
- Focus on puzzles which involve data manipulation, object-oriented programming, and algorithms.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Follow online tutorials on deep learning
Show steps
Supplement your course learning with practical hands-on experience through online tutorials.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Identify reputable sources for deep learning tutorials.
- Select tutorials that cover specific topics you want to improve your understanding of.
- Follow the tutorials step-by-step and implement the code examples.
Join a machine learning study group
Show steps
Learn from and collaborate with your peers to reinforce your understanding of course concepts.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Form or join a study group with classmates or other learners.
- Set regular meeting times and stick to them.
- Take turns presenting concepts, leading discussions, and solving problems.
Attend deep learning workshops
Show steps
Learn from experts and network with other professionals in the field to enhance your understanding of deep learning.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Research upcoming workshops in your area or online.
- Select workshops that align with your interests and career goals.
- Attend the workshops and actively participate in discussions.
Write blog posts on machine learning topics
Show steps
Solidify your understanding of course concepts by teaching them to others through writing.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Choose a specific machine learning topic to focus on.
- Research the topic thoroughly and gather relevant information.
- Organize your thoughts and write a clear and concise blog post.
Develop a machine learning project
Show steps
Apply the concepts learned in the course to a real-world problem and showcase your skills.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Define the project scope and objectives.
- Gather and preprocess the necessary data.
- Select and train a machine learning model.
- Evaluate the model's performance and tune it as needed.
- Deploy the model and make it usable by others.
Attend machine learning meetups and conferences
Show steps
Stay up-to-date with the latest trends and connect with professionals in the field.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Identify upcoming machine learning meetups and conferences in your area.
- Attend the events and actively participate in discussions.
- Network with other attendees and exchange ideas.
Career center
Learners who complete Health Data Science Foundation will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
**Data Scientists** use scientific methods and statistical techniques to extract knowledge from data in order to solve problems. This course is a great fit for an aspiring Data Scientist because it covers data analysis, neural networks, and machine learning, all of which are essential skills for success in this field. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Machine Learning Engineer
Machine Learning Engineer
**Machine Learning Engineers** design, develop, and deploy machine learning models to solve real-world problems. This course is a great fit for an aspiring Machine Learning Engineer because it covers the fundamentals of machine learning, deep learning, and health data analysis. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Healthcare Data Analyst
Healthcare Data Analyst
**Healthcare Data Analysts** use data analysis techniques to improve the quality and efficiency of healthcare. This course is a great fit for an aspiring Healthcare Data Analyst because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Health Informatics Specialist
Health Informatics Specialist
**Health Informatics Specialists** use information technology to improve the quality and efficiency of healthcare. This course is a great fit for an aspiring Health Informatics Specialist because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Medical Data Scientist
Medical Data Scientist
**Medical Data Scientists** use data science techniques to solve problems in the healthcare industry. This course is a great fit for an aspiring Medical Data Scientist because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Healthcare IT Specialist
Healthcare IT Specialist
**Healthcare IT Specialists** design, implement, and maintain information technology systems for healthcare organizations. This course is a great fit for an aspiring Healthcare IT Specialist because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Health Policy Analyst
Health Policy Analyst
**Health Policy Analysts** develop and evaluate policies that affect the health of populations. This course is a great fit for an aspiring Health Policy Analyst because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Healthcare Consultant
Healthcare Consultant
**Healthcare Consultants** help healthcare organizations improve their performance. This course is a great fit for an aspiring Healthcare Consultant because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Medical Writer
Medical Writer
**Medical Writers** create written materials about medical topics for a variety of audiences. This course is a great fit for an aspiring Medical Writer because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Public Health Analyst
Public Health Analyst
**Public Health Analysts** use data to improve the health of populations. This course is a great fit for an aspiring Public Health Analyst because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Clinical Research Associate
Clinical Research Associate
**Clinical Research Associates** work with doctors and researchers to design, conduct, and analyze clinical trials. This course is a great fit for an aspiring Clinical Research Associate because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Healthcare Marketer
Healthcare Marketer
**Healthcare Marketers** develop and implement marketing campaigns for healthcare products and services. This course is a great fit for an aspiring Healthcare Marketer because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Epidemiologist
Epidemiologist
**Epidemiologists** study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. This course is a great fit for an aspiring Epidemiologist because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Biostatistician
Biostatistician
**Biostatisticians** use statistical methods to solve problems in the healthcare industry. This course is a great fit for an aspiring Biostatistician because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
Healthcare Administrator
Healthcare Administrator
**Healthcare Administrators** manage the day-to-day operations of healthcare organizations. This course is a great fit for an aspiring Healthcare Administrator because it covers the fundamentals of data analysis, machine learning, and deep learning, as well as their applications in healthcare. The course also includes a large project that can lead to a technical report and functioning demo of deep learning models for addressing specific healthcare problems, which will give you the opportunity to gain hands-on experience with these technologies.
For more career information including salaries, visit:
OpenCourser.com/course/4634gi/health
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Health Data Science Foundation.
Provides a comprehensive introduction to deep learning with Python. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks. The book also includes case studies on real-world applications.
Save
Provides a comprehensive foundation in deep learning, covering neural network architectures, training methods, and applications. Offers a theoretical and practical understanding of deep learning for healthcare applications.
Provides an introduction to health data science. It covers topics such as data collection, data cleaning, and data analysis. The book also includes case studies on real-world healthcare applications.
Provides a hands-on introduction to machine learning with Python. It covers topics such as data preprocessing, model selection, training, and evaluation. The book also includes case studies on real-world applications.
Provides a comprehensive introduction to natural language processing with Python. It covers topics such as tokenization, stemming, lemmatization, and parsing. The book also includes case studies on real-world applications.
Provides an overview of the ethical and legal considerations in healthcare data analytics, including data privacy, informed consent, and data security. Offers practical guidance on navigating ethical and legal challenges in healthcare data analysis.
Provides a practical introduction to Python for data analysis, covering data manipulation, visualization, and statistical modeling. Offers hands-on exercises and examples relevant to healthcare data analysis.
Offers a beginner-friendly introduction to machine learning, covering fundamental concepts such as data preprocessing, model selection, and evaluation. Provides a practical approach to using machine learning in healthcare.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/4634gi/health
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Effort
The course is scheduled to take four weeks.
Level
Advanced
Via
Coursera
Institution
University of Illinois at Urbana-Champaign
Instructor
Jimeng Sun
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
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This course belongs to a
collection
called
Deep Learning for Healthcare. It's comprised of three courses:
- Health Data Science Foundation (viewing)
- Deep Learning Methods for Healthcare
- Advanced Deep Learning Methods for Healthcare
Good to know
Explores a modern and relevant topic that offers many real-world medical use cases to its learners to develop models and solutions
Teaches important methodologies and skills for getting started with machine learning in medicine
Covers fundamental concepts and techniques which are essential for building and training deep neural models on medical data
Offers a hands-on approach and project-based approach through guided labs and a final project which allows learners to gain practical experience
Taught by Jimeng Sun who is recognized for their work in deep learning and its application to healthcare
This course may be considered a dealbreaker for learners who are not interested in the intersection of machine learning and medical applications
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