ML in Healthcare: Fundamentals & Applications
Explore healthcare data mining methods, theoretical foundations of key techniques, selection criteria, and practical applications with emphasis on data cleansing, transformation, and modeling for real-world problem solving.
Description for ML in Healthcare: Fundamentals & Applications
Features of Course
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Northeastern University
Duration: 18 hours to complete
Schedule: Flexible
Pricing for ML in Healthcare: Fundamentals & Applications
Use Cases for ML in Healthcare: Fundamentals & Applications
FAQs for ML in Healthcare: Fundamentals & Applications
Reviews for ML in Healthcare: Fundamentals & Applications
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML in Healthcare: Fundamentals & Applications
The AI tool empowers non-programmers to construct and deploy AI, featuring data transformation, insights generation, identification of critical drivers, and prediction and forecasting functionalities to enhance business decision-making and planning processes.
Enhance your software development career with Gen AI. Develop hands-on, in-demand Generative AI skills to elevate your software engineering game in one month or less.
Utilize generative AI to advance in the field of data science. Develop hands-on generative AI skills that are in high demand to accelerate your data science career in under one month.
Achieve a professional status as an AI Engineer. Acquire the knowledge necessary to develop next-generation applications that are propelled by generative AI, a skill that is indispensable for startups, agencies, and large corporations.
Enhance your Product Manager career with Gen AI. Boost your Product Manager career in under two months by developing hands-on, in-demand generative AI skills. No prior experience is required to initiate the process.
Delve into the historical evolution of Generative AI and AI, exploring diverse models and their applications in business contexts for optimized decision-making and innovation.
Begin your vocation in generative AI data engineering. Obtain the necessary skills to secure a position as a data engineer by acquiring an understanding of generative AI. No prior experience is required.
Begin your professional journey as an AI Product Manager. Develop generative AI and product management skills that are in high demand to be job-ready in six months or less.
Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.
Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world
Featured Tools
Acquire a comprehensive understanding of the fundamental business and technical concepts of product management for AI and data science.
Introduces the fundamental procedures for the development, scripting, and training of a machine-learned model in Google Cloud.
The goal of this course is to provide professionals with the necessary data science abilities in MATLAB so that they can carry out practical activities in businesses that rely heavily on data without having to learn extensive programming.
This 2-hour project-based course will instruct you on the interpretation of the dataset for machine learning, the impact of various features on a mode, and the evaluation of these features.
A brief synopsis of this course is that it covers the development of interpretable machine learning applications utilizing random forest and decision tree models, emphasizing feature importance analysis for responsible machine learning implementation.