Ai & Machine Learning

Medical Insurance Premium Prediction with ML

(0 reviews)
Share icon
Coursera

With the help of machine learning, this course teaches students how to predict health insurance costs by taking into account factors like age, gender, BMI, and smoking habits.

Key AI Functions:data science, artificial neural network, python programming, machine learning, ai & machine learning

Description for Medical Insurance Premium Prediction with ML

  • Project-Based Learning: An experiential, case-study methodology for acquiring machine learning skills through engagement with a real-world problem.

  • Forecasting Insurance Expenditures: Concentrates on implementing machine learning methodologies to anticipate health insurance expenses based on diverse individual variables.

  • Extensive Feature Set: Incorporates essential variables such as age, gender, BMI, number of offspring, smoking behavior, and geographic location in the predictive model.

  • One-Hour Duration: A brief, 1-hour course tailored for those aiming to swiftly acquire practical expertise in forecasting insurance expenses utilizing machine learning.

Level: Intermediate

Certification Degree: Yes

Languages the Course is Available: 1 (English)

Offered by: On Coursera provided by Google Cloud

Duration:1 hr 30 mins (approximately)

Schedule: Project-based

Reviews for Medical Insurance Premium Prediction with ML

0 / 5

from 0 reviews

Ease of Use

Ease of Customization

Intuitive Interface

Value for Money

Support Team Responsiveness

Alternative Tools for Medical Insurance Premium Prediction with ML

A thorough grasp of artificial intelligence (AI) and machine learning, including its various forms, methods, and applications, is given in this course.

#artificial intelligence #data science
Visit icon

Learn the skills necessary to operate, optimize, and implement large language models through practical experience with state-of-the-art LLM architectures and open-source resources.

#opensource #llm
Visit icon

This course is dedicated to the setting up of GPU-based environments, the deployment of local large language models (LLMs), and their integration into Python applications utilizing open-source tools.

#llm #local llm
Visit icon

Learn proficiency in the construction, deployment, and safeguarding of large language models at scale, utilizing Rust, Amazon Web Services (AWS), and established DevOps best practices.

#llmops #devops
Visit icon

Develop expertise in the exposure and deployment of large language models via application programming interfaces (APIs), configure server environments, and incorporate natural language processing (NLP) functionalities into applications.

#llamafile #api
Visit icon

In this course, students gain the skills necessary to use Python for data science, machine learning, and foundational applications of artificial intelligence.

#scientific methods #data science
Visit icon

Examine how to improve learning and preserve integrity by incorporating morally sound and useful AI tools into evaluation procedures.

#artificial intelligence #education
Visit icon

Discover AI terminology, ethical norms, and protocols for responsibly utilizing and citing Generative AI.

#artificial intelligence #ethics
Visit icon

The material equips data engineers to incorporate machine learning models into pipelines while adhering to best practices in collaboration, version control, and artifact management.

#machine learning #data engineering
Visit icon

This program instructs instructors on the ethical and successful integration of AI, while promoting innovation and critical thinking among students.

#artificial intelligence #educational technologies
Visit icon