In this course, you will be introduced to the basics of artificial intelligence and machine learning and how they are applied in real-world scenarios in the AI for Good space. You will also be introduced to a framework for problem solving where AI is part of the solution. The course concludes with a case study featuring three Jupyter notebook labs where you’ll create an air quality monitoring application for the city of Bogotá, Colombia.
AI and Public Health
AI and Public Health
This course is part of AI for Good Specialization
Instructor: Robert Monarch
Access provided by FutureX
19,101 already enrolled
Gain insight into a topic and learn the fundamentals.
251 reviews
Beginner level
Recommended experience
Flexible schedule
9 hours to complete
Learn at your own pace
98%
Most learners liked this course
Skills you'll gain
- Supervised Learning
- Artificial Intelligence
- Deep Learning
- Data Preprocessing
- Exploratory Data Analysis
- Responsible AI
- Applied Machine Learning
- Information Privacy
- Public Health
- Machine Learning
- Environmental Monitoring
- AI literacy
- Healthcare Ethics
- Machine Learning Algorithms
- Model Evaluation
- Data Analysis
- Data Ethics
Tools you'll learn
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
4 assignments
Taught in English
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This course is part of the AI for Good Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 3 modules in this course
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Showing 3 of 251
AL
Reviewed on Dec 29, 2024
Well constructed to allow depth of understanding from a variety of backgrounds, while also offering exposure to specific projects to get a sense of relative information.
DE
Reviewed on Sep 12, 2023
A good beginner course. Not super hands on, but gives a good overview of the process to building a good project.
TN
Reviewed on Jan 6, 2024
In the area of the Labs, I expected it to be slightly more mentally challenging. Giving participants opportunity to make informed guesses and then autocorrecting errors.
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