Artificial Intelligence for Breast Cancer Detection

Coursera Courses ↗ · Coursera

Open Course on Coursera

Free to audit · Opens on Coursera

Artificial Intelligence for Breast Cancer Detection

Coursera · Intermediate ·🛡️ AI Safety & Ethics ·1mo ago
The objective of this course is to provide students the knowledge of artificial intelligence processing approaches to breast cancer detection. Students will take quizzes and participate in discussion sessions to reinforce critical concepts conveyed in the modules. Reading assignments, including journal papers to understand the topics in the modules, will be provided. The course is designed for students who are interested in the career of product development using artificial intelligence and would like to know how AI can be applied to mammography. The course content is focused on the AI processing paradigm along with the domain knowledge of breast imaging. This course approach is unique, providing students a broad perspective of AI, rather than homing in on a particular implementation method. Students who complete this course will not only leverage the knowledge into an entry level job in the field of artificial intelligence but also perform well on projects because their thorough understanding of the AI processing paradigm.
Watch on Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

Your Team Is the Part That Makes AI Safe
Ensure AI safety by prioritizing team dynamics and founder involvement, as they play a crucial role in mitigating risks
Medium · AI
Your Team Is the Part That Makes AI Safe
Building a safe AI system requires a well-structured team, and founders are at risk of losing control if they don't prioritize team development
Medium · Startup
Federal Prosecutors Indicted An Innocent Person On A Deepfake
A deepfake led to the indictment of an innocent person in federal court, highlighting the need for awareness and measures to combat AI-generated fake evidence
Forbes Innovation
The Human-in-the-Loop Trap
Learn to avoid the human-in-the-loop trap in enterprise AI teams by understanding its limitations and implementing effective human-AI collaboration
Medium · Data Science
Up next
The "Jackass Trophy" at OpenAI
The Information
Watch →