Data-Centric AI: Best Practices, Responsible AI, and More
With Aishwarya Srinivasan
Liked by 129 users
Duration: 2h 50m
Skill level: Intermediate
Released: 1/25/2024
Course details
Machine learning typically focuses on producing effective models for a given dataset. In real-world applications, data is messy and improving models is not the only way to get better performance. Data-centric AI (DCAI) is an emerging science that studies techniques to improve datasets, which is often the best way to improve performance in practical ML applications. While data scientists have long practiced this manually via ad hoc trial/error and intuition, DCAI considers the improvement of data as a systematic engineering discipline. In this course, Aishwarya Srinivasan covers the data-centric principles that guide our path forward in this new age of AI as we shift from a model-centric approach to a data-centric paradigm. Learn about DCAI—what it is and the value it offers. Aishwarya covers the DCAI workflow; MLOps as part of DCAI; data validation and preprocessing; model validation; bias detection and mitigation; responsible AI; and more.
Skills you’ll gain
Earn a sharable certificate
Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
-
Showcase on your LinkedIn profile under “Licenses and Certificate” section
-
Download or print out as PDF to share with others
-
Share as image online to demonstrate your skill
Meet the instructor
Learner reviews
-
-
-
Basit Amin (CDCTP®CDFOM®CDFOS®CDCP®), Engineer(BSc, MSc)
Basit Amin (CDCTP®CDFOM®CDFOS®CDCP®), Engineer(BSc, MSc)
Data Centre Engineer, Electrical Engineer (Engineers Ireland, PEC) Certified Data Centre (Technician Professional CNET, Facilities Operations Manager…
Contents
What’s included
- Learn on the go Access on tablet and phone
Similar courses
Download courses
Use your iOS or Android LinkedIn Learning app, and watch courses on your mobile device without an internet connection.