# The Importance of Data Integrity for Machine Learning: A Data Lifecycle Model

#### Extended Learning Learning Level: Intermediate

Artificial Intelligence (AI) is a broad field of study within computer science that includes technologies such as Machine Learning (ML), as well as deep and continuous learning. This webinar touches on the basics of ML, but more importantly examines the data life cycle of ML and the criticality of data integrity on the outcomes of what “machines” are able to process/learn, in addition to how that fits into an overarching GAMP5 System Development Life Cycle (SDLC).

## Learning Objectives

1. Identify the types of data and when they are needed/required throughout the Machine Learning life cycle
2. Recognize the importance of data integrity within Machine Learning
3. Understand how the Machine Learning development process fits into a GAMP 5 SDLC model

## Speakers

Eric J. Staib
Vice President of Compliance
Genpact