August 20, 2019
2:15 pm - 5:30 pm
Duration: Half Day Course
The growth of data science as a key practice in modern business has brought unique challenges—technical, organizational, and ethical.
Data science teams are often structured more loosely than traditional IT or analytics teams, and they may use a wider range of platforms, tools, and techniques than IT teams are used to managing. Plus the techniques they use may be advanced and difficult to document or audit.
On top of this, there is increasing public concern about data security and privacy, and governments worldwide have introduced legislation to address this, including the European Union's GDPR. There are also lingering questions about the ethics of machine learning as it is applied in many cases, along with concerns about bias, business impact, and even social engineering.
This course introduces a consistent, practical framework for addressing governance and ethics concern in your data science initiatives both strategically and tactically.
Rest easy—online registrations for this conference are secure. Our secured server environment keeps your information private.