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If you are embarking on the exciting journey of embedding advanced analytics and AI into your organisations, you will invariably run into questions of whether to engage a partner, which partners to engage with, and how to deliver projects beyond experiments and proof-of-concepts that scale within the enterprise. This session challenges established thinking on ways to effectively manage and deliver such projects considering the differences between advanced analytics/AI and typical IT projects, and the conditions needed to maximise the value such capabilities can bring to the organisation.
Five Ways Advanced Analytics and AI are evolving:
1) Citizen data scientists;
2) Need for executive education;
3) Changing nature of roles in data science;
4) End-to-end model management;
5) Effects of data science on society.
New to Managing Advanced Analytics and AI Projects? You will learn:
1) How advanced analytics and AI projects are different from IT projects;
2) Ways to structure an advanced analytics/AI project for success;
3) Measurement of project success;
4) Ethical considerations for AI projects.
Additionally, experienced PMs will focus their attention on:
1) Weighing the build-or-buy decision for advanced analytics/AI capabilities;
2) Separating delivery from platform;
3) Understanding value through the lens of open source.
If you have ever wondered about the following, then this is the presentation is definitely for you:
1) What are Advanced Analytics and AI?
2) What are the objectives and output(s) of these projects?
3) What additional skills do I need to learn to manage these projects?
4) What are the risks unique to such projects?