The project world is seeing dramatic changes that allow us to see into the future, with more clarity, intelligence and predictability. Once used traditional methods of descriptive assessments, such as comparisons of quantitative, lagging data, are now making way for more mature business technologies and intelligence through predictive analytics, artificial intelligence (AI) and machine learning (ML). This new surge of intelligence is provocative and exciting and provides the project delivery world with profound opportunities to increase efficiencies and effectiveness while decreasing uncertainties. Consequently, this type of intelligence creates endless possibilities to project delivery improvements, and subsequently, operational success.
With this said, the objective of this presentation is to provide the audience with a fundamental understanding of how to apply data science and advance analytics methodologies in the business and project environment, which includes:
Assessing and utilizing historical project data for problem solving and data analytics.
Learning business problem framing and turning the business problem statement into an analytics problem.
Developing an understanding of the predictive analytics process and how AI and ML can be used.
Learning how to recognize the attributes of data analytics and prepare datasets for modelling.
Please join me as I present these key requirements for adopting predictive analytics into your organization.
