General Objective: The twelve modules cover a repeatable and scalable set of AI workflows using spatial and time series upstream data sets. I introduce the different ML and DL techniques, supervised, unsupervised, and reinforcement learning workflows. We explore the critical data QC steps to provide a robust and comprehensive dataset for AI modeling. There is a module dealing with DL techniques, CNNs, and RNNs.

Audience: Its content will be very useful to people involved in production optimization, production technology, supervision and management, field personnel.

Dedication: Completion time: 7 hours. It includes the dedication corresponding to complementary reading and evaluations.