Training

Online Courses

Group Live Training Course

Industrial Data Science Industrial Data Science

Duration: 2 Days

Early bird: $1,100

Regular registration: $1,450

Delivery Date
Early Bird
TBCTBC

Course Overview:

Our 2-day Industrial Data Science (IDS) training course program presents an organized set of modules that address the important skill sets and understanding needed to explore the main tools used for data science and how these can be implemented to optimize asset management in heavy industry.

The topics in this course are illustrated via practical case studies for the delegates which are analysed and solved in a discussion-based environment. Case studies such as data science applied to industry problems and worked examples of how to use Cloud-Based Artificial Intelligence (AI) to lower the barrier to entry for Artificial Intelligence (AI) adoption are presented.

In this course, a comprehensive management method is utilized to address the concepts behind Big Data, Industrial Data Science, Industrial AI, Cross-Industry Standard Process for Data Mining (CRISP-DM) and their utilization to boost your business’ data extraction, analysis, visualization and predictive modelling techniques.

The course consists of an organized set of 8 modules that address the important skill sets and understanding needed to explore the main tools used for data science and how these can be implemented to optimize asset management in heavy industry.

  • The basic definitions to Industrial Data Science and Data Sources are introduced.
  • The details, optimization, steps, and industry examples for Cross-Industry Standard Process for Data Mining are explored.
  • The Fundamentals of Machine Learning (ML) & Artificial Intelligence (AI) are delved into.
  • The key elements of Data Preparation, Feature Engineering, and Data Labelling are explained.
  • Data Visualization techniques and principal communication methods are detailed.
  • Machine Learning (ML) & Artificial Intelligence (AI) Frameworks in Python are presented, whereby Python is the preferred language due to its expansive ecosystem and flexibility of deployment.
  • Cloud-Based Artificial Intelligence Services are explained, whereby such services allow low-cost access to high power AI models and training environments.
  • An overview of Reference architectures and best practices for data science is elaborated upon.

The objective of the course is to learn the capabilities of Big Data, Industrial Data Science, and Industrial AI, and how they can be applied to heavy industry to optimize critical processes and day-to-day tasks.

This training course is developed for practicing engineers, operators and managers in various industries such as:

  • Energy
  • Utilities
  • Mining
  • Aviation
  • Renewables

The course is of benefit to all levels of personnel whose jobs requires them to conduct data management and analysis tasks to enhance their skill sets be it in the field of integrity, maintenance, operations or HSE. It provides an introductory overview of the transformative potential of Data Science and its applications within modern day Industry.

Delegates attending this course do not require any previous knowledge in Data Science and Artificial Intelligence (AI) techniques – these concepts will be introduced during the course with numerous applications and industrial case studies presented.

  • Registration will only be confirmed once payment is received in full and notification is received back from AIE.
  • It is the responsibility of the attendee to ensure that they have an adequate internet connection as well as audio and microphone facilities.
  • Payments are non-refundable in the event of a cancellation. However, substitute delegates are permitted at any time by providing advance notice to AIE.
  • In the event that AIE postpones the course and the delegate is unable or unwilling to attend on the rescheduled date, a full refund of monies will be provided.
  • AIE shall assume no liability in the event of this conference being cancelled due to any unforeseen or uncontrollable circumstances.