• Class and Course

    Introduction to AI for the Energy Industry

    The training provides an introduction to the field of Artificial Intelligence (AI). It begins with an overview of AI's history, key developments, and its intricate relationship with machine learning and deep learning. The course then shifts to a hands-on approach, introducing Python for data science, including the setup of the development environment and usage of essential AI libraries like pandas, numpy, and scikit-learn. It further delves into classic machine learning concepts, popular algorithms, and significant artificial neural network architectures under deep learning. Lastly, the program offers an insight into the potential and challenges of deploying AI within the energy industry.

    Fundamentals of Artificial Intelligence

    Historical Context and Milestones

    Key developments and breakthroughs in the field of AI

    Relations between Artificial intelligence, machine learning, and deep learning

    Debunking AI myths

    Python setup

    Introduction to Machine Learning

    Python 101

    Supervised Learning

    Unsupervised Learning

    Most important Machine Learning Algorithms

    Machine Learning in practice

    Machine Learning in the Energy Industry

    Introduction to Deep Learning

    Understanding Neural Networks

    Different types of Neural Networks

    The Deep Learning Workflow.

    Deep Learning Tools and Libraries

    Deep Learning in the Energy Industry


    Python basics for Data Science

    Data Visualization

    Python Libraries for AI

    Data Processing

    Hands-on Exercises

    Introduction to No Code Tools in AI

    Intro to Dataiku

    Building workflows in Dataiku

    Machine Learning with Dataiku

    Hands-on Lab

    Case studies

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