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Energy is one of the many sectors being transformed by artificial intelligence (AI). The technology is being used to forecast energy resources, analyze data from the electric grid, figure out how to integrate electric vehicles and sources of renewable energy into infrastructure and develop cybersecurity monitoring and protection for infrastructure — as well as make energy more cost-effective and climate friendly. For professionals in the industry looking to expand their understanding or increase their use of AI, here are some top programs offering certificates in different aspects of energy:
Skills Learned: Students will learn to make forecasts about the future performance of energy resources, use of robotics and autonomous vehicles in harsh energy working environments, machine learning (ML) for operational detection and the application of neural networks in energy operations.
Requirements: Intended for professionals working with intelligent systems and operations
Duration: Three days
Cost: $2,950
2. Intelligent and Integrated Energy Systems
Certifying Organization: Delft University of Technology
Skills Learned: Evaluate the performance, role and impact of combined/integrated energy technologies on modern energy systems, such as renewable energy sources, energy storage, electric vehicles, thermal systems and interconnected multi-carrier grids. Identify how to digitalize the conventional grid using technologies, including machine learning, AI, blockchain and computer simulations. Evaluate the flexibility, grid support and reduction in carbon footprint that can be obtained by transition to electric mobility, electrified heating and hydrogen energy. Make informed decisions about managing infrastructure, actors, policy and energy markets that support energy transition and sustainable energy systems.
Duration: Four courses, each four to six hours a week for six weeks
Test: Graded assignments and exams
Cost: $536
3. Artificial Intelligence for Renewable Energies
4. No Code Analytics and Machine Learning in Energy
Certifying Organization: University of Houston
Skills Learned: Students will understand how to extract knowledge from raw data and be skilled at data exploration, data preprocessing, machine learning modeling and evaluating and improving model performance.
Requirements: Either industry professional or rising senior in a bachelor’s degree program in engineering, technology or business, with an understanding of energy industry operations, such as seismic, drilling and production.
Duration: Three 15-hour modules delivered over three weeks
Test: Weekly quizzes, plus finals
Cost: $1,000 for all three modules or $400 a module
5. Transforming the Grid: AI, Renewables, Storage, EVs and Prosumers
6. GridEd Short Course: Machine Learning and Big Data Analytics in Smart Grid
Certifying Organization: Electric Power Research Institute
Skills Learned: The program covers the basics of unsupervised learning, supervised learning, reinforcement learning algorithms and generative models. Various important applications of big data analytics and machine learning in electric power distribution systems, transmission networks and electricity markets will be presented with real-world data.
Requirements: Previous technical training is helpful but not necessary
Duration: 12 hours
Cost: $1,200
7. Data Mining and Artificial Intelligence for Energy Sector
Certifying Organization: Energy Training Centre
Skills Learned: Students will learn how to perform data mining, the identification of algorithms used in artificial intelligence that are beneficial for their industries and proper use of the technology. The program teaches how data mining is structured in their industry, how to differentiate good data from noise and biased data, how to find hidden patterns within data, the process of digital twins creation and how to avoid common pitfalls of Industry 4.0.
Requirements: The course is designed for professionals in the energy sector
Duration: Five days
Test: A project in designing a new digital product
Cost: $3,950
8. Data Science and AI for Energy Engineers
Certifying Organization: EIT InnoEnergy and KU Leuven
Skills Learned: Students will learn how to use Python and other tools to analyze and visualize energy demand data. They’ll gain practical knowledge of tools for monitoring and experimenting with energy data sets. They’ll explore the limitations of machine learning models and how they rely on time-series and statistical principles to forecast energy demand.
Requirements: Proficiency in a programming language, preferably Python. Understanding of core concepts in energy and power engineering.
Duration: 60 to 80 hours over two weeks
Test: Project presentation
Cost: 3,950 euros
9. Co-Benefits From Artificial Intelligence (AI) in Renewable Energy
Certifying Organization: Renewables Academy
Skills Learned: Students will learn to explain the place of artificial intelligence in regard to renewable energy and assess current AI applications around renewable energies and climate protection in the electricity sector.
Duration: About 14 hours over four weeks
Test: Self-assessments
Cost: 286 euros
10. Artificial Intelligence for Engineering
1. Artificial Intelligence for Energy Professionals
Certifying Organization: Energy Training CentreSkills Learned: Students will learn to make forecasts about the future performance of energy resources, use of robotics and autonomous vehicles in harsh energy working environments, machine learning (ML) for operational detection and the application of neural networks in energy operations.
Requirements: Intended for professionals working with intelligent systems and operations
Duration: Three days
Cost: $2,950
2. Intelligent and Integrated Energy Systems
Certifying Organization: Delft University of Technology Skills Learned: Evaluate the performance, role and impact of combined/integrated energy technologies on modern energy systems, such as renewable energy sources, energy storage, electric vehicles, thermal systems and interconnected multi-carrier grids. Identify how to digitalize the conventional grid using technologies, including machine learning, AI, blockchain and computer simulations. Evaluate the flexibility, grid support and reduction in carbon footprint that can be obtained by transition to electric mobility, electrified heating and hydrogen energy. Make informed decisions about managing infrastructure, actors, policy and energy markets that support energy transition and sustainable energy systems.
Duration: Four courses, each four to six hours a week for six weeks
Test: Graded assignments and exams
Cost: $536
3. Artificial Intelligence for Renewable Energies
Certifying Organization: The University of Oklahoma, Mewbourne College of Earth and Energy
Skills Learned: Starting with an introduction to the main concepts of programming in Python, students will learn the basic concepts of machine learning and deep learning algorithms for several applications: the time-series analysis related to patterns of consumption of water and energy resources; the estimation of energy resources associated with solar, wind and geothermal energy; and the use of satellite images through neural networks for the classification of the Earth's surface.
Requirements: No previous experience with Python or special software required
Duration: Five days, three hours a day
Test: Project using the main features of Python 3
Cost: $995
4. No Code Analytics and Machine Learning in Energy
Certifying Organization: University of Houston Skills Learned: Students will understand how to extract knowledge from raw data and be skilled at data exploration, data preprocessing, machine learning modeling and evaluating and improving model performance.
Requirements: Either industry professional or rising senior in a bachelor’s degree program in engineering, technology or business, with an understanding of energy industry operations, such as seismic, drilling and production.
Duration: Three 15-hour modules delivered over three weeks
Test: Weekly quizzes, plus finals
Cost: $1,000 for all three modules or $400 a module
5. Transforming the Grid: AI, Renewables, Storage, EVs and Prosumers
Certifying Organization: Stanford School of Engineering and Stanford Doerr School of Sustainability
Skills Learned: The program teaches about the modern electric grid with a focus on transforming technologies, including artificial intelligence, machine learning, storage technologies and electric vehicles.
Requirements: No engineering or energy background required
Duration: Six hours; 60 days to complete
Cost: $395
See more: Energy Hungry AI: Is It Sustainable?
6. GridEd Short Course: Machine Learning and Big Data Analytics in Smart Grid
Certifying Organization: Electric Power Research Institute Skills Learned: The program covers the basics of unsupervised learning, supervised learning, reinforcement learning algorithms and generative models. Various important applications of big data analytics and machine learning in electric power distribution systems, transmission networks and electricity markets will be presented with real-world data.
Requirements: Previous technical training is helpful but not necessary
Duration: 12 hours
Cost: $1,200
7. Data Mining and Artificial Intelligence for Energy Sector
Certifying Organization: Energy Training Centre Skills Learned: Students will learn how to perform data mining, the identification of algorithms used in artificial intelligence that are beneficial for their industries and proper use of the technology. The program teaches how data mining is structured in their industry, how to differentiate good data from noise and biased data, how to find hidden patterns within data, the process of digital twins creation and how to avoid common pitfalls of Industry 4.0.
Requirements: The course is designed for professionals in the energy sector
Duration: Five days
Test: A project in designing a new digital product
Cost: $3,950
8. Data Science and AI for Energy Engineers
Certifying Organization: EIT InnoEnergy and KU Leuven Skills Learned: Students will learn how to use Python and other tools to analyze and visualize energy demand data. They’ll gain practical knowledge of tools for monitoring and experimenting with energy data sets. They’ll explore the limitations of machine learning models and how they rely on time-series and statistical principles to forecast energy demand.
Requirements: Proficiency in a programming language, preferably Python. Understanding of core concepts in energy and power engineering.
Duration: 60 to 80 hours over two weeks
Test: Project presentation
Cost: 3,950 euros
9. Co-Benefits From Artificial Intelligence (AI) in Renewable Energy
Certifying Organization: Renewables Academy Skills Learned: Students will learn to explain the place of artificial intelligence in regard to renewable energy and assess current AI applications around renewable energies and climate protection in the electricity sector.
Duration: About 14 hours over four weeks
Test: Self-assessments
Cost: 286 euros
10. Artificial Intelligence for Engineering
Certifying Organization: Stevens Institute of Technology, Department of Electrical and Computer Engineering
Skills Learned: The graduate certification program requires students to complete four of the six following courses in computer science/electrical engineering for various engineering applications, such as smart grids: pattern recognition and classification; applied machine learning; engineering programming: Python; data acquisition, modeling and analysis: big data analytics; data acquisition, modeling and analysis: deep learning; and applied game theory and evolutionary algorithms.
Requirements: Meet the regular admission requirements for the master’s program
See more: 10 Top Generative AI Certifications
