Machine Learning and Data Management in the Power and Energy Industry - Virtual Learning
Course Methodology
This Machine Learning and Data Management in the Power and Energy Industry training course will use a plethora of proven adult learning techniques with the examples of big data, machine learning and AI for energy industry.
Course Objectives
At the end of this Machine Learning and Data Management in the Power and Energy Industry training course, you will learn to:
- Coordinate urban planning and energy use trough ML and AI
- Develop smart energy using AI and Data Management
- Planning and adaptation of additional energy resources to existing systems
- Implement smart energy planning to Power and Energy industries
Target Audience
This Gulf Rowad Machine Learning and Data Management in the Power and Energy Industry training course is intended for professionals working with intelligent systems and operations. This is also suitable for a wide range of professionals but will greatly benefit:
- Energy Development and Production Operations Engineers
- Professionals in Command Centre
- Compliance and Operational Excellence Officers
- Professionals who intend to understand the applications of Artificial Intelligence and Machine Learning
- Senior Corporate Leaders, Managers, Department Heads, and Supervisors in the Energy and Power Sector
- Professionals working in energy and power generation, industrial plants, and refineries
- Technologists and researchers in the arena of Artificial Intelligence and Energy
Target Competencies
Organisational Impact
Organizations will significantly benefit from the collective knowledge of their employees that will understand the ways to adequately Manage Energy Data, use ML and AI tools and methods to improve the effectiveness and sustainability of the system.
The organizations will:
- Enhance their understanding of Energy Data Management principles
- Learn how to properly plan incorporation of renewable energy into existing systems
- Be able to sustain the economic viability of energy system
- Improve the resilience of energy system to changes in energy demands
- Adopt the best in class solutions for Data Management, ML and AI in Energy Industry
- Use AI within energy system design and development
Personal Impact
- Identifying the energy requirements of the new era
- Learning how to address energy problems trough AI
- Understanding how to develop proper Data management system for energy industry
- Learn how to identify energy demands
- Apply techniques of innovation, Artificial Intelligence and pattern recognition
Course Outline
Energy System Design with the Use of AI
- Energy data management
- Data management framework for energy systems
- Working in unison with available Big Data
- Expanding the view through the use of AI
- AI systems in use for energy planning
Machine Learning and AI
- Pattern recognition for needs of energy
- Smart Grids with the use of AI
- Machine Learning techniques for energy demand
- Establishing a structural AI system in Energy Industry
- Complexity of energy requirements with introduction of renewable energy
Models in Use
- KNN
- SVM
- Naïve Bayes
- State Path Algorithm
- OneR
- JRip
- Adaboost
Sustainable Energy
- Sustainability triangle
- Microgrids
- System Performance Parameters
- Increasing resilience with the use of AI
- Focus on Intelligent Modelling and Analysis
Smart Energy
- Examples of AI for smart energy
- Intelligent Approach for Load Frequency Control
- Power System Analysis
- Power System Stability Analysis and Improvement
- Issues and recommendations
2026 Schedule & Fees
| Date | City | Language | Price | Action |
|---|---|---|---|---|
| 28 Jun - 02 Jul, 2026 | Online | English | USD 2,000 | Book |
| 28 Jun - 02 Jul, 2026 | Online | Arabic | USD 2,000 | Book |
| 05 Jul - 09 Jul, 2026 | Online | English | USD 2,000 | Book |
| 05 Jul - 09 Jul, 2026 | Online | Arabic | USD 2,000 | Book |
| 12 Jul - 16 Jul, 2026 | Online | Arabic | USD 2,000 | Book |
| 12 Jul - 16 Jul, 2026 | Online | English | USD 2,000 | Book |
| 19 Jul - 23 Jul, 2026 | Online | Arabic | USD 2,000 | Book |
| 19 Jul - 23 Jul, 2026 | Online | English | USD 2,000 | Book |
| 26 Jul - 30 Jul, 2026 | Online | English | USD 2,000 | Book |
| 26 Jul - 30 Jul, 2026 | Online | Arabic | USD 2,000 | Book |
| 02 Aug - 06 Aug, 2026 | Online | English | USD 2,000 | Book |
| 02 Aug - 06 Aug, 2026 | Online | Arabic | USD 2,000 | Book |
| 09 Aug - 13 Aug, 2026 | Online | Arabic | USD 2,000 | Book |
| 09 Aug - 13 Aug, 2026 | Online | English | USD 2,000 | Book |
| 16 Aug - 20 Aug, 2026 | Online | Arabic | USD 2,000 | Book |
| 16 Aug - 20 Aug, 2026 | Online | English | USD 2,000 | Book |
| 23 Aug - 27 Aug, 2026 | Online | Arabic | USD 2,000 | Book |
| 23 Aug - 27 Aug, 2026 | Online | English | USD 2,000 | Book |
| 30 Aug - 03 Sep, 2026 | Online | Arabic | USD 2,000 | Book |
| 30 Aug - 03 Sep, 2026 | Online | English | USD 2,000 | Book |
| 06 Sep - 10 Sep, 2026 | Online | Arabic | USD 2,000 | Book |
| 06 Sep - 10 Sep, 2026 | Online | English | USD 2,000 | Book |
| 13 Sep - 17 Sep, 2026 | Online | Arabic | USD 2,000 | Book |
| 13 Sep - 17 Sep, 2026 | Online | English | USD 2,000 | Book |
| 20 Sep - 24 Sep, 2026 | Online | English | USD 2,000 | Book |
| 20 Sep - 24 Sep, 2026 | Online | Arabic | USD 2,000 | Book |
| 27 Sep - 01 Oct, 2026 | Online | English | USD 2,000 | Book |
| 27 Sep - 01 Oct, 2026 | Online | Arabic | USD 2,000 | Book |
| 04 Oct - 08 Oct, 2026 | Online | English | USD 2,000 | Book |
| 04 Oct - 08 Oct, 2026 | Online | Arabic | USD 2,000 | Book |
| 11 Oct - 15 Oct, 2026 | Online | English | USD 2,000 | Book |
| 11 Oct - 15 Oct, 2026 | Online | Arabic | USD 2,000 | Book |
| 18 Oct - 22 Oct, 2026 | Online | Arabic | USD 2,000 | Book |
| 18 Oct - 22 Oct, 2026 | Online | English | USD 2,000 | Book |
| 25 Oct - 29 Oct, 2026 | Online | Arabic | USD 2,000 | Book |
| 25 Oct - 29 Oct, 2026 | Online | English | USD 2,000 | Book |
| 01 Nov - 05 Nov, 2026 | Online | Arabic | USD 2,000 | Book |
| 01 Nov - 05 Nov, 2026 | Online | English | USD 2,000 | Book |
| 08 Nov - 12 Nov, 2026 | Online | Arabic | USD 2,000 | Book |
| 08 Nov - 12 Nov, 2026 | Online | English | USD 2,000 | Book |
| 15 Nov - 19 Nov, 2026 | Online | Arabic | USD 2,000 | Book |
| 15 Nov - 19 Nov, 2026 | Online | English | USD 2,000 | Book |
| 22 Nov - 26 Nov, 2026 | Online | Arabic | USD 2,000 | Book |
| 22 Nov - 26 Nov, 2026 | Online | English | USD 2,000 | Book |
| 29 Nov - 03 Dec, 2026 | Online | English | USD 2,000 | Book |
| 29 Nov - 03 Dec, 2026 | Online | Arabic | USD 2,000 | Book |
| 06 Dec - 10 Dec, 2026 | Online | English | USD 2,000 | Book |
| 06 Dec - 10 Dec, 2026 | Online | Arabic | USD 2,000 | Book |
| 13 Dec - 17 Dec, 2026 | Online | Arabic | USD 2,000 | Book |
| 13 Dec - 17 Dec, 2026 | Online | English | USD 2,000 | Book |
| 20 Dec - 24 Dec, 2026 | Online | Arabic | USD 2,000 | Book |
| 20 Dec - 24 Dec, 2026 | Online | English | USD 2,000 | Book |
| 27 Dec - 31 Dec, 2026 | Online | English | USD 2,000 | Book |
| 27 Dec - 31 Dec, 2026 | Online | Arabic | USD 2,000 | Book |
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