Digital Energy and Optimization - Virtual Learning
Course Methodology
This training course will utilize a variety of proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information presented. This includes theoretical presentation of the concepts, but the emphasis will be on the exercises performed by the delegates with the guidance of the instructor.
The delegates will be “learning by doing” as the training course is designed around the project of designing a novel product for the digital world. Delivery will be by presentation, group syndicate exercises, training e-manual, as well as group discussion on the results of the exercises.
Course Objectives
The objective of this training course is to prepare the delegates for the digital world and the requirements of Industry 4.0 as it is becoming present in all the sectors and shows special opportunities in the area of energy preservation and optimization.
At the end of this training course, you will learn to:
- Apply the data mining methodology for energy usage patterns
- Effectively utilize Artificial Intelligence algorithms for real-time optimization
- Identify key areas where the Data Mining and Artificial Intelligence can be utilized
- Understand the benefits through the example cases
- Use Data Mining and Artificial Intelligence methods for optimization of spinning reserves
Target Audience
This Gulf Rowad training course is suitable to a wide range of professionals but will greatly benefit:
- Professionals who wants to learn techniques of Data Mining and Artificial Intelligence
- Team Leaders, Supervisors, Section Heads and Managers
- Professionals who have an interest in Data Science
- Technical Professionals including those in Maintenance, Engineering & Production
- Project Managers
- Anyone interested in optimization and energy consumption reduction
Target Competencies
Organisational Impact
The energy consumption has increased multi-fold, and it continues to be one of the most important, if not the most important issue in the modern world. The modern world simply cannot function without energy, and wastes of energy or shortages create enormous damages and great disturbances. Energy saving and optimization art therefore paramount for the success of any industry, organization or enterprise, and as a result of sending their employees on this training course, organizations can expect to benefit from:
- Acquiring the employees that understand the importance of optimization
- The knowledge of how to create digital twins of the unit, company or a system
- Identify the optimization opportunities
- Understand the use of Artificial Intelligence and Simulation in energy and industry
- Learn the data mining techniques
Personal Impact
Delegates will learn how to perform the data mining, identification of algorithms used in Artificial Intelligence which are beneficial for their respective industries, proper use of the technology, specifically, delegates will acquire:
- The structured way of data mining in their respective industries
- Knowledge on how to differentiate good data from the noise and biased data
- The understanding on how to find hidden patterns within the data
- Step-by-step process of digital twins’ creation
- How to avoid common pitfalls of Industry 4.0
Course Outline
Data Mining and Pattern Recognition
- Data Mining Process
- Data Preparation
- Association and Pattern Recognition
- Data Mining in Energy Industry
- Data Mining-clusters and Outliers
Artificial Intelligence Algorithms
- Artificial Intelligence Development
- Linear Regression
- Logistic Regression
- Decision Tree
- Support Vector Machine
- Other Algorithms Applied in Artificial Intelligence (AI)
Energy Distribution Planning and Optimization
- Energy Storage Planning
- Managing Incidents and Instrument Failures
- Energy Grid Management
- Energy Consumption Forecasting
Developing Digital Twins
- Digitization of Industry and Energy
- Optimal Power Flow Problem Formulation
- Neural Network Application to Optimal Power Flow
- Particle Swarm Optimization for Optimal Power Flow
- Total Transfer Capability Enhancement by Evolutionary Algorithm
Simulation, Machine Learning and Smart Contracts
- Dynamic Simulation of Industry Systems
- Simulation of Unit Commitment Problem
- Machine Learning for Renewable Energy
- Forecasting Renewable Energy Generation
- Smart Contracts within the Energy Industry
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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