This is a theoretical and practical introductory group tuition during which you will be taught common, essential leather crafting and basic sewing techniques.You will be taught how to correctly use hand tools, how to hand sew leather and understand the most common finishing techniques used in bag and accessory making.You will learn about different types of leather and understand how to select the correct type of material(s) for your project. You will receive an overview of the technical aspects of working with leather and constructing bags and accessories such as preparing, marking, cutting, gluing, reinforcing, debossing and more.You will produce your own samples of work to take home with you.You will receive relevant, useful and informative handouts as well as lists of leather and tool suppliers.This is a professional course delivered by a prototype maker and manufacturer, with the aim of providing an overview and hands-on experience on more common leather working practices. At the end of the tuition you will have:– Gained an understanding of leather types and tanning methods– Understood what it means to work with different leather types and thicknesses and have the ability to source and select the correct tools and materials for your projects.– Gained confidence in using specific tools for preparing, marking, finishing and cutting leather.– Understood and practiced leather craft techniques such as beveling and burnishing techniques– Learnt basic leather hand sewing techniquesWHAT WILL BE TAUGHT?Below is a list of topics covered during the classes:– Understanding leather: overviews on types of leather, tanning, finishings and best use– Vegan leathers: an overview on different types and features– Understanding the importance of choosing the right materials for your project and the right tools for your materials– Leather preparing, pattern placement and marking on leather– Cutting complex shapes using a variety of tools– Using leather punches– Understanding the use of skiving, beveling and grooving– Finishing leather edges: painting vs burnishing– Using various leather glues and tapes– Understand the use of reinforcements, fusings and stabilisers to back leather– To learn basic leather hand sewing techniques– To understand the tools and materials used in saddle stitching– Prototyping and manufacturing leather goods: mentions of different working methods, machines and tools IMPORTANT TO KNOW:We will always try to cover as much on the syllabus as possible and depending on your ability and previous experience, we might not be able to complete the program or we might instead be able to teach you additional techniques relating to the above listed topics, such as:– Understanding fittings, closure types, fastening techniques and tools: sam browns, magnets, pop buttons, eyelets, etc– Sew and finish simple zips styles, handles and straps– Understanding options and the construction of how to line bags and accessories INCLUDED IN THE COURSE:You will be provided with useful digital and paper handouts which contain:– A list of tools and materials used during the lesson(s), including a description of what they are and how they are used– A list of recommended suppliers for both leather and fittings (physically in London and online)– A glossary containing information about leather types and characteristics WHAT ARE THE ENTRY REQUIREMENTS?This course is suitable for total beginners, beginners with some experience and intermediate.You should be able to use measurements and understand verbal and written English instructions. ARE THERE ANY OTHER COSTS? IS THERE ANYTHING I NEED TO BRING?Materials are included.Feel free to bring a notepad, if you would like to take some notes, we will provide the rest. HOW LONG IS THIS TUITION?:This tuition will require up to 6.5 hours to complete.We aim to provide customised and high quality tuition services and by only allowing up to 6 students at a time, we are able to focus on each person needs and interests.As every student has a different level of ability and previous experience, this course might lead some students to complete the core aspects of the lesson in a shorter time frame than others.Students who complete the course early will be welcome to stay and use the studio facilities to exercise on the topics of the lesson.
About this training course Artificial lift systems are an important part of production operations for the entire lifecycle of an asset. Often, oil and gas wells require artificial lift for most of the life cycle. This 5-day training course offers a thorough treatment of artificial lift techniques including design and operation for production optimization. With the increasing need to optimize dynamic production in highly constrained cost environments, opportunities and issues related to real-time measurements and optimization techniques needs to be discussed and understood. Artificial lift selection and life cycle analysis are covered. These concepts are discussed and reinforced using case studies, quizzing tools, and exercises with software. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion. Understanding of these important production concepts is a must have to exploit the existing assets profitably. Unique Features: Hands-on usage of SNAP Software to solve gas-lift exercises Discussion on digital oil field Machine learning applications in gas-lift optimization Training Objectives After the completion of this training course, participants will be able to: Understand the basics and advanced concepts of each form of artificial lift systems including application envelope, relative strengths, and weaknesses Easily recognize the different components from downhole to the surface and their basic structural and operational features Design and analyze different components using appropriate software tools Understand challenges facing artificial lift applications and the mitigation of these challenges during selection, design, and operation Learn about the role of digital oilfield tools and techniques and their applications in artificial lift and production optimization Learn about use cases of Machine learning and artificial intelligence in the artificial lift Target Audience This training course is suitable and will greatly benefit the following specific groups: Production, reservoir, completion, drilling and facilities engineers, analysts, and operators Anyone interested in learning about selection, design, analysis and optimum operation of artificial lift and related production systems will benefit from this course. Course Level Intermediate Advanced Training Methods The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization. Course Duration: 5 days in total (35 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts. Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software. Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations
About this Training Course There are various kinds of geophysical data available. They are separated into seismic and non-seismic (multi-physics) data. Non-seismic or multi-physics data (which includes gravity, magnetics, electrical, electromagnetics, spectral etc - apart from providing complimentary information to seismic) is the main source of information for very shallow subsurface applications such as engineering, mapping pollution, archaeology, geothermal energy, and related areas. This 5 full-day blended course will focus specifically on seismic data which is the main method used in the Oil & Gas industry. In this blended course, participants will be equipped to understand that seismic data represents the movement of the surface, resulting from waves generated by a source, dynamite or vibrator which are reflected by changes in the subsurface rocks. The basic principles of acquisition and processing will be explained and insights into advanced methods, allowing a much more accurate interpretation of seismic data than previously considered possible, will also be provided. This blended course contains an introduction to Machine Learning and its important role in all aspects of seismic acquisition, processing, and interpretation. There is no need to know in detail how the algorithms work internally but it is necessary to know how to use them correctly to achieve optimum results. Training Objectives By attending this course, participants will be able to acquire the following: Obtain an understanding of the strengths and limitations of geophysical methods, specifically seismic, and the costs and risks involved, and how to reduce these. Be able to communicate more effectively with staff in other disciplines. Understand the potential applications of seismic data and know how to formulate the requirements needed for prospect and field evaluation. Gain an awareness of modern seismic technology. Apply the learning in a series of practical, illustrative exercises. Know what types of questions to ask to assess the necessary quality of a seismic project in its role in a sequence of E&P activities Target Audience The blended course is intended for non-geophysicists who have intensive interaction with geophysicists. But it may be of interest to those who want to know about the recent progress made in geophysics, leading to amazing imaging results, which could not be imagined a decade ago. The blended course will bring to the attention of the geologists, petrophysicists and reservoir/petroleum engineers an awareness of how the data they will work with is acquired and processed by the geophysicist. It will introduce the concepts that are of importance in geophysics and thus relevant for non-geophysicists to know and be able to communicate with geophysicists as well as formulate their requests. Course Level Intermediate Trainer Your expert course leader has degree in Geology (University of Leiden), a Master's degree in Theoretical Geophysics (University of Utrecht) and a PhD in Utrecht on 'Full wave theory and the structure of the lower mantle'. This involved forward modelling of P- and S-waves diffracted around the core-mantle boundary and comparison of the frequency-dependent attenuation of the signal with those obtained from major earthquakes observed at long offsets in the 'shadow zone' of the core. These observations were then translated into rock properties of the D' transition zone. After his PhD, he joined Shell Research in The Netherlands to develop methods to predict lithology and pore-fluid based on seismic, petrophysical and geological data. He subsequently worked for Shell in London to interpret seismic data from the Central North Sea Graben. As part of the Quantitative Interpretation assignment, he was also actively involved in managing, processing and interpreting Offshore Seismic Profiling experiments. After his return to The Netherlands, he headed a team for the development of 3D interpretation methods using multi-attribute statistical and pattern recognition analysis on workstations. After a period of Quality Assurance of 'Contractor' software for seismic processing, he became responsible for Geophysics in the Shell Learning Centre. During that period, he was also a part-time professor in Applied Geophysics at the University of Utrecht. From 2001 to 2005, he worked on the development of Potential Field Methods (Gravity, Magnetics) for detecting oil and gas. Finally, he became a champion on the use of EM methods and became involved in designing acquisition, processing and interpretation methods for Marine Controlled Source EM (CSEM) methods. After his retirement from Shell, he founded his own company, specialising in courses on acquisition, processing and interpretation of geophysical data (seismic, gravity, magnetic and electromagnetic data), providing courses to International and National energy companies. In the last couple of years, he became keenly interested in the use of Machine Learning in Geophysics. Apart from incorporating 'Artificial Intelligence' in his courses, he also developed a dedicated Machine Learning course for geophysics. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations
This course is not suitable for total beginners. To attend this course, you must already have some experience with industrial machines and be able to operate and set up a walking foot independently, or have attended our MODULE 3 – INDUSTRIAL MACHINE TRAINING. Summary of topics covered in the class: – Pattern making, pattern development and pattern vocabulary – Leather preparation, pattern placement, and leather marking – Leather cutting, gluing, and reinforcing – Patterns development, assembling and making for different card holder constructions By the end of the tuition, you will have: – Developed your understanding of pattern drafting and pattern development – Understood the concept of seam, folding, and trimming allowances when drafting patterns – Created some finished patterns, constructed and completed up to 3 finished card holders (depending on your personal abilities the quantity might change) – Learned how to use your patterns to correctly cut your material, minimising waste and using the best parts of a hide/skin – Worked with a variety of tools for pattern making and leatherworking, as well as various types of leather – Developed essential leather craft skills such as preparation, marking, finishing, cutting, and more – Obtained a basic understanding of the differences and best uses of reinforcements, stiffeners and stabilisers Included in the course: You will receive useful paper handouts containing: – A list of tools and materials used during the lesson(s), with descriptions and usage instructions – A list of recommended suppliers for leather and fittings, both in London and online – A glossary containing pattern making terms and general guidelines for pattern drafting All materials are included, there are no additional costs. Find all modules here: https://the-london-leather-workshop.cademy.co.uk/
About this training course Gas-lift is one of the predominant forms of artificial lift used for lifting liquids from conventional, unconventional, onshore and offshore assets. Gas-lift and its various forms (intermittent lift, gas-assisted plunger lift) allows life of well lift-possibilities when selected and applied properly. This 5-day training course is designed to give participants a thorough understanding of gas-lift technology and related application concepts. This training course covers main components such as application envelope, relative strengths and weaknesses of gas-lift and its different forms like intermittent lift, gas-assisted plunger lift. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion. Unique Features: Hands-on usage of SNAP Software to solve gas-lift exercises Discussion on digital oil field Machine learning applications in gas-lift optimization Training Objectives After the completion of this training course, participants will be able to: Understand the fundamental theories and procedures related to Gas-Lift operations Easily recognize the different components of the gas-lift system and their basic structural and operational features Be able to design a gas-lift installation Comprehend how digital oilfield tools help address ESP challenges Examine recent advances in real-time approaches to the production monitoring and lift management Target Audience This training course is suitable and will greatly benefit the following specific groups: Production, reservoir, completion, drilling and facilities engineers, analysts, and operators Anyone interested in learning about implications of gas-lift systems for their fields and reservoirs Course Level Intermediate Advanced Training Methods The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization. Course Duration: 5 days in total (35 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts. Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software. Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations
Cloud deployment training course description This course covers the important topics every cloud professional needs, including, configuration and deployment, security, maintenance, management, and troubleshooting. It covers all aspects of cloud computing infrastructure and administration, with a practical focus on real-world skills. It will help you to master the fundamental concepts, terminology, and characteristics of cloud computing. Deploy and implement cloud solutions, manage the infrastructure, and monitor performance. You will also be able to install, configure, and manage virtual machines. What will you learn Cloud services, models, and characteristics. Virtualization components, installation, and configuration. Infrastructure configurations and optimization. Resource management and specific allocations. IT security concepts, tools, and best practices. Recovery, availability and continuity in the cloud. Cloud deployment training course details Who will benefit: IT professionals looking to deploy and implement cloud solutions, manage the infrastructure, and monitor performance, Install, configure, and manage virtual machines. Prerequisites: Introduction to virtualization. Duration 5 days Cloud deployment training course contents Preparing to Deploy Cloud Solutions Deploying a Pilot Project Testing Pilot Project Deployments Designing a Secure and Compliant Cloud Infrastructure Designing and Implementing a Secure Cloud Environment Planning Identity and Access Management for Cloud Deployments Determining CPU and Memory Sizing for Cloud Deployments Determining Storage Requirements for Cloud Deployments Analysing Workload Characteristics to Ensure Successful Migration Maintaining Cloud Systems Implementing Backup, Restore, Disaster Recovery, and Business Continuity Measures Analysing Cloud Systems for Performance Analysing Cloud Systems for Anomalies and Growth Forecasting Troubleshooting Deployment, Capacity, Automation, and Orchestration Issues Troubleshooting Connectivity Issues Troubleshooting Security Issues
About this Course This 5 full-day course presents the most modern statistical and mathematical forecasting frameworks used by practitioners to tackle the load forecasting problem across short time and long time scales. The course presents practical applications to solving forecasting challenges, supported by real life examples from large control areas. It presents the weather impacts on the load forecasts and the methodologies employed to quantify the weather effect and building a repository of weather normal data. A good load forecast methodology must improve its forecasting accuracy and support a consistent load forecasting process. The load forecasting widely used in the power industry has evolved significantly with the advancement and adoption of Artificial Intelligence techniques such as Machine Learning. With the increased penetration of inverter-based resources, the operation of electric grids grew in complexity, leading to load forecasts that are updated more frequently than once a day. Furthermore, several jurisdictions adopted a smaller granularity than the hourly load forecasts in the effort to reduce the forecasting uncertainties. On the generation side, fuel forecasting professionals must meet energy requirements while making allowance for the uncertainty on both the demand and the supply side. This training course will also feature a guest speaker, who is a Ph.D candidate to provide insights into the most modern aspects of Artificial Intelligence in the context of load forecasting. Training Objectives This course offers a comprehensive approach to all aspects of load forecasting: Gain a perspective of load forecasting from both operators in the generating plant and system operators. Understand and review the advanced load forecasting concepts and forecasting methodologies Learn the application of Artificial Neural Networks and Probabilistic Forecasting methods to manage forecasting uncertainties in short time frames Appreciate market segmentation and econometric framework for long term forecasts Find out the most recent practical application of load forecasting as examples from large power companies Get access to recent industry reports and developments Target Audience Energy load forecasting professionals from power plant and system operators Energy planners and energy outlook forecasters and plant operators Fuel procurement professionals Planners and schedulers of thermal generating units Course Level Intermediate Trainer Your expert course instructor is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Our Key expert delivered over 60 specialized seminars to executives and engineers from Canada, Europe, South and North America, Middle East, South East Asia and Japan. Few examples are: Modern Power System in Digital Utilities - The Energy Commission, Malaysia and utilities in the Middle East, GCCIA, June 2020 Assessment of OETC Control Centre, Oman, December 2019 Demand Side management, Load Forecasting in a Smart Grid, Oman, 2019 Renewable Resources in a Smart Grid (Malaysia, Thailand, Indonesia, GCCIA, Saudi Arabia) The Modern Power System: Impact of the Power Electronics on the Power System The Digital Utility, AI and Blockchain Smart Grid and Reliability of Distribution Systems, Cyme, Montreal, Canada Economic Dispatch in the context of an Energy Market (TNB, Sarawak Energy, Malaysia) Energy Markets, Risk Assessment and Financial Management, PES, IEEE: Chicago, San Francisco, New York, Portugal, South Africa, Japan. Provided training at CEO and CRO level. Enterprise Risk methodology, EDP, Portugal Energy Markets: Saudi Electricity Company, Tenaga National Berhad, Malaysia Reliability Centre Maintenance (South East Asia, Saudi Electricity Company, KSA) EUSN, ENERGY & UTILITIES SECTOR NETWORK, Government of Canada, 2016 Connected+, IOT, Toronto, Canada September 2016 and 2015 Smart Grid, Smart Home HomeConnect, Toronto, Canada November 2014 Wind Power: a Cautionary Tale, Ontario Centre for Public Policy, 2010 POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations
NPORS Plant Machinery Marshal (N133)
Windows clustering training course description This course covers high availability and disaster recovery technologies such as live migration, storage migration and Hyper-V Replica, as well as providing indepth coverage of failover clustering including a detailed implementation of failover clustering of Hyper- V using SoFS. The course also covers System Center Virtual Machine Manager and implementing Network Load Balancing (NLB) and load balancing clusters. What will you learn Plan and implement a failover cluster. Describe managing server roles and clustering resources. Implement and manage virtual machines. Use System Center Virtual Machine Manager. Describe cloud-based storage and high availability solutions. Implement a Network Load Balancing (NLB) cluster. Windows clustering training course details Who will benefit: Technical staff working with Microsoft clusters. Prerequisites: Supporting Microsoft Windows server Duration 3 days Windows clustering training course contents High Availability in Windows Server Defining levels of availability, High Availability and disaster recovery solutions with Hyper-V Virtual Machines, High Availability with failover clustering in Windows Server. Hands on Configuring High Availability and Disaster Recovery. Implementing failover clustering Planning a failover cluster, creating a new failover cluster. Hands on Creating and Administering a Cluster. Server roles and clustering resources Configuring highly available applications and services on a failover cluster, managing and maintaining a failover cluster, troubleshooting a failover cluster, implementing site high availability with multisite failover clusters. Hands on Managing server roles and clustering resources. Failover clustering with Hyper-V Overview of integrating Hyper-V with failover clustering, implementing Hyper-V with failover clustering, managing and maintaining Hyper-V Virtual Machines on failover clusters. Hands on Implementing failover clustering by using Hyper-V Storage Infrastructure Management with Virtual Machine Manager Virtual Machine Manager, managing storage infrastructure with Virtual Machine Manager, provisioning failover clustering in Virtual Machine Manager. Hands on Managing storage infrastructure. Cloud-Based storage and High Availability Azure storage solutions and infrastructure, cloud integrated storage with StorSimple, disaster recovery with Azure Site Recovery. Hands on Managing cloud-based storage and high availability Network Load Balancing Clusters Overview of NLB, configuring an NLB cluster, planning NLB. Hands on Implementing a Network Load Balancing Cluster
MPEG training course description This course studies the MPEG standards for video and audio compression. A major focus is on MPEG-4 and MPEG-TS. Hands on includes decoding and analysing MPEG streams. What will you learn Recognise the main MPEG standards. Describe the techniques used in MPEG video and audio compression. Compare MPEG2m MPEG4 and MPEG-H. Describe the MPEG-TS. Analyse MPEG streams. MPEG training course details Who will benefit: Anyone working with MPEG. Prerequisites: None. Duration 2 days MPEG training course contents Introduction What is MPEG? MPEG and VCEG, MPEG 1, MPEG 2, MPEG-3, MPEG-4, MPEG-H, others, codecs and containers, licensing and patents, parts and layers (System, Video, Audio, others). MPEG2 DVD, DVB, characteristics, MPEG2 Part2, audio MPEG2 Part 7 (AAC). MPEG tools Wireshark, vlc, analysers, decoders, ffmpeg, wowzer. MPEG2 Video compression Sampling, bit rates, resolution. Inter and Intra frame coding, I, B, P frames, GOP, slices, blocks, macroblocks. Motion estimation. Hands on Analysing MPEG frames. MPEG4 Profiles and levels, Enhancements, Parts 1,2,3, Part 10 and AVC, Part 14 and mp4. Performance versus MPEG2. MPEG audio Coding, frequencies, bit rates. MPEG-TS PES, Transport Streams, TS elements, packets, PID, Programs, PSI, PAT, PMT, synchronisation, PCR, PTS. MPEG-H Part 2 HEVC, benefits, improvements. Video codecs What is a CODEC, pictures and audio, digitisation, sampling, quantisation, encoding, compressing.