452 Developer courses in Cardiff delivered Live Online

About this Training Course Liquefied Natural Gas (LNG) has provided intercontinental mobility to natural gas, which now provides about 25% of the global primary energy. Being the cleanest fossil fuel, natural gas/LNG consumption is forecasted to grow in all future scenarios. With the entry of various players, including Trading companies, the LNG value chain is becoming increasingly complex, and a solid understanding of its economics and management of its interfaces have become crucial to identify and assess investment opportunities and risks. Recent market disturbances caused by COVID-19, Oil & Gas price instabilities - coupled with the political (Ukraine/Russia) challenges - make a deep understanding of LNG Value Chain Logistics and Economics even more essential to ensure the security of energy supplies sustainably and profitably. This intermediate level 3 full-day course starts with a concise introduction to the LNG business. Thereafter, the elements of the LNG value chain are described, and their individual economics analysed. A Business Activity Model along the value chain will be developed and discussed in depth, covering the following key processes: 'Buy Gas - Transport Gas - Liquefy Gas - Sell LNG/Products - Ship LNG - Regasify LNG' The integrated chain economics will then be developed and quantified. A hands-on group workshop/exercise developing the economic case of a full-sized Liquefaction project will be carried out, considering the forecasted cash flows throughout the project life, the location of the plant, its markets, project sensitivities and profitability assessment. Participants will be provided with Excel based tools/models (LNG Liquefaction project development Net Present Value (NPV) analyses, Shipping Freight Calculations and Economics) to work through the exercises and also for their future personal use. Training Objectives After the completion of this course, participants will be able to: Understand how the LNG Value Chain operates, bound by the relevant Contracts and Agreements. Learn the basic economic parameters (operating, capital costs, financing, profitability) of each major element of the value chain. Appreciate the complexity of the value chain, and the associated opportunities and risks. Develop quantitative project evaluation skills. Explore options to maximise profitability in a given LNG value chain. Discuss best practices on how to manage, steer and govern these activities. Target Audience Technical, Operational, Shipping, Commercial, Project and Governance professionals who are already active in a specific section of the LNG Value Chain will directly benefit in developing a wider and deeper perspective on how the LNG Value Chain operations and can be optimised. Managers (Technical, Financial, Legal and Governance) less familiar with the specifics of the LNG Industry will also benefit from attending this VILT course, as they will obtain the required background to be able to set sharper targets, suitable performance indicators, and governance and performance assessment guidelines for units engaged in the chain. The course is most relevant for professionals engaged in the LNG industry at: National and International Oil & Gas/Energy Companies LNG Importers/Exporters/Traders/Shippers Government & Regulatory Agencies Finance Institutions It will also apply to the following audience: Business Development Managers Corporate Planning Professionals Project Developers Supply Planners & Scheduling Professionals Regulators Tax & Finance Advisors Compliance Officers Equity Analyst and Bankers Joint Venture Representatives, Board Directors Negotiators and Contracting Staff Trading Professionals Course Level Intermediate Trainer Your expert course leader is an Oil & Gas/LNG professional with more than 35 years of international experience, majority of which was gained at Shell International Joint Ventures engaged in Oil Refining, Supply / Trading, Gas Supply and LNG Businesses in the Netherlands, France, Thailand, Dominican Republic and Nigeria. Since 2004, he has had several roles in the management of the LNG Value Chain including the Commercial Operational Management of Nigeria LNG (NLNG). He played an active role in the start-up and integration of LNG trains 4, 5 and 6 with NLNG becoming the 3rd largest LNG producer in the world in 2007. Commercial operations spanned 4 Gas Supply, 11 LNG Sales & Purchase Agreements, ad-hoc LPG and Condensate Sales and LNG Ship Chartering contracts. Under his supervision, more than 2,000 LNG cargoes were exported. He was part of the organizational transformation of the company from a Project-based set-up to a Production / Commercial based structure and implemented an 'Integrated Planning and Scheduling Department' in which he optimized the value chain (Buy-Gas - Liquify Gas to LNG - Sell - Ship LNG). Staff competence management was one of his focus areas during this period. He was also the NLNG representative on JV Technical, Commercial, Shipping Committees where he interfaced with Government & Regulatory authorities. In 2014, he was appointed as Shell Shareholder representative to NLNG and became a Non-Executive Board member to NLNG companies, including Bonny Gas Transport (BGT) managing 24 LNG Ships. During this period, he was involved in the Economic and Technical steering of the Shipping Fleet and Liquefaction Plant Rejuvenation projects and a further capacity expansion of liquefaction plant which resulted in the achievement of NLNG train 7 project FID in 2019. Since 2016, he has been active as an independent consultant. He co-authored 2 patents and more than 30 published papers/presentations. He holds a PhD from Delft University of Technology in the Netherlands and a MSc and BSc in Chemical Engineering from the University of Birmingham, UK. 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

MySQL Performance & Tuning training course description This MySQL Performance & Tuning course is designed for Database Administrators, Application Developers and Technical Consultants who need to monitor and tune the performance of MySQL servers and databases. The course provides practical experience in monitoring and tuning MySQL servers and databases. Note: This MySQL Performance & Tuning course does not cover clustering (other than at overview level), replication or non-standard storage engines such as Falcon and PBXT. What will you learn Develop a monitoring and tuning plan Use server configuration and status variables. Identify and improve problem queries. Make efficient use of indexes. Monitor and size memory caches and locks. Tune the MyISAM and InnoDB storage engine. Evaluate the use of partitioning for performance. MySQL Performance & Tuning training course details Who will benefit: Anyone who wishes to monitor and tune MySQL performance. Prerequisites: Delegates must have a working knowledge of MySQL Database Administration Duration 3 days MySQL Performance & Tuning training course contents Introduction to performance tuning Tuning overview, Resolving performance issues, Recommended approach to tuning, Items to evaluate, Where to look, Planning a monitoring routine, Building a new database for performance, Tuning an existing database, Setting suitable goals. MySQL performance tuning tools Administration tools, the information schema, performance-related SHOW commands, benchmarking tools, the MySQL performance schema, MonYog. Hands on Obtaining performance information. Schema design Normalisation, de-normalisation, naming conventions, load generation, stress testing and benchmarking tools, selecting data types, data types, character sets, choosing storage engines. Hands on effects of design on performance. Statement tuning Overview of statement tuning, identifying problem queries, the optimizer, explain, explain extended. Hands on identifying problem queries and using explain. Indexes Index overview, Types of index, Index tuning, Indexes and joins. Hands on Indexes and performance. Server configuration and monitoring Server configuration variables, server status variables, table cache, multi-threading, connection issues, query cache. Hands on setting and interpreting server variables and caching. Locking Types of locking, locking and storage engines, effects of locking on performance. Hands on locking and performance. The InnoDB engine Transactions, crash recovery, locking, monitoring InnoDB, caches and buffers, configuring data files, configuring the log files. Hands on InnoDB configuration and performance. Other storage engines MyISAM engine, merge engine, archive engine, memory engine, blackhole engine, CSV engine, the Spider engine, the ColumnStore engine, the MyRocks engine, mixing sorage engines. Hands on storage engine performance. Overview of clustering and performance Advantages of performance, advantages of clustering, performance issues and clustering, the NDBCluster engine, the Galera cluster, the Percona XtraDB cluster, MySQL InnoDB cluster, the federated engine, the federatedX engine, overview of other high availability techniques. NOSQL and Mencached overview. Dumping and loading data SQL statements versus delimited data, parameters affecting dump performance, parameters affecting load performance. Hands on dump and load performance. Partitioned tables Partitioned tables concepts, range partitioning, hash partitioning, key partitioning, list partitioning, composite partitioning or subpartitioning, partition pruning. Hands on partitioned table performance.

Maximize the value of data assets in the oil and gas sector with EnergyEdge's assessment-based training course on Python programming and analytics.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for software developers, testers, and architects who design and develop software in various programming languages and platforms, including desktop, web, cloud, and mobile, and who want to improve their ability to deliver software that is of high quality, particularly regarding security and privacy. This course is also designed for students who are seeking the CertNexus Cyber Secure Coder (CSC) Exam CSC-210 certification Overview In this course, you will employ best practices in software development to develop secure software.You will: Identify the need for security in your software projects. Eliminate vulnerabilities within software. Use a Security by Design approach to design a secure architecture for your software. Implement common protections to protect users and data. Apply various testing methods to find and correct security defects in your software. Maintain deployed software to ensure ongoing security... The stakes for software security are very high, and yet many development teams deal with software security only after the code has been developed and the software is being prepared for delivery. As with any aspect of software quality, to ensure successful implementation, security and privacy issues should be managed throughout the entire software development lifecycle. This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects. You will learn general strategies for dealing with security defects and misconfiguration, how to design software to deal with the human element in security, and how to incorporate security into all phases of development. Identifying the Need for Security in Your Software Projects Identify Security Requirements and Expectations Identify Factors That Undermine Software Security Find Vulnerabilities in Your Software Gather Intelligence on Vulnerabilities and Exploits Handling Vulnerabilities Handle Vulnerabilities Due to Software Defects and Misconfiguration Handle Vulnerabilities Due to Human Factors Handle Vulnerabilities Due to Process Shortcomings Designing for Security Apply General Principles for Secure Design Design Software to Counter Specific Threats Developing Secure Code Follow Best Practices for Secure Coding Prevent Platform Vulnerabilities Prevent Privacy Vulnerabilities Implementing Common Protections Limit Access Using Login and User Roles Protect Data in Transit and At Rest Implement Error Handling and Logging Protect Sensitive Data and Functions Protect Database Access Testing Software Security Perform Security Testing Analyze Code to find Security Problems Use Automated Testing Tools to Find Security Problems Maintaining Security in Deployed Software Monitor and Log Applications to Support Security Maintain Security after Deployment

About this Virtual Instructor Led Training (VILT)  Electrification of the transportation sector will impact the power system in several ways. Besides the additional load, local impact on the grid needs to be managed by the grid operators. Simultaneously charging of many electric vehicles (EVs) might exceed the limits in specific locations. On the other hand, EVs can provide flexibility and other ancillary services that will help grid operators. This 3 half-day VILT course will provide a complete overview of integrating electric vehicles (EVs) into the power grid. It will cover the whole value chain from grid operations to the car battery. This includes the control room, possible grid reinforcement, demand side management and power electronics. This course will demonstrate the impact on the grid and solutions for a safe & cost-effective grid plan and operation, with examples of successful integration of EVs. The course will also provide vital knowledge about technology used for EVs such as power electronics, demand side management, communication and batteries. In this context, the focus will be on power electronics as it has the highest impact on the grid. The grid planning tool, pandapower, is introduced as an open source tool for power system modelling. The set-up of the training course allows for discussion and questions. Questions can be formulated by the participants upfront or during the training. This course is delivered in partnership with Fraunhofer IEE. Training Objectives At the end of this course, the participants will: Understand the charging options for EVs and its impact on the grid and batteries Identify system services for EVs with regards to voltage quality at the point of common coupling Discover what are the 'grid friendly' and grid supporting functions in EVs Uncover the different applications, standards and data researched on EVs Examine the application of a grid planning tool (pandapower) for power system modelling Be able to develop code snippets with pandapower Apply and execute a code example for power system modelling with pandapower Target Audience EV and grid project developers and administrators Power grid operators and planners EPC organisations involved in grid development EV/ battery manufacturers and designers EV transport planners and designers Government regulators and policy makers Training Methods The VILT will be delivered online in 3 half-day sessions comprising 4 hours per day, with 2 x 10 minutes breaks per day, including time for lectures, discussion, quizzes and short interactive exercises. Additionally, some self-study will be requested. Participants are invited but not obliged to bring a short presentation (10 mins max) on a practical problem they encountered in their work. This will then be explained and discussed during the VILT. A short test or quiz will be held at the end of every session/day. Trainer Our first course expert is Head of Department Converters and Electrical Drive Systems at Fraunhofer IEE and Professor for Electromobility and Electrical Infrastructure at Bonn-Rhein-Sieg University of Applied Sciences. He received his engineering degree in automation in 2008 by the THM Technische Hochschule Mittelhessen (FH Giessen-Friedberg). Afterwards he studied power engineering at University of Kassel and received his diploma certificate in 2010. In 2016 he received the Ph.D. (Dr.-Ing.) from the University of Hannover. The title of his dissertation is Optimized multifunctional bi-directional charger for electric vehicles. He has been a researcher at the Fraunhofer IEE in Kassel since 2010 and deals with power converters for electric vehicles, photovoltaics and wind energy. His current research interests include the bidirectional inductive power transfer, battery charger and inverter as well as new power electronic components such as SiC MOSFETs and chokes. Additionally, our key expert is Chairman of the IEEE Joint IAS/PELS/IES German Chapter and a member of the International Scientific Committee of the EPE Association. Our second course expert is deputy head of energy storage department at Fraunhofer IEE. Prior to this he was the Director of Grid Integration department at SMA Solar Technology AG, one of the world's largest manufacturers of PV power converters. Before joining SMA, our course expert was manager of the Front Office System Planning at Amprion GmbH (formerly RWE TSO), one of the four German transmission system operators. He holds a degree of electrical engineering of the University of Kassel, Germany. In 2003 he finished his Ph.D. (Dr.-Ing.) on the topic of wind power forecasting at the 'Institute of Solar Energy Supply Technology' (now Fraunhofer IEE) in Kassel. In 2004 he started his career at RWE TSO with main focus on wind power integration and congestion management. Our course expert is chairman of the IEC SC 8A 'Grid Integration of Large-capacity Renewable Energy (RE) Generation' and has published several papers about grid integration of renewable energy source and forecasting systems on books, magazines, international conferences and workshops. Our third course expert is Research Associate at Fraunhofer IEE. He is actively working on different projects related to the integration of electric vehicle charging into the electric distribution grid. The focus of this work concerns time series based simulations for grid planning and operation in order to investigate the effect of a future rollout of electric vehicles and charging infrastructure on economics e.g. costs for grid reinforcement. He completed his master degree (MSc.) in Business Administration and Engineering: Electrical Power Engineering at RWTH Aachen University, Germany. Our trainers are experts from Fraunhofer Institute for Energy Economics and Energy System Technology (Fraunhofer, IEE), Germany. The Fraunhofer IEE researches for the national and international transformation of energy supply systems 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 about post training coaching support and fees applicable for this. Accreditions And Affliations

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course is people who are moving into a database role, or whose role has expanded to include database technologies. Developers that deliver content from SQL Server databases will also benefit from this material. Overview After completing this course, you will be able to: Describe key database concepts in the context of SQL Server Describe database languages used in SQL Server Describe data modelling techniques Describe normalization and denormalization techniques Describe relationship types and effects in database design Describe the effects of database design on performance Describe commonly used database objects This course is provided as an introductory class for anyone getting started with databases. It will be useful to programmers and other IT professionals whose job roles are expanding into database management. Students will learn fundamental database concepts through demonstrations and hands-on labs on a SQL Server instance. This material updates and replaces course Microsoft course 10985 which was previously published under the same title. Module 1: Introduction to databases Introduction to Relational Databases Other Databases and Storage Data Analysis SQL Server Database Languages Module 2: Data Modeling Data Modelling Designing a Database Relationship Modeling Module 3: Normalization Fundamentals of Normalization Normal Form Denormalization Module 4: Relationships Introduction to Relationships Planning Referential Integrity Module 5: Performance Indexing Query Performance Concurrency Module 6: Database Objects Tables Views Stored Procedures, Triggers and Functions

Duration 3 Days 18 CPD hours This course is intended for This course is intended for IT professionals who are experienced in general Windows Server and Windows Client administration. Students should have a foundational knowledge of Windows PowerShell, which they can obtain by taking course 10961C: Automating Administration with Windows PowerShell. In addition, this course provides scripting guidance for Microsoft Azure administrators and developers who support development environments and deployment processes. Overview After completing this course, you will be able to: Create advanced functions. Use Microsoft .NET Framework and REST API in Windows PowerShell. Handle script errors. Use XML, JSON, and custom formatted data. Manage Microsoft Azure resources Analyze and debug scripts Understand Windows PowerShell workflow. This course teaches students how to automate administrative tasks using PowerShell. Students will learn crucial scripting skills such as creating advanced functions, writing controller scripts, and handling script errors. Candidates will learn how to use PowerShell when working with Microsoft Azure, SQL Server, Active Directory, IIS, Windows PowerShell Workflow, .NET resources, the REST API and XML, CSV & JSON formatted data files.This course replaces retired Microsoft course 10962. Module 1: Creating advanced functions Lesson 1: Converting a command into an advanced function Lesson 2: Creating a script module Lesson 3: Defining parameter attributes and input validation Lesson 4: Writing functions that accept pipeline input Lesson 5: Producing complex pipeline output Lesson 6: Using comment-based Help Lesson 7: Using Whatif and Confirm parameters Module 2: Using Microsoft .NET Framework and REST API in Windows PowerShell Lesson 1: Using .NET Framework in PowerShell Lesson 2: Using REST API in PowerShell Module 3: Writing controller scripts Lesson 1: Understanding controller scripts Lesson 2: Writing controller scripts with a user interface Lesson 3: Writing controller scripts that create reports Module 4: Handling script errors Lesson 1: Understanding error handling Lesson 2: Handling errors in a script Module 5: Using XML, JSON, and custom-formatted data Lesson 1: Working with XML formatted data Lesson 2: Working with JSON formatted data Lesson 3: Working with custom-formatted data Module 6: Enhancing server management with Desired State Configuration and Just Enough Administration Lesson 1: Implementing Desired State Configuration Lesson 2: Implementing Just Enough Administration Module 7: Analyzing and debugging scripts Lesson 1: Debugging in Windows PowerShell Lesson 2: Analyzing and debugging an existing script Module 8: Understanding Windows PowerShell Workflow Lesson 1: Understanding Windows PowerShell Workflows Lesson 2: Running Windows PowerShell Workflows

Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution

About this Virtual Instructor Led Training (VILT) Hydrogen will play an increasingly critical role in the future of energy system as it moves forward to supplement and potentially replace fossil fuels in the long run. Offshore wind offers a clean and sustainable renewable resource for green hydrogen production. However, it can also be volatile and presents inherent risks that need to be managed. Even though offshore production of hydrogen has yet to achieve a high state of maturity, many current projects are already dealing with the conditions and effects of offshore production of hydrogen and are grappling with the technological requirements and necessary gas transportation with grid integration. This 2 half-day Virtual Instructor Lead Training (VILT) course will examine the technological options for on-site production of hydrogen by electrolysis (onshore or offshore directly at the platform) as well as the transport of hydrogen (pipeline or ship). This VILT course will also explore the economic considerations and the outlook on future market opportunities. There will be exercises for the participants to work on over the two half-days. This course is delivered in partnership with Fraunhofer IEE. Training Objectives By the end of this VILT course, participants will be able to: Understand the technological attributes and options for green hydrogen production based on electricity from offshore wind. Explore the associated economic analysis for offshore wind hydrogen production, including CAPEX, OPEX, LCOE and LCOH Identify the critical infrastructure and technical configuration required for offshore green hydrogen including transportation networks and grid connectivity Learn from recent findings from current Research & Development projects concerning the differences between onshore and offshore hydrogen production. Target Audience This VILT course is intended: Renewable energy developers and operators Offshore oil & gas operators Energy transport and marine operators Energy policy makers and regulators IPPs and power utilities Training Methods The VILT course will be delivered online in 2 half-day sessions comprising 4 hours per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 2 half-day sessions, 4 hours per session (8 hours in total). Trainer Trainer 1: Your expert course leader is Director of Energy Process Technology Division at the Fraunhofer Institute for Energy Economics and Energy System Technology, IEE. The research activities of the division link the areas of energy conversion processes and control engineering. The application fields covered are renewable energy technologies, energy storage systems and power to gas with a strong focus on green hydrogen. From 2006 - 2007, he worked as a research analyst of the German Advisory Council on Global Change, WBGU, Berlin. He has extensive training experience from Bachelor and Master courses at different universities as well as in the context of international training activities - recently on hydrogen and PtX for partners in the MENA region and South America. He holds a University degree (Diploma) in Physics, University of Karlsruhe (KIT). Trainer 2: Your expert course leader is Deputy Head of Energy Storage Department at Fraunhofer IEE. Prior to this, he was the director of the Grid Integration Department at SMA Solar Technology AG, one of the world's largest manufacturers of PV power converters. Before joining SMA, he was manager of the Front Office System Planning at Amprion GmbH (formerly RWE TSO), one of the four German transmission system operators. He holds a Degree of Electrical Engineering from the University of Kassel, Germany. In 2003, he finished his Ph.D. (Dr.-Ing.) on the topic of wind power forecasting at the Institute of Solar Energy Supply Technology (now known as Fraunhofer IEE) in Kassel. In 2004, he started his career at RWE TSO with a main focus on wind power integration and congestion management. He is Chairman of the IEC SC 8A 'Grid Integration of Large-capacity Renewable Energy (RE) Generation' and has published several papers about grid integration of renewable energy source and forecasting systems on books, magazines, international conferences and workshops. Trainer 3: Your expert course leader is Deputy Director of the Energy Process Technology division and Head of the Renewable Gases and Bio Energy Department at Fraunhofer IEE. His work is mainly focused on the integration of renewable gases and bioenergy systems into the energy supply structures. He has been working in this field since more than 20 years. He is a university lecturer in national and international master courses. He is member of the scientific advisory council of the European Biogas Association, member of the steering committee of the Association for Technology and Structures in Agriculture, member of the International Advisory Committee (ISAC) of the European Biomass Conference and member of the scientific committees of national bioenergy conferences. He studied mechanical engineering at the University of Darmstadt, Germany. He received his Doctoral degree on the topic of aerothermodynamics of gas turbine combustion chambers. He started his career in renewable energies in 2001, with the topic of biogas fired micro gas turbines. Trainer 4: Your expert course leader has an M. Sc. and she joined Fraunhofer IEE in 2018. In the Division of Energy Process Technology, she is currently working as a Research Associate on various projects related to techno-economic analysis of international PtX projects and advises KfW Development Bank on PtX projects in North Africa. Her focus is on the calculation of electricity, hydrogen and derivative production costs (LCOE, LCOH, LCOA, etc) based on various methods of dynamic investment costing. She also supervises the development of models that simulate different PtX plant configurations to analyze the influence of different parameters on the cost of the final product, and to find the configuration that gives the lowest production cost. She received her Bachelor's degree in Industrial Engineering at the HAWK in Göttingen and her Master's degree in renewable energy and energy efficiency at the University of Kassel. 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 about post training coaching support and fees applicable for this. Accreditions And Affliations

DevOps training course description This course is an introduction to DevOps. The course emphasizes communication, collaboration , integration, and automation to improve the workflow between developers and IT operations professionals. Improved workflows lead to more opportunities to design software and services in a more agile fashion. This course is a basis for discovering the most important DevOps concepts and to understand the principles and methods behind this. The course will leave you with the inspiration to be the advocate of change. What will you learn Explain DevOps principles. Describe the relationship between Agile , Lean and IT Service Management ( ITSM). Describe methods for automation and technology factors. Describe considerations when changing. Describe challenges, risks and critical success factors. DevOps training course details Who will benefit: IT development, IT operations and IT service management. Prerequisites: Introduction to data communications & networking. Duration 2 days DevOps training course contents Why DevOps? Introduction DevOps Goals DevOps Added value of DevOps Proven Results DevOps for businesses DevOps principles (The Three Ways) DevOps and other frameworks DevOps and Agile DevOps and Lean DevOps and IT Service Management DevOps culture Characteristics of a DevOps culture Organizational Considerations DevOps DevOps stakeholders DevOps roles DevOps teams DevOps organizational structures DevOps methods Continuous Integration Continuous delivery Continuous deployment Value stream mapping Kanban Theory of Constraints Improvement Kata Deming's quality circle ITSM processes DevOps and Automation Methods for DevOps automation Longevity and tools categories DevOps applications Transitioning to a DevOps culture. Implementation Challenges, risks and critical success factors Measuring DevOps successes