517 Opera courses in Addlestone

Total STP training course description The Spanning Tree Protocol (STP) dates from 1985. This course explores in depth how the protocol works and the implications this has on network performance. We also study STP variants including 802.1w (RSTP) and 802.1s (MSTP). What will you learn Explain how STP works. Explain how RSTP works. Explain how MSTP works. Troubleshoot STP and variants. Total STP training course details Who will benefit: Technical network staff. Prerequisites: Definitive Ethernet switching for engineers Duration 1 day Total STP training course contents STP What is 802.1D, what is STP, resilience, broadcast storms, forwarding and blocking, single path. Hands on Impact of broadcast storms, enabling disabling STP. Operation STP frames, BPDUs, root bridge election, blocked ports, root ports, designated ports. STP path costs. Hands on Analysing STP, troubleshooting implications. Topology changes Hello timer, Forward delay timer, max age timer, Topology Change Notification (TCN) BPDU. Hands on STP convergence. STP enhancements and tuning Bridge ID, Bridge priority, port priority, 30 second delay, Edge ports, PortFast, root guard, loop guard, BPDU guard. Hands on Root bridge positioning, improving STP convergence. RSTP 802.1w, Improvements, convergence times. RSTP bridge port roles, RSTP switch port states. Edge ports, link ports. Hands on RSTP configuration and convergence. VLANs and STP Access/untagged ports, trunk/tagged ports, PVST, PVST+, RPVST, MISTP, MSTP and 802.1s. MSTP BPDUs. Instances, Load balancing, impact on CPU. Hands on MSTP load balancing. Interoperability Regions, Virtual bridges, domains. Hands on STP, RSTP and MSTP interoperation.

Securing Kubernetes training course description This course introduces concepts, procedures, and best practices to harden Kubernetes based systems and container-based applications against security threats. It deals with the main areas of cloud-native security: Kubernetes cluster setup, Kubernetes cluster hardening, hardening the underlying operating system and networks, minimizing microservices vulnerabilities, obtaining supply chain security as well as monitoring, logging, and runtime security. What will you learn Harden Kubernetes systems and clusters. Harden containers. Configure and use Kubernetes audit logs. Securing Kubernetes training course details Who will benefit: Technical staff working with Kubernetes Prerequisites: Kubernetes_for_engineers_course.htm Definitive Docker for engineers Duration 2 days Securing Kubernetes training course contents This course does not only deal with the daily security administration of Kubernetes-based systems but also prepares delegates for the official Certified Kubernetes Security Specialist (CKS) exams of the Cloud Native Computing Foundation (CNCF). Structure: 50% theory 50% hands on lab exercise Module 1: User and authorization management Users and service accounts in Kubernetes Authenticating users Managing authorizations with RBAC Module 2: Supply chain security Vulnerabilit checking for images Image validation in Kubernetes Reducing image footprint Secure image registries Module 3: Validating cluster setup and penetration testing Use CIS benchmark to review the security configuration of Kubernetes components. Modify the cluster components' configuration to match the CIS Benchmark. Penetration testing Kubernetes for known vulnerabilities. Module 4: System hardening Use kernel hardening tools Setup appropriate OS level security domains Container runtime sandboxes Limit network access Module 5: Monitoring and logging Configure Kubernetes audit logs Configure Audit Policies Monitor applications behaviour with Falco

IP addressing and subnetting course description A course focusing purely on IP addressing and subnetting. The course assumes that delegates already have some knowledge of IP addressing. In particular delegates will be able to calculate subnet numbers in seconds without using binary. What will you learn Download and install Wireshark. Calculate subnet numbers in seconds Design IP addressing schemes. Troubleshoot IP address problems. Calculate CIDR prefixes in seconds IP addressing and subnetting course details Who will benefit: Anyone working with TCP/IP. Prerequisites: TCP/IP Foundation for engineers Duration 2 days IP addressing and subnetting course contents IP addressing review What is an IP address? What is a subnet? Classless IP addressing. The rules of IP addressing. Ways IP addresses are used: On hosts, in packets, in routing tables. Hands on Byte boundary subnetting. Configuring IP addresses Interfaces, Static vs. dynamic configuration. DHCP: Scopes, leases, relays, using multiple DHCP servers. Multihoming. Subnetting Default subnet masks, subnet notations. How to subnet without binary. VLSMs. Hands on Bit boundary subnetting. Address ranges and routing Routing tables, IP address spoofing, host specific routing, subnets in routing tables, supernets in routing tables. CIDR. Impact of choice of routing protocol. Hands on IP addressing plans. Allocations and assignments IAB, IANA, RIRs, RIPE, LIRs and ISPs. PI vs. PA addressing. Hands on Querying the RIPE database. Private addressing and NAT NAT, NAPT, NAT terms, private addresses, NAT operation, NAT architecture, NAT and security, why use NAT? NAT-ALG, Types of NAT, RSIP. Special use addresses Unicasts, broadcasts, multicasts, anycasts. Directed broadcasts. Allowing broadcasts through routers.

Network virtualization training course description This course covers network virtualization. It has been designed to enable network engineers to recognise and handle the requirements of networking Virtual Machines. Both internal and external network virtualization is covered along with the technologies used to map overlay networks on to the physical infrastructure. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer implementations. What will you learn Evaluate network virtualization implementations and technologies. Connect Virtual Machines with virtual switches. Explain how overlay networks operate. Describe the technologies in overlay networks. Network virtualization training course details Who will benefit: Engineers networking virtual machines. Prerequisites: Introduction to virtualization. Duration 2 days Network virtualization training course contents Virtualization review Hypervisors, VMs, containers, migration issues, Data Centre network design. TOR and spine switches. VM IP addressing and MAC addresses. Hands on VM network configuration Network virtualization What is network virtualization, internal virtual networks, external virtual networks. Wireless network virtualization: spectrum, infrastructure, air interface. Implementations: Open vSwitch, NSX, Cisco, others. Hands on VM communication over the network. Single host network virtualization NICs, vNICs, resource allocation, vSwitches, tables, packet walks. vRouters. Hands on vSwitch configuration, MAC and ARP tables. Container networks Single host, network modes: Bridge, host, container, none. Hands on Docker networking. Multi host network virtualization Access control, path isolation, controllers, overlay networks. L2 extensions. NSX manager. OpenStack neutron. Packet walks. Distributed logical firewalls. Load balancing. Hands on Creating, configuring and using a distributed vSwitch. Mapping virtual to physical networks VXLAN, VTEP, VXLAN encapsulation, controllers, multicasts and VXLAN. VRF lite, GRE, MPLS VPN, 802.1x. Hands on VXLAN configuration. Orchestration vCenter, vagrant, OpenStack, Kubernetes, scheduling, service discovery, load balancing, plugins, CNI, Kubernetes architecture. Hands on Kubernetes networking. Summary Performance, NFV, automation. Monitoring in virtual networks.

Definitive Puppet training course description Puppet is a framework and toolset for configuration management. This course covers Puppet to enable delegates to manage configurations. Hands on sessions follow all the major sections. What will you learn Deploy Puppet. Manage configurations with Puppet. Build hosts with Puppet. Produce reports with Puppet. Definitive Puppet training course details Who will benefit: Anyone working with Puppet. Prerequisites: Linux fundamentals. Duration 2 days Definitive Puppet training course contents Getting started with Puppet What is Puppet, Selecting the right version of Puppet, Installing Puppet, Configuring Puppet. Developing and deploying Puppet The puppet apply command and modes of operation, Foreground Puppet master, Developing Puppet with Vagrant, Environments, Making changes to the development environment, Testing the new environments with the Puppet agent, Environment branching and merging, Dynamic Puppet environments with Git branches, Summary, Resources. Scaling Puppet Identifying the challenges, Running the Puppet master with Apache and Passenger, Testing the Puppet master in Apache, Load balancing multiple Puppet masters, Scaling further, Load balancing alternatives. Measuring performance, Splay time, Summary, Going further, Resources. Externalizing Puppet configuration External node classification, Storing node configuration in LDAP, Summary, Resources. Exporting and storing configuration Virtual resources, Getting started with exported and stored configurations, Using exported resources, Expiring state resources, Summary, Resources. Puppet consoles The foreman, Puppet enterprise console, Puppetboard, Summary, Resources. Tools and integration Puppet forge and the module tool, Searching and installing a module from the forge, Generating a module, Managing module dependencies, Testing the modules, Developing Puppet modules with Geppetto, Summary, Resources. Reporting with Puppet Getting started, Configuring reporting, Report processors, Custom reporting, Other Puppet reporters, Summary, Resources. Extending Facter and Puppet Writing and distributing custom facts, Developing custom types, providers and functions, Summary, Resources, Complex data structures, Additional backends, Hiera functions in depth, Module data bindings, Hiera examples. Jiera-2, Summary, Resources. Mcollective Installing and configuring Mcollective, testing, Mcollective plugins, accessing hosts with Metadata. Hiera Lists, initial Hiera configuration, Hiera command line utility, complex data structures, additional backends, Hiera functions in depth, module data bindings. Hiera-2.

Signalling training course description An intensive course that defines and explores the signalling methods that are to be found in today's telecommunications services. What will you learn Describe the Functionality and Features of Signalling. Describe the Functionality of Analogue & Digital Subscriber Signalling. Describe the various types of signalling used on different network types. Describe the Functionality of Private Network Signalling. Describe the Functionality of Public Network Signalling. Signalling training course details Who will benefit: Personnel involved with systems design, implementation and support. Prerequisites: Telecommunications Introduction Duration 2 days Signalling training course contents Introduction What is Signalling?, Standards, ITU-T Recommendations, Signalling Categories - Supervisory Addressing, E.164, Call Information, Network Management, Network Components, Inband/Outband Switch Signalling, Analogue Vs Digital Signalling. Analogue Subscriber Signalling Analogue Local Loops/Switches/Trunks, Digital Switches/Local Loops, Telephone Handset, Accessing the Local Exchange, Pulse/Tone Dialling. Digital Subscriber Signalling Integrated Digital Access, DASS2 & DPNSS, DASS2 - Call, IMUX, Euro ISDN, Q.931 Call Control, Message Identification, Message Types, Call Establishment Messages, Call Clearing. Network Types Service Types, Circuit Switched, Packet Switched, Signalling Terminology, In-Channel Signalling, G.704, Performance and Quality, Digital Signalling, CAS, CAS Applications, Foreign Exchange, CCS, Break-In/Out Private Network Signalling Types Networking PABXs, Inter PABX Analogue Signalling Methods, E & M, Tone-On-Idle, Inter PABX Digital Signalling Methods, DPNSS, DPNSS Deployment, PABX Support for DPNSS, DPNSS Call, Q.Sig, Q.Sig support/functionality/protocol, Message Overview, Call Establishment. Public Network Signalling SS7, SS7 Operations, SS7 Topology, SSP, STP, SCP, Database Types - CMSDB NP LIDB HLR VLR, Signalling Modes, Link Types, Further Redundancy, Linksets, SS7 addressing, Point Codes, Sub-System, Global Title Addressing and Translation, ANSI PCs, ITU-T PCs, SS7 Protocol Stack, MTP Level 1, MTP Level 2, Flow Control, FISU, LSSU, MSU, MSU SIF, MTP Level 3, SCCP, TCAP, TUP, Facility Format, Main Facilities, Flow Control Negotiation, Closed User Groups, Reverse Charging, Fast Select Facility, Throughput Class Negotiation, Call Barring, On-Line Facility Registration. BTUP, ISDN ISUP, Supplementary Services, ISUP Call - IAM, Progress/Answer/Suspend/ Resume/Release Messages, Intelligent Network (IN) Introduction, IN Evolution, IN Conceptual Model, IN Target Services & Service Features, Service Independent Building Blocks

Definitive Salt training course description Salt is a remote execution framework and configuration management system. This course covers Salt from the basics. After a quick first taste the course moves onto execution modules, salt states, minion and master data, jinja, Salt extensions and then topology and configuration options. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer equipment. What will you learn Install and use Salt. Describe the architecture of Salt. Manage configurations with Salt. Extend Salt. Definitive Salt training course details Who will benefit: Anyone working with Salt. Prerequisites: Linux fundamentals. Duration 2 days Definitive Salt training course contents Introduction What is Salt? High- level architecture, Some quick examples, system management, configuration management, A brief history, Topology options, Extending Salt. Quick start: First taste of Salt Single-master setup, from packages, bootstrap scripts, Starting up, Basic commands, salt: the main workhorse, salt-key: key management, salt-call: execution on the minion, salt-run: co-ordination of jobs on the master, summary of commands, Key management, viewing keys, accepting keys, rejecting keys, key files, Minion targeting, minion ID, list (-L), glob, regular expressions (-E), grains (-G), compound (-C), targeting summary, Additional remote execution details, Conclusion. Execution modules: The functional foundation sys: information and documentation about modules, sys.doc basic documentation, sys.list_modules, sys.list_functions: simple listings, cmd: execute via shell, cmd.run: run any command, pkg: manage packages, virtual modules, pkg.lists_pkgs: list all installed packages, pkg.available version: see what version will be installed, pkg.install: install packages, user: manage users, user.add: add users, user.list_users, user info: get user info, saltutil: access various Salt utilities, Summary. Configuration management: Salt states Salt files overview, SLS example: adding a user, working with the multi-layered state system, Highstate and the top file, the top file, State ordering, require: depend on another state, watch: run based on other changes, odds and ends, Summary. Minion data / master data Grains are minion data, performing basic grain operations, setting grains, targeting with grains in the top file, Pillars are data from the master, querying pillar data, querying other sources with external pillars, Renderers give data options. Extending Salt: part I Introduction to Jinja, Jinja basics, Templating with Jinja, filtering by grains, Custom execution module, Custom state modules, Custom grains, External pillars, Summary. More on the matter Runners, manage minions, manage jobs, The orchestrate runner, The event system, The reactor system, Summary. Extending Salt: part II Python client API, reading configuration data on a master and minion, using the master client (localclient) API, Using the caller client API, Custom runners, writing a custom runner, using the runnerclient API, Summary. Topology and configuration options Master configuration, directories and files, logging, access control, files server options, Topology variations, masterless minions, peer systems, syndication masters, multiple masters. Brief introduction to salt-cloud Overview, Setup AWS and salt-cloud, installing salt-cloud, cloud providers, cloud profiles, cloud maps, Introspection via salt cloud, Creating infrastructure, More information. Using vagrant to run Salt examples YAML.

About this training Decarbonization of the Upstream Oil & Gas sector has previously been based on inter-fuel competition. Market actions were seen as the most effective method for reducing the level of emissions. However, the pace of decarbonization is now being led by government policy acting in concert with a coalition of stakeholders such as investors and consumers. The primary focus of this pathway is on the management of carbon emissions to both mitigate and adapt to climate change. Some energy analysts have forecast that global production of oil and natural gas will have to decline annually by 4 to 6 percent in order to meet the global target of Net Zero Emissions by 2050. Oil and gas producers face a difficult challenge in deciding upon the strategy and measures that will best achieve targets set for them while maintaining supply, attracting investments and accessing markets. This 2-day training course will provide participants with an understanding of the strategies and measures for decarbonizing the Upstream Oil and Gas sector within the framework of measures implemented by individual governments through their respective commitments to reduce emissions to achieve their National Determined Contribution under the Paris Agreement. This course offers a unique opportunity to understand the rapidly increasing issues confronting the industry as well as the options for the management of carbon emissions to comply with corporate as well as national policies and the implementation of measures for controlling, reporting and verification. Training Objectives Upon completion of this course, participants will be better equipped to participate in the implementation of measures for the management of carbon emissions in the following areas: Implementation of measures for reducing carbon emissions Establishing systems for monitoring and reporting carbon emissions Evaluating the commerciality of discoveries Reviewing and strategizing future field development plans Meeting Environmental Obligations Target Audience This course has been specifically designed for professionals involved in the international oil and gas industry, whether employed a field operator, national oil company, or government. It offers a unique opportunity to rapidly increase your understanding of the issues confronting the industry as well as the options for the management of carbon emissions to comply with corporate as well as national policies and the implementation of measures for controlling, reporting and verification. Staff with the following roles will find this course particularly useful: Corporate Planners Project Engineers Financial Analysts Environmental Specialists Legal Advisors Regulatory & Compliance Officers Course Level Basic or Foundation Trainer Your expert course leader is an international legal expert in petroleum law who has been listed in the Guide to the World's Leading Energy and Natural Resources Lawyers. In his thirty years of practice, he has been the lead negotiator and acquisitions advisor for oil and gas companies in the US and the Asia-Pacific. These transactions have included both upstream (licences and leases) and downstream (refineries and pipelines) assets. He has been appointed as Distinguished Visiting Professor in Oil and Gas at the University of Wyoming and Honorary Professor at the Centre for Energy, Petroleum & Mineral Law & Policy (CEPMLP) at Dundee University. 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 Business Impact: The main aim is to provide insight and understanding of data analytics and machine learning principles through applications. Field data is used to explain data-analysis workflows. Using easy to follow solution scripts, the participants will assess and extract value from the data sets. Hands-on solution approach will give them confidence to try out applicable techniques on data from their field assets. Data analysis means cleaning, inspecting, transforming, and modeling data with the goal of discovering new, useful information and supporting decision-making. In this hands-on 2-day training course, the participants learn some data analysis and data science techniques and workflows applied to petroleum production (specifically artificial lift) while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles. Unique Features: Eight business use cases covering their business impact, code walkthroughs for most all and solution approach. Industry data sets for participants to practice on and take home. No software or complicated Python frameworks required. Training Objectives After the completion of this training course, participants will be able to: Understand digital oil field transformation and its impact on business Examine machine learning methods Review workflows and code implementations After completing the course, participants will have a set of tools and some pathways to model and analyze their data in the cloud, find trends, and develop data-driven models Target Audience This training course is suitable and will greatly benefit the following specific groups: Artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets Course Level Intermediate Advanced Training Methods The course discusses several business use-cases that are amenable to data-driven workflows. For each use case, the instructor will show the solution using a data analysis technique with Python code deployed in the Google cloud. Trainees will solve a problem and tweak their solution. Course Duration: 2 days in total (14 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 Knowledge of Python is not a must but preferred to get the full benefit. The training will use the Google Collaboratory environment available in Google-Cloud for hands-on exercises Trainees will need to bring a computer with a Google Chrome browser and a Google email account (available for free) 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 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