577 Mac courses in Brownhills delivered Live Online

Network management technologies course description A comprehensive tour of the available network management technologies available for todays networks. The course starts with basic tools such as syslog along with Python network automation. SNMP is then covered with the *flow technologies and streaming telemetry. Configuration management with ansible, Python, NETCONF and RESTCONF is then studied. The final part of the course looks at SDN. Hands on sessions are used throughout to reinforce the theory rather than teach specific manufacturer equipment. Note that sections are available as individual courses. What will you learn Evaluate network management technologies. Evaluate network management technologies. Recognise the weaknesses of SNMP versus NETCONF and streaming telemetry. Explain the role of NETCONF and RESTCONF. Compare & contrast *flow and streaming telemetry. Explain the role of SDN in network management. Automate network configuration with ansible and Python. Network management technologies course details Who will benefit: Those wishing to manage networks. (Previous Python experience is NOT needed) Prerequisites: Intro to data comms Duration 5 days Network management technologies course content Basic network management Network management What is network management? Benefits, issues. FCAPS model. Fault management, Configuration management, accounting, performance, security. What to manage, what not to manage. Managing network devices, managing servers. Monitoring networks Traditional network tools Ping..., SSH, syslog, TFTP for configurations. nmap. Wireshark. CLI. Web based management. Splunk. Nessus, snort, Kali. Hands on syslog, network inventories. Network automation using the CLI Programming and automating networks, netOps. Python, Git. Python network modules, SSH, paramiko, netmiko. EVE-NG. Hands onPython network modules. Structured versus unstructured data Problems with automation and unstructured data. XML, JSON, YAML. The role of YANG. Hands on Parsing data. SNMP SNMP architecture, SNMP MIBs, SMI, the SNMP protocol, polling security. Configuring SNMP. SNMPv1, v2, v3, SNMP security. Which version should you use? MIBs and MIB structure. mib-2, extra parts of mib-2, Private enterprise MIBs. Summary: What SNMP is good/bad at. Hands on Configuring agents and a NMS. MIB browsing. Server management Microsoft, Linux, application polling. WMI vs SNMP. Hands on: Application polling. Performance management *flow Polling, push vs pull, netflow, sflow, IPFIX, *flow. Flows. Where to monitor traffic. Comparing *flow with SNMP. Architecture: Generators and collectors. When flows are exported. NetFlow reporting products. SolarWinds. Hands on Netflow configuration. Collectors. Streaming telemetry Model driven telemetry, periodic/on change. Structured data. Telemetry protocol stack. gRPC and gNMI. Protobuf. gNMI operations. Telemetry architecture. Telegraf, databases, Grafana. Hands on Telemetry example. Configuration management Configuration management tools Chef, puppet, ansible, saltstack. Ansible architecture, controlling machines, nodes, agentless, SSH, modules. Inventories, playbooks, modules, network modules, jinja2 templates. Hands on Network configuration with ansible. NETCONF What is NETCONF? Protocol stack, Data stores, traffic flows, validating configurations, rollback. YANG data models and how YANG is used by NETCONF. XML. Explorers and other tools. Hands on anx, Python and NETCONF. RESTCONF The REST API, HTTP, What is RESTCONF? Tools including Postman. Comparison with NETCONF. Hands on Configuration with RESTCONF. Python network automation: configuration SSH issues. Using structured data. Jinja2. ncclient, requests, NAPALM, Nornir. Automated testing. Hands on Python network device configuration with nornir. Software Defined Networks and orchestration Classic SDN What is SDN? benefits. SDN architecture. SDN applications, SDN switches, SDN controllers, Network Operating Systems. Control plane, data plane. Northbound interfaces. SDN components. Southbound interfaces. OpenFlow. ONF, OpenFlow ports, Flow tables. Network virtualization Virtual networks, virtual switches, NfV. Service chaining. NfV and SDN. SDN implementations Classic SDN, Hybrid SDN, SDN via APIs, SDN via overlays. Data centre SDN, VXLAN, Service Provider SDN, SD WAN, Enterprise SDN, WiFi. SDN and open source OpenDaylight, OpenVSwitch, Open Networking Forum, Open Network Operating System. Hands onOpenStack. SD-WAN What is SD-WAN? Architecture: Edge, gateway, orchestrator, controller. Overlay and underlay. Use of MPLS, 4G/5G. Benefits and features. Secure Access Service Edge (SASE).

OpenStack for NFV and SDN course description OpenStack is predominately a cloud management technology. This course looks at how OpenStack can be used in a NFV and SDN environment. What will you learn Describe the architecture of NFV. Explain the relationship between NFV and SDN. Implement NFV VIM using OpenStack. Explain how OpenStack as VNFM and orchestrator works. OpenStack for NFV and SDN course details Who will benefit: Anyone wishing to implement NFV using OpenStack. Prerequisites: Introduction to Virtualization Duration 3 day OpenStack for NFV and SDN course content What is NFV? What is NFV? What are network Functions? NFV benefits, NFV market drivers. ETSI NFV framework. ETSI documents, Architecture overview, compute domain, hypervisor domain, infrastructure network domain. What is OpenStack? Virtual machines, clouds, management. OpenStack architecture, OpenStack modules. Why OpenStack for NFV? Hands on OpenStack installation. OpenStack Virtualization and NFV Server, storage and network virtualization and NFV. Where OpenStack fits in the ETSI framework. Virtual machines, containers and docker. Data centres, clouds, SaaS, IaaS, PaaS. Hands on OpenStack Iaas, OpenStack Nova. The virtualization layer VM centric model, containers versus hypervisors, FD.io. Hands on OpenStack as the VIM. OpenStack Neutron VXLAN, Networks, subnets, ports. Security groups. Routers. Service and component hierarchy. Hands on Implementing a virtual network with OpenStack Neutron. Virtualization of Network Functions Network virtualization versus Network Function virtualization. NFV MANO Management and Orchestration. Where OpenStack fits. MANO descriptors, Open orchestration. OpenStack Tacker, Open MANO, OpenBaton, other orchestrators. OpenStack Tacker Installation, getting started, configuration. SFC and OpenStack. Hands on Deploying a VNF. OPNFV What is OPNFV, Where OpenStack fits into OPNFV. SDN What is SDN? Control and data planes. SDN controllers. Classic SDN versus real SDN. Hybrid SDN, network automation, SDN with overlays. Northbound, southbound, SDN protocols, OpenFlow, OpenDaylight, ONOS, SDN with NFV. SDN and OpenStack. Summary Deploying NFV, performance, testing. Futures

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

Duration 5 Days 30 CPD hours This course is intended for Ideal candidates include network professionals who are looking to build their foundational knowledge of the ClearPass product portfolio. Overview After you successfully complete this course, expect to be able to: Ability to setup ClearPass as a AAA server Demonstrate Configuration Guest, OnGurad, Onboard and Profiling features Integrate with External AD Server Understand Monitoring and Reporting Demonstrate Scaling and deployment of best practices Configure AAA services for both wired and wireless networks Demonstrate the configuration of Aruba Downloadable User Roles. Demonstrate the configuration of Dynamic Segmentation with Aruba switches. This course prepares participants with foundational skills in Network Access Control using the ClearPass product portfolio. This 5-day classroom session includes both instructional modules and labs to teach participants about the major features of the ClearPass portfolio. Participants will learn how to setup ClearPass as an AAA server, and configure the Policy Manager, Guest, OnGuard and Onboard feature sets. In addition, this course covers integration with external Active Directory servers, Monitoring and Reporting, as well as deployment best practices. The student will gain insight into configuring authentication with ClearPass on both wired and wireless networks. Intro to ClearPass BYOD High Level Overview Posture and Profiling Guest and Onboard ClearPass for AAA Policy Service Rules Authentication Authorization and Roles Enforcement Policy and Profiles Authentication and Security Concepts Authentication Types Servers Radius COA Active Directory Certificates Intro to NAD NAD Devices Adding NAD to ClearPass Network Device Groups Network Device Attributes Aruba Controller as NAD Aruba Switch Aruba Instant Monitoring and Troubleshooting Monitoring Troubleshooting Logging Policy Simulation ClearPass Insight Insight Dashboard Insight Reports Insight Alerts Insight Search Insight Administration Insight Replication Active Directory Adding AD as Auth Source Joining AD domain Using AD services External Authentication Multiple AD domains LDAP Static Host Lists SQL Database External Radius Server Guest Guest Account creation Web Login pages Guest Service configuration Self-registration pages Configuring NADS for Guest Guest Manager Deep Dive Web Login Deep Dive Sponsor Approval MAC Caching Onboard Intro to Onboard Basic Onboard Setup Onboard Deepdive Single SSID Onboarding Dual SSID Onboarding Profiling Intro to Profiling Endpoint Analysis Deep Dive Posture Intro to Posture Posture Deployment Options OnGuard Agent Health Collection OnGuard workflow 802.1x with Posture using Persistent/dissolvable agent OnGuard web Login Monitoring and Updates Operation and Admin Users Operations Admin Users Clustering and Redundancy Clustering Redundancy LAB Licensing ClearPass Licensing Base License Applications ClearPass Exchange Intro Examples General HTTP Palo Alto Firewall Configuration Case Study Objectives Discussion Advanced Labs Overview Wired Port Authentication 802.1X for access layer switch ports Profiling on Wired Network Configuration of Dynamic Segmentation Aruba Downloadable User Roles Downloadable User Role Enforcement in ClearPass Aruba Controller/Gateway configuration Aruba Switch configuration Troubleshooting

Ansible for engineers training course description An introduction to automation using ansible. Ansible is a general purpose IT automation platform that can be use for a number of purposes. The course covers configuration management, cloud provisioning and application deployment with ansible. Hands on sessions follow all major sections. What will you learn Install ansible. Automate tasks with ansible. Write ansible playbooks. Ansible for engineers training course details Who will benefit: Administrators and developers automating tasks. Prerequisites: Linux administration skills Duration 3 days Ansible for engineers training course contents What is ansible? The language, the engine, the framework. Uses of ansible, orchestration. Hands on Installing ansible. Ansible architecture ible architecture Controlling machines, nodes, Agentless, SSH, modules, JSON protocol. Configuration management, inventories, playbooks, modules, roles. Hands on Getting started, running ad hoc commands. Ansible and Vagrant Prototyping and testing. Hands on Using ansible with Vagrant. Ad hoc commands Parallelism, shell commands, managing files and directories, file transfer, package management, manage user and groups, deploying applications, service management, background jobs, checking log files, managing cron jobs. Hands on Using ansible with Vagrant. Playbooks ansible-playbook, users, sudo, YAML, plays, tasks, handlers, modules. Hands on Running playbooks. More playbooks Handlers, variables, environmental variables, playbook variables, inventory variables, variable scope and precedence, accessing variables, facts, ansible vault. Conditionals, wait_for. Hands on Using variables and conditions in playbooks. Roles and includes Dynamic includes, Handler includes, playbook includes. Roles, role parts: handlers, files, templates, cross platform roles, ansible galaxy. Hands on includes example, building roles. Inventories /etc/ansible/hosts, inventory variables, static inventories, dynamic inventories. Hands on Inventories and variables. Miscellanea Individual server cookbooks, Main playbook for configuring all servers. Hands onPlaybooks.

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

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

Duration 5 Days 30 CPD hours This course is intended for This course is intended for IT professionals who have some experience working with Windows Server, and who are looking for a single five-day course that covers storage and compute technologies in Windows Server. This course will help them update their knowledge and skills related to storage and compute for Windows Server. Overview Prepare and install Windows Server and plan a server upgrade and migration strategy. Describe the various storage options, including partition table formats, basic and dynamic disks, file systems, virtual hard disks, and drive hardware, and explain how to manage disks and volumes. Describe enterprise storage solutions, and select the appropriate solution for a given situation. Implement and manage Storage Spaces and Data Deduplication. Install and configure Microsoft Hyper-V, and configure virtual machines. Deploy, configure, and manage Windows and Hyper-V containers. Describe the high availability and disaster recovery technologies in Windows Server. Plan, create, and manage a failover cluster. Implement failover clustering for Hyper-V virtual machines. Configure a Network Load Balancing (NLB) cluster, and plan for an NLB implementation. Create and manage deployment images. Manage, monitor, and maintain virtual machine installations. This five-day course is designed primarily for IT professionals who have some experience with Windows Server. It is designed for professionals who will be responsible for managing storage and compute by using Windows Server, and who need to understand the scenarios, requirements, and storage and compute options that are available and applicable to Windows Server. Although this course and the associated labs are written for Windows Server 2022, the skills taught will also be backwards compatible for Server 2016 and Server 2019. The course and labs also focus on how to administer Windows Server using not only the traditional tools such as PowerShell and Server manager, but also Windows Admin Center. Prerequisites A basic understanding of networking fundamentals. An awareness and understanding of security best practices. An understanding of basic Active Directory concepts. Basic knowledge of server hardware. Experience supporting and configuring Windows client operating systems such as Windows 10 or Windows 11. 1 - Installing, upgrading, and migrating servers and workloads Introducing Windows Server Preparing and installing Server Core Preparing for upgrades and migrations Migrating server roles and workloads Windows Server activation models 2 - Configuring local storage Managing disks in Windows Server Managing volumes in Windows Server 3 - Implementing enterprise storage solutions Overview of DAS, NAS, and SANs Comparing Fibre Channel, iSCSI, and Fibre Channel over Ethernet Understanding iSNS, DCB, and MPIO Configuring sharing in Windows Server 4 - Implementing Storage Spaces and Data Deduplication Implementing Storage Spaces Managing Storage Spaces Implementing Data Deduplication 5 - Installing and configuring Hyper-V and virtual machines Overview of Hyper-V Installing Hyper-V Configuring storage on Hyper-V host servers Configuring networking on Hyper-V host servers Configuring Hyper-V virtual machines Managing virtual machines 6 - Deploying and managing containers Overview of containers in Windows Server Deploying Windows Server and Hyper-V containers Installing, configuring, and managing containers by using Docker 7 - High availability and disaster recovery Defining levels of availability Planning high availability and disaster recovery solutions with Hyper-V virtual machines Backing up and restoring by using Windows Server Backup High availability with failover clustering in Windows Server 8 - Implementing failover clustering Planning a failover cluster Creating and configuring a new failover cluster Maintaining a failover cluster Troubleshooting a failover cluster Implementing site high availability with stretch clustering 9 - Implementing failover clustering with Windows Server Hyper-V Overview of the integration of Hyper-V with failover clustering Implementing Hyper-V VMs on failover clusters Key features for VMs in a clustered environment 10 - Implementing Network Load Balancing Overview of NLB Configuring an NLB cluster Planning an NLB implementation 11 - Creating and managing deployment images Introduction to deployment images Creating and managing deployment images by using MDT Virtual machine environments for different workloads 12 - Managing, monitoring, and maintaining virtual machine installations WSUS overview and deployment options Update management process with WSUS Overview of Windows PowerShell DSC Overview of Windows Server monitoring tools Using Performance Monitor Monitoring event logs

Duration 5 Days 30 CPD hours This course is intended for This course is intended for IT Professionals who are already experienced in general Windows Server, Windows client, Azure, and Microsoft 365 administration, and who want to learn more about using Windows PowerShell for administration. No prior experience with any version of PowerShell or any scripting language is assumed. This course is also suitable for IT Professionals already experienced in server administration, including Microsoft Exchange Server, Microsoft SharePoint Server, and Microsoft SQL Server. This course provides students with the fundamental knowledge and skills to use PowerShell for administering and automating administration of Windows servers. This course provides students the skills to identify and build the command they require to perform a specific task. In addition, students learn how to build scripts to accomplish advanced tasks such as automating repetitive tasks and generating reports. This course provides prerequisite skills supporting a broad range of Microsoft products, including Windows Server, Windows Client, Microsoft Azure, and Microsoft 365. In keeping with that goal, this course will not focus on any one of those products, although Windows Server, which is the common platform for all of those products, will serve as the example for the techniques this course teaches. Prerequisites Before attending this course, students must have: -Experience with Windows networking technologies and implementation. - Experience with Windows Server administration, maintenance, and troubleshooting. 1 - Review Windows PowerShell Learn about Windows PowerShell Get familiar with Windows PowerShell applications Identify factors to install and use Windows PowerShell Configure the Windows PowerShell console Configure the Windows PowerShell Integrated Scripting Environment (ISE) Use Visual Studio Code with PowerShell 2 - Understand the command syntax in Windows PowerShell Discover the structure of PowerShell cmdlets Discover the parameters for using PowerShell cmdlets Review the tab completion feature in PowerShell Display the About files content in PowerShell 3 - Find commands and Get-Help in Windows PowerShell Define modules in PowerShell Find cmdlets in PowerShell Use command aliases in PowerShell Use Show-Command and Get-Help in PowerShell Interpret the help file contents and update the local help content in PowerShell 4 - Manage Active Directory Domain Services using PowerShell cmdlets Manage user accounts in PowerShell Manage groups and group memberships in PowerShell Manage computer accounts in PowerShell Manage organizational units and Active Directory objects in PowerShell 5 - Manage network service settings for Windows devices using PowerShell cmdlets Manage IP addresses in PowerShell Manage IP routing in PowerShell Manage DNS clients in PowerShell Manage Windows Firewall settings in PowerShell 6 - Manage Windows Server settings using PowerShell cmdlets Automate management tasks using the Group Policy management cmdlets Manage server roles and services using PowerShell cmdlets Manage Hyper-V Virtual Machines using PowerShell cmdlets Manage Internet Information Services using PowerShell cmdlets 7 - Manage settings for a local Windows machine using PowerShell cmdlets Manage Windows 10 using PowerShell Manage permissions with PowerShell 8 - Understand the Windows PowerShell pipeline Review Windows PowerShell pipeline and its output Discover object members in PowerShell Control the formatting of pipeline output 9 - Select, sort, and measure objects using the pipeline Sort and group objects by property in the pipeline Measure objects in the pipeline Select a set of objects in the pipeline Select object properties in the pipeline Create and format calculated properties in the pipeline 10 - Filter objects out of the pipeline Learn about the comparison operators in PowerShell Review basic filter syntax in the pipeline Review advanced filter syntax in the pipeline Optimize the filter performance in the pipeline 11 - Enumerate objects in the pipeline Learn about enumerations in the pipeline Review basic syntax to enumerate objects in the pipeline Review advanced syntax to enumerate objects in the pipeline 12 - Send and pass data as output from the pipeline Write pipeline data to a file Convert pipeline objects to other forms of data representation in PowerShell Control additional output options in PowerShell 13 - Pass pipeline objects Pipeline parameter binding Identify ByValue parameters Pass data by using ByValue Pass data by using ByPropertyName Identify ByPropertyName parameters Use manual parameters to override the pipeline Use parenthetical commands Expand property values 14 - Connect with data stores using PowerShell providers Define Windows PowerShell providers Review the built-in providers in PowerShell Access provider help in PowerShell 15 - Use PowerShell drives in PowerShell Explain PowerShell drives in PowerShell Use PowerShell drive cmdlets in PowerShell Manage the file system in PowerShell Manage the registry in PowerShell Work with certificates in PowerShell Work with other PowerShell drives in PowerShell 16 - Review CIM and WMI Review architecture of CIM and WMI Review repositories in CIM and WMI Locate online class documentation by using CIM and WMI cmdlets 17 - Query configuration information by using CIM and WMI List local repository namespaces and classes by using CIM and WMI Query instances by using commands and WMI Query Language Connect to remote computers by using CIM and WMI cmdlets Query repository classes from remote computers by using CIMSession objects 18 - Query and manipulate repository objects by using CIM and WMI methods Discover methods of repository objects by using CIM and WMI Locate class methods and documentation by using CIM and WMI Invoke methods of repository objects by using CIM and WMI 19 - Manage variables in Windows PowerShell scripts Define variables in Windows PowerShell scripts Create variable names in Windows PowerShell scripts Assign values and types to variables in Windows PowerShell scripts Identify the methods and properties of variables in Windows PowerShell scripts Use string variables and methods in Windows PowerShell scripts Use date variables and methods in Windows PowerShell scripts 20 - Work with arrays and hash tables in Windows PowerShell scripts Define an array in Windows PowerShell scripts Work with array lists in Windows PowerShell scripts Define hash tables in Windows PowerShell Scripts Work with hash tables in Windows PowerShell scripts 21 - Create and run scripts by using Windows PowerShell Review Windows PowerShell scripts Modify scripts in the PowerShell Gallery Create scripts using Windows PowerShell Review the PowerShellGet module in Windows PowerShell Run scripts and set the execution policy in Windows PowerShell Review Windows PowerShell and AppLocker Sign the scripts digitally in Windows PowerShell 22 - Work with scripting constructs in Windows PowerShell Review and use the ForEach loop in Windows PowerShell scripts Review and use the If construct in Windows PowerShell scripts Review and use the Switch construct in Windows PowerShell scripts Review the For construct in Windows PowerShell scripts Review other loop constructs in Windows PowerShell scripts Review Break and Continue in Windows PowerShell scripts 23 - Import data in different formats for use in scripts by using Windows PowerShell cmdlets Use the Get-Content command in Windows PowerShell scripts Use the Import-Csv cmdlet in Windows PowerShell scripts Use the Import-Clixml cmdlet in Windows PowerShell scripts Use the ConvertFrom-Json cmdlet in Windows PowerShell scripts 24 - Use methods to accept user inputs in Windows PowerShell scripts Identify values that might change in Windows PowerShell scripts Use the Read-Host cmdlet in Windows PowerShell scripts Use the Get-Credential cmdlet in Windows PowerShell scripts Use the Out-GridView cmdlet in Windows PowerShell scripts Pass parameters to a Windows PowerShell script 25 - Troubleshoot scripts and handle errors in Windows PowerShell Interpret error messages generated for Windows PowerShell commands Add output to Windows PowerShell scripts Use breakpoints in Windows PowerShell scripts Interpret error actions for Windows PowerShell commands 26 - Use functions and modules in Windows PowerShell scripts Review functions in Windows PowerShell scripts Use variable scope in Windows PowerShell scripts Create modules in Windows PowerShell scripts Use the dot sourcing feature in Windows PowerShell 27 - Manage single and multiple computers by using Windows PowerShell remoting Review the remoting feature of Windows PowerShell Compare remoting with remote connectivity Review the remoting security feature of Windows PowerShell Enable remoting by using Windows PowerShell Use one-to-one remoting by using Windows PowerShell Use one-to-many remoting by using Windows PowerShell Compare remoting output with local output 28 - Use advanced Windows PowerShell remoting techniques Review common remoting techniques of Windows PowerShell Send parameters to remote computers in Windows PowerShell Set access protection to variables, aliases, and functions by using the scope modifier Enable multi-hop remoting in Windows PowerShell 29 - Manage persistent connections to remote computers by using Windows PowerShell sessions Review persistent connections in Windows PowerShell Create and manage persistent PSSessions by using Windows PowerShell Disconnect PSSessions by using Windows PowerShell Review the feature of implicit remoting in Windows PowerShell 30 - Review Azure PowerShell module Review Azure PowerShell Review the benefits of the Azure PowerShell module Install the Azure PowerShell module Migrate Azure PowerShell from AzureRM to Azure Review Microsoft Azure Active Directory module for Windows PowerShell and Azure Active Directory PowerShell for Graph modules 31 - Review the features and tools for Azure Cloud Shell Review the characteristics of Azure Cloud Shell Review the features and tools of Azure Cloud Shell Configure and experiment with Azure Cloud Shell 32 - Manage Azure resources with Windows PowerShell Create a new Azure virtual machine by using Windows PowerShell commands Manage Azure virtual machines by using Windows PowerShell commands Manage Azure related storage by using Azure PowerShell Manage Azure subscriptions by using Azure PowerShell 33 - Manage users, groups, and licenses in Microsoft Entra ID by using Windows PowerShell Review benefits to manage Microsoft 365 services by using Windows PowerShell Connect to the Microsoft 365 tenant by using Windows PowerShell Manage users in Microsoft 365 by using Windows PowerShell Manage groups in Microsoft 365 by using Windows PowerShell Manage roles in Microsoft 365 by using Windows PowerShell Manage licenses in Microsoft 365 by using Windows PowerShell 34 - Manage Exchange Online by using Windows PowerShell Connect to Exchange Online by using Windows PowerShell Manage mailboxes in Exchange Online by using Windows PowerShell Manage resources in Exchange Online by using Windows PowerShell Manage admin roles in Exchange Online by using Windows PowerShell 35 - Manage SharePoint Online by using Windows PowerShell Install and connect to SharePoint Online Management Shell by using Windows PowerShell Manage SharePoint Online users and groups by using Windows PowerShell Manage SharePoint sites by using Windows PowerShell Manage SharePoint Online external user sharing by using Windows PowerShell 36 - Manage Microsoft Teams by using Windows PowerShell Review Microsoft Teams PowerShell module Install the Microsoft Teams PowerShell module Manage teams with Microsoft Teams PowerShell module 37 - Create and manage background jobs using Windows PowerShell Define the types of background jobs in Windows PowerShell Start remote jobs and CIM/WMI jobs in Windows PowerShell Monitor jobs in Windows PowerShell Retrieve results for running jobs in Windows PowerShell 38 - Create and manage scheduled jobs using Windows PowerShell Create and run Windows PowerShell scripts as scheduled tasks Define scheduled jobs in Windows PowerShell Create job option and job trigger objects in Windows PowerShell Create and register a scheduled job in Windows PowerShell Retrieve the results from a scheduled job in Windows PowerShell

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