314 Mac courses in Epsom

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.

The objective of the ID Liner Permanent Eyeliner fundamental course is to teach you how to achieve this look for your clients. It is the perfect solution for clients who struggle to draw on their own eyeliner or who just want an expertly enhanced look 24/7

Cloud deployment training course description This course covers the important topics every cloud professional needs, including, configuration and deployment, security, maintenance, management, and troubleshooting. It covers all aspects of cloud computing infrastructure and administration, with a practical focus on real-world skills. It will help you to master the fundamental concepts, terminology, and characteristics of cloud computing. Deploy and implement cloud solutions, manage the infrastructure, and monitor performance. You will also be able to install, configure, and manage virtual machines. What will you learn Cloud services, models, and characteristics. Virtualization components, installation, and configuration. Infrastructure configurations and optimization. Resource management and specific allocations. IT security concepts, tools, and best practices. Recovery, availability and continuity in the cloud. Cloud deployment training course details Who will benefit: IT professionals looking to deploy and implement cloud solutions, manage the infrastructure, and monitor performance, Install, configure, and manage virtual machines. Prerequisites: Introduction to virtualization. Duration 5 days Cloud deployment training course contents Preparing to Deploy Cloud Solutions Deploying a Pilot Project Testing Pilot Project Deployments Designing a Secure and Compliant Cloud Infrastructure Designing and Implementing a Secure Cloud Environment Planning Identity and Access Management for Cloud Deployments Determining CPU and Memory Sizing for Cloud Deployments Determining Storage Requirements for Cloud Deployments Analysing Workload Characteristics to Ensure Successful Migration Maintaining Cloud Systems Implementing Backup, Restore, Disaster Recovery, and Business Continuity Measures Analysing Cloud Systems for Performance Analysing Cloud Systems for Anomalies and Growth Forecasting Troubleshooting Deployment, Capacity, Automation, and Orchestration Issues Troubleshooting Connectivity Issues Troubleshooting Security Issues

Level 2 NVQ Diploma in Construction Plant or Machinery Maintenance

Windows clustering training course description This course covers high availability and disaster recovery technologies such as live migration, storage migration and Hyper-V Replica, as well as providing indepth coverage of failover clustering including a detailed implementation of failover clustering of Hyper- V using SoFS. The course also covers System Center Virtual Machine Manager and implementing Network Load Balancing (NLB) and load balancing clusters. What will you learn Plan and implement a failover cluster. Describe managing server roles and clustering resources. Implement and manage virtual machines. Use System Center Virtual Machine Manager. Describe cloud-based storage and high availability solutions. Implement a Network Load Balancing (NLB) cluster. Windows clustering training course details Who will benefit: Technical staff working with Microsoft clusters. Prerequisites: Supporting Microsoft Windows server Duration 3 days Windows clustering training course contents High Availability in Windows Server Defining levels of availability, High Availability and disaster recovery solutions with Hyper-V Virtual Machines, High Availability with failover clustering in Windows Server. Hands on Configuring High Availability and Disaster Recovery. Implementing failover clustering Planning a failover cluster, creating a new failover cluster. Hands on Creating and Administering a Cluster. Server roles and clustering resources Configuring highly available applications and services on a failover cluster, managing and maintaining a failover cluster, troubleshooting a failover cluster, implementing site high availability with multisite failover clusters. Hands on Managing server roles and clustering resources. Failover clustering with Hyper-V Overview of integrating Hyper-V with failover clustering, implementing Hyper-V with failover clustering, managing and maintaining Hyper-V Virtual Machines on failover clusters. Hands on Implementing failover clustering by using Hyper-V Storage Infrastructure Management with Virtual Machine Manager Virtual Machine Manager, managing storage infrastructure with Virtual Machine Manager, provisioning failover clustering in Virtual Machine Manager. Hands on Managing storage infrastructure. Cloud-Based storage and High Availability Azure storage solutions and infrastructure, cloud integrated storage with StorSimple, disaster recovery with Azure Site Recovery. Hands on Managing cloud-based storage and high availability Network Load Balancing Clusters Overview of NLB, configuring an NLB cluster, planning NLB. Hands on Implementing a Network Load Balancing Cluster

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

MPEG training course description This course studies the MPEG standards for video and audio compression. A major focus is on MPEG-4 and MPEG-TS. Hands on includes decoding and analysing MPEG streams. What will you learn Recognise the main MPEG standards. Describe the techniques used in MPEG video and audio compression. Compare MPEG2m MPEG4 and MPEG-H. Describe the MPEG-TS. Analyse MPEG streams. MPEG training course details Who will benefit: Anyone working with MPEG. Prerequisites: None. Duration 2 days MPEG training course contents Introduction What is MPEG? MPEG and VCEG, MPEG 1, MPEG 2, MPEG-3, MPEG-4, MPEG-H, others, codecs and containers, licensing and patents, parts and layers (System, Video, Audio, others). MPEG2 DVD, DVB, characteristics, MPEG2 Part2, audio MPEG2 Part 7 (AAC). MPEG tools Wireshark, vlc, analysers, decoders, ffmpeg, wowzer. MPEG2 Video compression Sampling, bit rates, resolution. Inter and Intra frame coding, I, B, P frames, GOP, slices, blocks, macroblocks. Motion estimation. Hands on Analysing MPEG frames. MPEG4 Profiles and levels, Enhancements, Parts 1,2,3, Part 10 and AVC, Part 14 and mp4. Performance versus MPEG2. MPEG audio Coding, frequencies, bit rates. MPEG-TS PES, Transport Streams, TS elements, packets, PID, Programs, PSI, PAT, PMT, synchronisation, PCR, PTS. MPEG-H Part 2 HEVC, benefits, improvements. Video codecs What is a CODEC, pictures and audio, digitisation, sampling, quantisation, encoding, compressing.

Samba training course description Samba enables UNIX/Linux machines to act as Microsoft File and Print servers. This two day hands on training course progresses from the basics of installing samba and simple configurations through to authentication issues and troubleshooting. What will you learn Install and configure Samba. Administrate file and printer sharing. Secure Samba servers. Troubleshoot Samba Samba training course details Who will benefit: Technical staff working with Samba. Prerequisites: Intro to UNIX Systems Administration TCP/IP Foundation. Duration 2 days Samba training course contents What is Samba? File and print servers, Samba server roles, Windows networking, NetBIOS, SMB. Hands on Microsoft File and Print shares, analysing the network traffic. Installing Samba Source, binaries, where to find samba, building and compiling Samba. Hands on Download and install Samba. Controlling Samba Samba daemons, starting and stopping Samba, smbcontrol, Samba net command, smb.conf. Viewing Samba status, smbclient. Hands on Starting and stopping Samba, testing the server. Samba configuration Simple shares, smb.conf variables, configuration from a web browser, swat, enabling access to swat. Hands on Configuring samba servers and clients. File sharing Basic shares, [homes], locking options, UNIX file permissions, controlling user access, Windows ACLs, virtual samba servers, browsing. Hands on File sharing and browsing. Print sharing Sharing printers, UNIX printing, CUPS, printer drivers, [printers], PRINT$. Hands on Samba print server. Authentication Workgroups, domains, users and passwords, Samba domain security, Samba password backends: smbpasswd, tdbsam, nisplus, mysql, Active Directory. Hands on Securing samba shares. Troubleshooting Logging options, controlling logs, Samba utilities, network protocols, .SMB/CIFS. Performance tuning. Hands on Troubleshooting Samba

Data centre infrastructure course description This course provides a foundation in data centre infrastructure technologies. It begins with a tour of virtualisation and the impact of this on the network before moving on to the spine and leaf design, how it works and how to scale. Layer 2 technologies enabling this architecture are studied in terms of the impact on the data centre. The course then progresses onto how Layer 3 technologies such as BGP, EVPN and VXLAN are used in data centre networks. The course then studies interconnecting data centres finishing with a section on automation and orchestration of both underlay and overlay networks. What will you learn Explain the spine and leaf architecture Recognise the impact of virtualisation, containers and orchestration on the network Describe how the following technologies are used in data centres: Multi port aggregation Overlay networks MBGP, VRFs, EVPN VXLAN COOP Data centre infrastructure course details Who will benefit: Staff involved with Data centres. Prerequisites: Network fundamentals for engineers Duration 2 days Data centre infrastructure course contents What is Ethernet? Data centres versus enterprise networks. Servers, Blades, Racks, Clusters, Storage, Virtual Machines, Hosts, guests, containers, orchestration. Virtual switches. Distributed switches. Live migrations (e.g. vMotion). IP addressing and VM traffic. Data centre network architecture Spine leaf design. North south traffic, East West traffic, Scaling: Ports, bandwidth. N+1 redundancy, ratio East West optimisation, oversubscription. 2 tier versus 3 tier Leaf/Spine. Pods. Underlay, Overlay L2 technologies STP vs link aggregation vs multi link aggregation. LACP, LLDP, CDP. Scalability. VLANs and VLAN pruning. L2 design recommendations. Disabling STP on edge ports. L3 technologies Underlay, Overlay, VXLAN, VTEP, VXLAN overlay forwarding, EVPN, IS-IS, COOP, MP BGP, VRFs, EBGP, IBGP, AS numbers, route reflectors. Anycast gateways. MTU considerations-for data and control planes. BUM traffic. Data centre interconnects Pods, fabrics, multi pods, multi fabric, multi site. VXLAN with BGP/EVPN Data center interconnect. Cloud integration, Inter Site Networks. Automation Automation and orchestration, Zero touch provisioning, Devops, Netops, telemetry automated configuration for underlay and overlay, SDN.

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