PC fundamentals training course description A basic introductory course for those who have never worked with PCs before. The principle target audience is for those who will become PC support people. What will you learn Cable PCs. Perform preventive maintenance on PCs Run Windows and start applications. Use Microsoft Office applications. Customise Windows. PC fundamentals training course details Who will benefit: Anyone new to PCs. Prerequisites: None. Duration 3 days PC fundamentals training course contents PC hardware Overview of components inside a PC, cabling up a PC, preventive maintenance, cleaning mice, hardware screen controls, booting a PC. Windows overview Versions of Windows, Starting Windows, logging on, shutting down. Using Windows The desktop, the start menu and submenus, getting help, shutting down Windows, switching between applications, sizing and controlling windows, special keys on the keyboard. Accessing files and folders Folders and files, Windows explorer, IE, creating, viewing and manipulating folders, creating, viewing and manipulating files, permissions, bits and bytes, the recycle bin, undeleting and undoing, formatting floppy disks, using floppy disks DOS Accessing DOS, basic DOS commands, drives. Microsoft Office Word documents, Excel spreadsheets, emails, browsing the Internet, printing files, managing print queues. Printing Overview, printing, properties Customisation Customising the task bar, customising the start menu. The control panel, mouse and display properties, Desktop settings, setting the date and time. Networking overview Workgroups and domains, Accessing file and print resources
The course covers research design principles and all main quantitative evaluation methods: randomised experiments, instrumental variables, sharp and fuzzy regression discontinuity designs, regression methods, matching methods and longitudinal methods (before-after, difference-in-differences and synthetic controls).
The course covers research design principles and all main quantitative evaluation methods: randomised experiments, instrumental variables, sharp and fuzzy regression discontinuity designs, regression methods, matching methods and longitudinal methods (before-after, difference-in-differences and synthetic controls).
The course covers research design principles and all main quantitative evaluation methods: randomised experiments, instrumental variables, sharp and fuzzy regression discontinuity designs, regression methods, matching methods and longitudinal methods (before-after, difference-in-differences and synthetic controls).
The course covers research design principles and all main quantitative evaluation methods: randomised experiments, instrumental variables, sharp and fuzzy regression discontinuity designs, regression methods, matching methods and longitudinal methods (before-after, difference-in-differences and synthetic controls).
The course covers research design principles and all main quantitative evaluation methods: randomised experiments, instrumental variables, sharp and fuzzy regression discontinuity designs, regression methods, matching methods and longitudinal methods (before-after, difference-in-differences and synthetic controls).
The course covers research design principles and all main quantitative evaluation methods: randomised experiments, instrumental variables, sharp and fuzzy regression discontinuity designs, regression methods, matching methods and longitudinal methods (before-after, difference-in-differences and synthetic controls).
The course covers research design principles and all main quantitative evaluation methods: randomised experiments, instrumental variables, sharp and fuzzy regression discontinuity designs, regression methods, matching methods and longitudinal methods (before-after, difference-in-differences and synthetic controls).
The course covers research design principles and all main quantitative evaluation methods: randomised experiments, instrumental variables, sharp and fuzzy regression discontinuity designs, regression methods, matching methods and longitudinal methods (before-after, difference-in-differences and synthetic controls).
NFV training course description Network Functions Virtualization (NFV) brings many benefits, this training course cuts through the hype and looks at the technology, architecture and products available for NFV. What will you learn Explain how NFV works. Describe the architecture of NFV. Explain the relationship between NFV and SDN. Recognise the impact NFV will have on existing networks. NFV training course details Who will benefit: Anyone wishing to know more about NFV. Prerequisites: Introduction to Virtualization. Duration 2 days NFV training course content Introduction What is NfV? What are network Functions? NfV benefits, NfV market drivers. ETSI NfV framework. Virtualization review Server, storage and network virtualization and NfV. Virtual machines, containers and docker. Data centres, clouds, SaaS, IaaS, PaaS. Virtualization of Network Functions Network virtualization versus Network Function virtualization. ETSI NfV architecture ETSI documents, Architecture overview, compute domain, hypervisor domain, infrastructure network domain. IETF and NfV Creating services, Service Functions, Service Function Chaining. SPRING and source packet routing. YANG and NetConf. RESTCONF. VLANs, VPNs, VXLAN. MANO Management and Orchestration. OpenStack, OpenDaylight PaaS and NfV. The VNF domain. Service graphs, MANO descriptors, Open orchestration. The virtualization layer VM centric model, containers versus hypervisors, FD.io. Summary Deploying NfV, performance, testing. Futures.