29 Gan courses in London delivered Live Online

Learn how to better apply project management techniques to manage small projects as part of your normal role.

Learn how to manage internal and/or external stakeholders’ expectations within a project environment. Course overview Duration: 1 day (6.5 hours) This course is suitable for anyone who has to manage internal and/or external stakeholders’ expectations within a project environment. The course will provide tools and techniques to manage stakeholder’s expectations and needs. It will help participants to map all stakeholders who impact the capability to deliver the desired results. Participants will work with a fictitious project to bring all the analysis and tools to life.  Objectives  By the end of the course you will be able to: Identify both primary and secondary stakeholders Use tools and processes to manage stakeholder expectations Use techniques to help win support for your projects Put together a stakeholder communication plan Determine the best communication methods Build relationships between you and key stakeholders Use influencing skills to influence stakeholders before they influence you Effectively handle conflict that occurs throughout the project lifecycle Determine the fundamental rules of negotiation and how to achieve a satisfactory outcome Content Identification and stakeholder analysis Using a mind map to determine stakeholders and stakeholder groups Analysis of stakeholder interest and power Using different tools to help determine stakeholder needs and expectations Categorising your stakeholders into primary, secondary and key Interviewing stakeholders to determine needs, expectations and politics Influencing strategies Using a planning tool to determine how different stakeholders can be influenced Interviewing stakeholders to determine what will motivate/de-motivate them Looking at communication methods and choosing the most appropriate in order to influence and manage expectations Production the communication strategy Using a case study and project Gantt to produce a detailed communication plan Using a communication plan structure Conflict Management Identifying common causes of conflict in the project lifecycle Finding the most appropriate response to resolve conflicts effectively Determining your default position and understanding why it might not always be right Negotiation The different types of negotiation used in the project environment Determining a simple negotiation process Understanding the principles of effective negotiation – the do’s and don’ts

Course Objectives At the end of this course you will be able to: Identify the components of the Microsoft Project environment Create a new project plan Create the project schedule Use different views to analyse the project plan Create, allocate and manage resources in a project plan Finalise a project plan Track progress View and report project plan information ' 1 year email support service Customer Feedback Very good course. Learnt a lot. Looking forward to the next level. Alexandra - CIAL ' 1 year email support service Take a closer look at the consistent excellent feedback from our growing corporate clients visiting our site ms-officetraining co uk With more than 20 years experience, we deliver courses on all levels of the Desktop version of Microsoft Office and Office 365; ranging from Beginner, Intermediate, Advanced to the VBA level. Our trainers are Microsoft certified professionals with a proven track record with several years experience in delivering public, one to one, tailored and bespoke courses. Our competitive rates start from £550.00 per day of training Tailored training courses: You can choose to run the course exactly as they are outlined by us or we can customise it so that it meets your specific needs. A tailored or bespoke course will follow the standard outline but may be adapted to your specific organisational needs. Introduction to Microsoft Project Recap on project management concepts Project environment overview The 3 databases: Tasks, Resources and Assignments Different ways of displaying the Project Plan Access Help Creating a Project Plan Create a New Project Plan Project Information Create and apply the project calendar Defining recurring exceptions to the calendar Defining the calendar's work weeks Create the Summary tasks Create the Work Breakdown Structure Task creation and scheduling Exploring the Entry Table and its fields Task editing and the Task Information window Task Durations Defining Milestones Manual Scheduling vs Automatic Scheduling Changing the Task's Calendar Create a split in a Task Create Task Relationships Adding Lag or Lead to a Relationship Identifying the Critical Path Adding Constraints and Deadlines to Tasks Create Recurring Activities Adding Notes and links to Tasks Managing Resources Exploring the Entry Table and its fields Resource editing and the Resource Information window Resource Types Fixed Costs vs Variable Costs Adding Resource Costs Defining when costs accrue Changing the Resource Calendar and Availability Project calendar vs Resource and Task Calendar Assigning Resources to Tasks Effort Driven Scheduling Resolving Resource Overallocation Tracking the Project Progress Setting a Project Baseline Entering Actuals Different ways of viewing the Progress Checking if the Project is on track Viewing and Reporting Project Detail Adding Tasks to the Timeline and sharing it Modifying the Timescale and Zoom level Formatting the Gantt View Filtering and Grouping Tasks Print and Troubleshoot the Gantt View Using built-in Reports in Microsoft Project Who is this course for? Who is this course for? This course is designed for a person who has an understanding of project management concepts, who is responsible for creating and modifying project plans, and who needs a tool to manage these project plans. Requirements Requirements General knowledge of the Windows OS Career path Career path Microsoft Office know-how can instantly increase your job prospects as well as your salary. 80 percent of job openings require spreadsheet and word-processing software skills

Learn the art of tambour beading in this class

WORKSHOP: Working as a Psychologist Expert Witness specialising in Trauma and Memory: From Instruction to Cross Examination An online practical workshop for Clinical, Counselling and Forensic Psychologists, guiding you through the process of working as an Expert Witness.

Music industry advice sessions are back! Sound Gallery studios are proud to host once again music industry advice seminars led by Integrity Records Record label owner one of the U.K.’s longest running truly independent record labels and known for finding & nurturing cool new talent.  Find out how to pitch your music to music industry professionals, how to build and sustain a career as a professional musician, how to set up your own record label, how to protect your creation including copyright and music publishing, how to get airplay and more from Integrity Records CEO and founder Nick Tarbitt.  Nick has many years experience as a media & entertainment lawyer, advising musicians, management companies and record labels on contractual issues, but with a particular interest in assisting new artists, musicians and performers with their early steps in the industry, including their first band agreements, management contracts, recording deals, licensing and publishing agreements. Integrity Records releases, spanning various genres from punk to drum & bass via indie-folk and quirky pop, have been heard on BBC Radio 1, BBC 6 Music and BBC Radio 2, alongside XFM/Radio X, Q Radio, Amazing Radio and numerous regional stations in the UK and abroad. Many of their artists have played live sessions from the BBC Maida Vale studios for Steve Lamacq, Jo Whiley, Zane Lowe and more. Suitable for: unsigned and emerging artists, singer-songwriter, bands and musicians. Bookings: call the studio: 01392-495301 or email: marketing@sound-gallery.net Venue: Sound Gallery Studios, Exeter Phoenix, Gandy street, Exeter, EX4 3LS Costs:  £120 / 2 hr session for 1:1 sessions - £150 / 2 hr session for small groups 4-8 people

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

This programme concentrates on the core planning skills needed to develop sound practical project plans in a team environment. This enables the plan to be modified should requirements change or difficulties arise. The programme also gives participants the confidence to practise those skills and apply them in the work environment and deliver their projects more successfully in the future. Participants learn fundamental project management concepts and terminology, demystifying the project management process, and, in particular, how to: Break a project down into manageable sections and ensure nothing is left out Understand and apply estimating techniques to develop realistic estimates Sequence work effectively and carry out critical path analysis to determine project duration and which tasks to pay closest attention to Manage project risk effectively to protect project value Monitor, control and re-plan the project to best keep it on track Close out the project and ensure the project comes to an orderly end 1 Introduction Self-introductions and personal objectives Course objectives Sharing of project issues 2 Project management concepts Characteristics of a project and what should be kept as operational responsibilities Understanding the triple and quadruple constraints - and their limitations Prioritising requirements through the MOSCOW technique Product v project life cycle Key project roles and responsibilities - the importance of sponsorship and clarity of roles 3 Starting a project, and the importance of the terms of reference / project brief Avoiding the pressure to 'just do it'! The importance and benefits of planning The best time to learn! Initial project documentation - the BOSCARDI approach 4 Breaking the work down Understanding alternative breakdown structures such as the product breakdown structure and work breakdown structure Guidelines for creating a work breakdown structure to ensure the full work scope is identified 5 Estimating Alternative estimating techniques and associated confidence levels Further considerations - loss and resource factors 6 Organising the work Use of network diagrams to develop a clear sequence of work Critical path analysis and calculating the project duration and task float - and usage 7 The management of project risk Understanding the nature of project risk The risk analysis and risk management processes How to best manage threats and opportunities Running a risk workshop Using the risk register 8 Scheduling the work The importance of the Gantt chart and understanding its limitations The Gantt chart layout and using alternative views such as the tracking Gantt Using alternative dependencies 9 Resource issues Assigning resources and resolving resource overloads Crashing and fast-tracking your project and potential issues to look out for 10 Controlling the project The control cycle and alternative feedback mechanisms Alternative progress reporting Assessing the impact The importance of re-planning The benefits of control Change control - the importance of impact analysis The steps of change control and the use of the issue register 11 Closing the project The project closure checklist Reviewing the project - things to avoid Developing meaningful lessons and ensuring they are applied effectively The post-project review - its importance to the organisation

Duration 3 Days 18 CPD hours This course is intended for This advanced course is for IT professionals tasked with administering a Spectrum Scale system. Overview Please see Overview This course is intended for IT professionals tasked with administering a Spectrum Scale system. It includes information on installing, configuring and monitoring a Spectrum Scale cluster. Migrating to IBM Spectrum Scale 4.2Spectrum Scale 4.2 GUIMulti-clusterClustered NFSCluster Export Services for multi-protocol supportSMB Protocol SupportNFS Support in CES; Ganesha overview/performanceActive File ManagementAFM-Based Disaster Recovery (DR) and Asynchronous DRPlanning LTFS and GPFS environment for data archivingFile Placement OptimizerIBM© GPFS-FPO and integration with GPFS Hadoop connectorIBM© Spectrum Scale Call HomeMonitoring and performance tuningFlash Cache metadata migration