129 Driving courses in Coseley delivered Live Online

Duration 4 Days 24 CPD hours This course is intended for This is an intermediate-level programming course, designed for experienced .Net developers who wish to get up and running on developing well defended software applications. Real world programming experience with .Net is required. Overview Students who attend Attacking and Securing .Net Web Applications will leave the course armed with the skills required to recognize actual and potential software vulnerabilities and implement defenses for those vulnerabilities. This course begins by developing the skills required to fingerprint a web application and then scan it for vulnerabilities and bugs. Practical labs using current tools and techniques provide students with the experience needed to begin testing their own applications. Students also gain a deeper understanding of how attackers probe applications to understand the runtime environment as well as find potential weaknesses. This course the introduces developers to the most common security vulnerabilities faced by web applications today. Each vulnerability is examined from a .Net perspective through a process of describing the threat and attack mechanisms, recognizing associated vulnerabilities, and, finally, designing, implementing effective defenses. Practical labs reinforce these concepts with real vulnerabilities and attacks. Students are then challenged to design and implement the layered defenses they will need in defending their own applications. There is an emphasis on the underlying vulnerability patterns since the technologies, use cases, and methods of attack as constantly changing. The patterns remain the same through all the change and flux. This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in secure web application development, coding and design, coupling the most current, effective techniques with the soundest industry practices. Our instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. This lab-intensive course provides hands-on .Net security training that offers a unique look at .Net application security. Beginning with penetration testing and hunting for bugs in .Net web applications, you thoroughly examine best practices for defensively coding web applications, covering all the OWASP Top Ten as well as several additional prominent vulnerabilities. You will repeatedly attack and then defend various assets associated with fully functional web applications and services, driving home the mechanics of how to secure .Net web applications in the most practical of terms. Bug Hunting Foundation Why Hunt Bugs? Safe and Appropriate Bug Hunting/Hacking Scanning Web Applications Scanning Applications Overview Moving Forward from Hunting Bugs Removing Bugs Foundation for Securing Applications Principles of Information Security Bug Stomping 101 Unvalidated Data Injection Broken Authentication Sensitive Data Exposure XML External Entities (XXE) Broken Access Control Bug Stomping 102 Security Misconfiguration Cross Site Scripting (XSS) Deserialization/Vulnerable Components Insufficient Logging and Monitoring Spoofing, CSRF, and Redirects Moving Forward with Application Security Applications: What Next? .NET Issues and Best Practices Making Application Security Real Time Permitting Topics Cryptography Overview .NET Cryptographic Services

Women in Local Government Leadership Workshop is for Local Government professionals looking to learn new skills with like-minded peers and further or advance their within Local government.

Are you struggling with a Data Governance issue and wish you had a team of other Data Governance professionals you could bounce it around with? You’ve done Data Governance training and you know what you’re focusing on. While your team is supportive, you spend a lot of time dealing with, and driving forward, culture change, managing stakeholders, and fielding questions from people who have their own priorities and now need to do this ‘Data Governance stuff’ on top. It would be nice, once in a while, to have a conversation about how to achieve something free from internal issues. You want to talk about best practices and get some alternative ideas. That’s what my Data Governance Mastermind gives you: space to reflect with the support of your peers and practical solutions you can implement.

'Motorcycle Skills - Improve your Riding in Eight Weeks' is an online distance learning e-course which will help motorcyclists improve their riding skills. It's suitable for intermediate and advanced riders.

This two-day programme gives the key insights and understanding of contracting principles and the impact they have on business and operations. The course is designed for individuals involved in or supporting contracting who want to improve their commercial management skills; individuals in functions such as project management, business development, finance, operations who need practical training in commercial management; general audiences wanting to gain a basic understanding of commercial management. This is an assessed programme, leading to the International Association for Contracts & Commercial Management (IACCM)'s coveted Contract and Commercial Management Associate (CCMA) qualification. The programme addresses 31 different subject areas, across the five stages of the contracting process. By the end of the course the participants will be able, among other things, to: Develop robust contract plans, including scope of work and award strategies Conduct effective contracting activities, including ITT, RFP, negotiated outcomes Negotiate effectively with key stakeholders, making use of the key skills of persuading and influencing and to work with stakeholders to improve outcomes Set up and maintain contract management systems Take a proactive approach to managing contracts Make effective use of lessons learned to promote improvements from less than optimal outcomes, using appropriate templates Develop and monitor appropriate and robust Key Performance Indicators to manage the contractor and facilitate improved performance Understand the approvals process and how to develop and present robust propositions Make appropriate use of best practice contract management tools, techniques and templates DAY ONE 1 Introductions Aims Objectives Plan for the day 2 Commercial context Explaining the contracting context Define the key objective The importance of contact management Impact upon the business 3 Stakeholders How to undertake stakeholder mapping and analysis Shared vision concept, How to engage with HSE, Finance, Operations 4 Roles and responsibilities Exploring the key roles and responsibilities of contract administrators, HSE, Finance, Divisional managers, etc 5 Initiating the contract cycle Overview of the contracting cycle Requirement to tender Methods Rationale and exceptions 6 Specifications Developing robust scope of works Use of performance specifications Output based SOW 7 Strategy and award criteria Developing a robust contract strategy Award submissions/criteria 8 Managing the tender process Review the pre-qualification process Vendor registration rules and processes Creation of bidder lists Evaluation, short listing, and how to use of the 10Cs© model template and app 9 Types of contract Classify the different types of contracts Call-offs Framework agreement Price agreements Supply agreements 10 The contract I: price Understanding contract terms Methods of compensation Lump sum, unit price, cost plus, time and materials, alternative methods Cost plus a fee, target cost, gain share contracts Advanced payments Price escalation clauses DAY TWO 11 Risk How to manage risks Risk classification Mitigation of contractual risks 12 Contractor relationship management session Effectively managing relationships with contractors, Types of relationships Driving forces? Link between type of contract and style of relationship 13 Disputes Dealing with disputes Conflict resolution Negotiation Mediation Arbitration 14 Contract management Measuring and improving contract performance Using KPIs and SLAs Benchmarking Cost controls 15 The contract II: terms and conditions Contract terms and conditions Legal aspects Drafting special terms 16 Managing claims and variations How to manage contract and works variations orders Identifying the causes of variations Contractor claims process 17 Completion Contract close-out process Acceptance/completion Capture the learning/HSE Final payments, evaluation of performance 18 Close Review Final assessment

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

STGO Abnormal Loads

DG Awareness & Highway Code Course Details: Course Overview Time: 8:00 AM - 16:00 PM (Registration starts at 7:30 AM) Location: Online Price: £50 This comprehensive one-day course provides essential training in two critical areas: Dangerous Goods (DG) awareness and the Highway Code. DG Awareness: Understand the different hazard classes and types of dangerous goods. Learn about the legal requirements for transporting and storing DG. Discover the essential safety protocols for handling hazardous materials. Identify and assess potential risks associated with DG. Apply best practices for documentation and labeling. Highway Code: Course introduction, objectives, and expectations. Introduction to the Highway Code and its relevance. Types of road users and training for various groups. Respecting and understanding the risks to different road user categories. Confirmation of knowledge quizzes covering all aspects of the Highway Code and traffic regulations. Key Course Benefits: Meet Driver CPC requirements for periodic training Enhance your understanding of dangerous goods transportation Improve your knowledge of the Highway Code Learn how to respond to accidents, incidents, and breakdowns Boost your overall road safety awareness Don't miss this opportunity to enhance your knowledge and skills in DG Awareness & Highway Code. Register now for £50 and secure your spot!

What do engineers and project managers need to know of finance? 'Nothing - leave it to the accountants!' No, no, no! Engineers must be conversant with the terminology and statements that accountants use. Technical expertise in projects, service delivery, production or other areas can only really be harnessed if the managers understand the accounting and reporting that drives businesses. This course gives the necessary understanding to project, production and technical managers. It develops their skills in understanding financial and management accounting. Accountants may not always like it but a major part of their work is to be the 'servants of business' and to gather, compile and present your figures. So you must understand the figures - they belong to you, your processes or projects. There are many reasons for maintaining accurate accounts. This course focuses on the strategic issues (those over-used words) - what figures reveal about the drivers of business and what they reveal about the day-to-day issues that accountants bother you with. The course will enhance your understanding of finance and of the accounting issues which affect your projects, production and technical areas of business. This course will help you: Understand the business world in figures - make sense of what the accountants are telling you Appreciate what drives business - and how this affects your role in your part of the business Relate your activities to the success of the business - through figures Gain the skills to advance in management - financial awareness is a 'must have' if you are to progress in your career 1 What do accountants do? The finance function, types of accountant, financial v management accounting and the treasury function Understanding the role of the finance function and how the information you provide may be used 2 The basic financial statements Balance sheets and income statements (P&L accounts) What they are, what they contain and above all what they can reveal - how to read them The accounting process - from transactions to financial statements What underpins the statements - accounting systems and internal controls 3 Why be in business - from a financial perspective The driving forces behind financial information Performance measures - profitability, asset utilisation, sales and throughput, managing capital expenditure 4 Accounting rules - accounting standards Accounting concepts and the accounting rules: accruals, 'going concern' - substance over form and other 'desirable qualities' Accruals - why the timing of a transaction is so important to the finance function Depreciation and amortisation - the concepts and practice Accounting standards - the role of International Financial Reporting Standards 5 Cash The importance of cash flow - working capital management Cash flow statements - monitoring overall cash flows Raising cash - levels of borrowing, gearing Spending cash - an outline of capital expenditure appraisal 6 Budgeting Why budget? - good and bad practice Determining why budgets play a key role and should not be simply an annual ritual Justifying your budgets - the link between the strategic plan and day-to-day budgeting - alignment of company culture Budgets as motivators - the importance of the right culture Techniques to improve budgeting - whether day-to-day or capital budgeting 7 Costing The type and detail of costing very much depends on your business - eg, manufacturing piston rings is quite different from the construction of a power plant Issues with overhead allocation Accounting for R&D 8 Reading financial statements Annual financial statements - why they are produced, what's in them and what you should look for Learning what a set of accounts reveals about a company's current situation, profitability and future prospects 9 Performance measurement - analytical reviews and ratio analysis ROI/ROCE Profitability, margins and cost control Sales - asset turnover Efficiency (asset / stock turnover, debtor / creditor days) 'City' measures Investment (interest / dividend cover, earnings per share, dividend yield)