This training is for lawyers and covers key topics to ensure compliance with the Lexcel standard and other regulations.
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
Our Financial Compliance and Legal Aid Payments Course provides a brief overview of historical changes and the current regulations. The course will cover what VAT regulations and the SRA Accounts Rules say on legal aid payments and will provide practical advice and tips on how to account for these payments so you adhere to the rules and regulations of the profession. Target Audience This online course is suitable for those in the legal profession who oversees, or is responsible for or involved in accounting for legal aid funds, including, costs lawyers, legal cashiers, COFA, those supporting the COFA, account managers, etc. Resources An information pack including the course slides will be provided to all delegates after the course, which may be useful for ongoing reference. Please note a recording of the course will not be made available. Speaker Sarah Charlton, Consultant, DG Legal Sarah has a BSc (Hons) in Applied Accounting and is a Fellow member of the Association of Chartered and Certified Accountants. Her career spans over 35 years working within the legal sector, fulfilling roles from COFA through to CEO. During her career she has worked with a number of legal regulators, professional bodies and government organisations. Sarah has been a member of the Institute of Legal Finance and Management throughout her career, qualifying as a Fellow member in 2005. Sarah also served as chairperson between 2010-2012 and continues to serve as an Executive Council Member.
Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview This skills-focused combines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques. Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Building Recommendation Systems with Python (TTAI2360) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Building Recommendation Systems with Python (TTAI2360) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
This one day course will support teachers and RSE leads in special colleges and special schools with post 16 learners to deliver a meaningful curriculum through the Preparing for Adulthood outcomes. The course will explore key issues for older learners, including how to teach about practical aspects of relationships such as attraction and fancying people, starting relationships, negotiation and consent discussions, and how to keep yourself safe. Participants will leave with increased confidence to develop and deliver a skills-based, rights focused curriculum that will empower learners to be able to navigate their personal lives and relationships with autonomy. Aim: To develop confidence to create and deliver an age-appropriate, rights based RSE curriculum for young adults with learning disabilities. Outcomes: Participants will develop understanding of requirements for RSE for older learners, including the statutory guidance and preparation for adulthood outcomes, and how RSE can support independent living consider specific challenges young people with SEND may face in developing relationships and explore practical and creative ways to support relationship skill development explore strategies to address sexualised behaviour, and what to do if a learner begins or wants to masturbate in college Who is this course for? This one day course is ideal for teachers and RSE leads working in special schools and tutors in colleges with older learners, up to age 25, and beyond.
Duration 1.5 Days 9 CPD hours This course is intended for This course is intended for individuals who want to gain basic knowledge communicating, etiquette, professionalism and time management for the office environment. Overview Upon successful completion of this course, students will be able to communicate, be professional and manage their time effectively in a business environment. In this course, students will learn how to communicate, act and manage time effective in a business environment. Getting Started Icebreaker Housekeeping Items The Parking Lot Workshop Objectives The Big Picture What is Communication? How Do We Communicate? Other Factors in Communication Understanding Communication Barriers An Overview of Common Barriers Language Barriers Cultural Barriers Differences in Time and Place Paraverbal Communication Skills The Power of Pitch The Truth about Tone The Strength of Speed Non-Verbal Communication Understanding the Mehrabian Study All About Body Language Interpreting Gestures Speaking like a Star S = Situation T = Task A = Action R = Result Summary Listening Skills Seven Ways to Listen Better Today Understanding Active Listening Sending Good Signals to Others Asking Good Questions Open Questions Closed Questions Probing Questions Appreciative Inquiry The Purpose of AI The Four Stages Examples and Case Studies Mastering the Art of Conversation Level One: Discussing General Topics Level Two: Sharing Ideas and Perspectives Level Three: Sharing Personal Experiences Our Top Networking Tips Advanced Communication Skills Understanding Precipitating Factors Establishing Common Ground Using ?I? Messages Wrapping Up Words from the Wise Review of Parking Lot Lessons Learned Completion of Action Plans and Evaluations Principles of Professional Behavior Always be Your Best Meeting and Greeting Sending Social Invitations to Business Associates Interview Etiquette Interviewing Before the Interview In the Waiting Room During the Interview After the Interview Job Fair Interviews Planning & Attending Business Meetings Office Meetings Meal Meetings Electronic Etiquette Voicemail Cell Phones Email Multiculture Etiquette Defining the Challenge Five Steps to Dealing with Diversity Guidelines for Managing Diverse Relationships Time Management Concepts Benefits of better time utilization Who controls your schedule? Your Job: What You Are Responsible for Accomplishing? Your job responsibilities Setting objectives Setting priorities How to Use Your Time Gathering data-the time log Analyzing the data Delegation: Working Through Others Why some people don't delegate Levels of delegation How to delegate Benefits of delegation Getting started Planning: Keys to Achievement Planning: Keys to Achievement Coping with Common Time Wasters Coping with self-generated time wasters Coping with environmental time wasters Personal Needs that Get in the Way of Effective Time Utilization Needs profile analysis Self-assessment questionnaire Applying needs assessment results Planning for Improvement Six tips for effective time management Planning for improved time utilization Follow-Up: Staying on Track Time savings progress report Time savings progress chart Time management progress survey Additional course details: Nexus Humans Business Soft Skills training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Business Soft Skills course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
A workshop on EMDR with clients who are Neurodivergent on 13th of May 2025.
This module aims to develop knowledge and understanding of the exporting process used in international trade from novice to practitioner. It includes documentation, incoterms, responsibilities of an exporter, commodity codes, origin and duties and taxes.
QA Level 1 Award In Health And Safety In The Workplace (RQF) Face to Face: Half-day course Virtual Classroom: Spread over 2 sessions of 2½ hr duration A basic course to train your workers in basic health and safety Teaches workers how to keep themselves and others safe at work Course Contents: Roles and responsibilities of employers and employees The importance of health and safety in the workplace Workplace hazards and Risks, including:Slips, Trips and FallsManual HandlingFireWorking from HeightElectricityHazardous SubstancesMachinery and Vehicles Workplace conditions that can affect health and safety Health and Safety Signage Personal Protective Equipment and its uses Importance of Personal hygiene The Purpose of First Aid Provision The need for Reporting Incidents and ill Health Benefits of this course: In 2018/19, 1.4 million people suffered from a work-related illness 581,000 sustained an injury 147 People lost their lives The estimated cost of injuries and ill health last year was £15 billion 28.2 million working days, or 108,045 working years, were lost due to work-related illnesses and injuries It is an employer's duty to protect the health, safety and welfare of their employees and other people who might be affected by their business. This includes providing sufficient information, instruction and training of employees, so they can work in a way that does not put themselves or others at risk Our QA Level 1 Award in Health and Safety in the Workplace (RQF) course helps employs gain a bit more understanding of health and safety issues and their own role within that Accredited, Ofqual regulated qualification: Our Health and Safety Training Course is a nationally recognised, Ofqual regulated qualification accredited by Qualsafe Awards.This means that you can be rest assured that your Health and Safety Certificate fulfils the legal requirements and is a very good way to make sure you and your employees are trained in Health and Safety.The Ofqual Register number for this course is 603/0774/2