68 Robotics courses delivered Online

Become an iOS Augmented Reality Developer by Building 11 High-Level AR Apps using ARKit in iOS 11 and Swift 4.

Duration 1 Days 6 CPD hours This course is intended for This course does not have any technical knowledge prerequisites for the learners, besides being proficient in using a computer and the Internet. IT and/or AI knowledge is a benefit but not a hard requirement. Given the rapid development of AI and the broad range of its applications in everyday life, it is crucial for anyone to attend this course to update their digital skills in an ever-changing world. It is expected that all learners have registered for a free account of OpenAI ChatGPT at https://chat.openai.com. Overview Discover how AI relates to other 4th industrial revolution technologies Learn about AI, ML, and associated cognitive services Overview of AI development frameworks, tools and services Evaluate the OpenAI ChatGPT4 / ChatGPT3.5 model features in more detail The core aim of this ?AI for beginners? course is to introduce its audience to Artificial Intelligence (AI) and Machine Learning (ML) technologies and allow them to understand the practical applications of AI in their everyday personal and professional life. Moreover, the course aims to provide a handful of demos and hands-on exercises to allow the learners to familiarize themselves with usage scenarios of OpenAI ChatGPT and other Generative AI (GenAI) models. The content of this course has been created primarily by using the OpenAI ChatGPT model. AI theoretical concepts. Introduction to AI, ML, and associated cognitive services (Computer vision, Natural language processing, Speech analysis, Decision making). How AI relates to other 4th industrial revolution technologies (cloud computing, edge computing, internet of things, blockchain, metaverse, robotics, quantum computing). AI model classification by utilizing mind maps and the distinctive role of Gen AI models. Introduction to the OpenAI ChatGPT model and alternative generative AI models. Familiarization with the basics of the ChatGPT interface (https://chat.openai.com). Talking about Responsible AI: Security, privacy, compliance, copyright, legal challenges, and ethical implications. AI practical applications Overview of AI development frameworks, tools and services. AI aggregators review. Hand-picked AI tool demos: a.Workplace productivity and the case of Microsoft 365 Copilot. b.The content creation industry. Create text, code, images, audio and video with Gen AI. c.Redefining the education sector with AI-powered learning. Evaluate the OpenAI ChatGPT4 / ChatGPT3.5 model features in more detail: a.Prompting and plugin demos. b.Code interpreter demos. Closing words. Discussion with an AI model on the future of AI. Additional course details: Nexus Humans AI for beginners 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 AI for beginners 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 Level 4 course encourages individuals in digital and technical roles to enhance their skills by exploring different techniques, formats, and tools to communicate and understand the impact of their communication choices.

The course is relevant to anyone requiring an understanding of the use of Agile or looking to adopt it. This includes, but is not limited to, organisational leaders and managers, marketing executives and managers, and/or all professionals working in an Agile environment, including software sesters, developers, business analysts, UX designers, project management office (PMO), project support and project coordinators.

Sale Ends Today Automotive Engineering & Design Masterclass Admission Gifts FREE PDF & Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter Are you a professional feeling stuck in your career, or perhaps you're a beginner, unsure of where to start or how to break into your desired field? Whichever stage you're in, our exclusive Basic Automotive Engineering & Design Masterclass Bundle provides unique insights and tools that can help you achieve your goals. So, get ready to accelerate your career and become a leader in automotive engineering in the UK automotive sector, which is rapidly evolving with the advent of electric and hybrid technologies. The Automotive Engineering & Design Masterclass spans a wide array of critical subjects to mold you into a highly skilled automotive professional. Starting with essentials such as Automotive Engineering: Onboard Diagnostics and progressing to complex areas like Electric and Hybrid Vehicles Engineering, this course ensures a deep understanding of both foundational and advanced concepts. It also focuses on topics like Car Mechanic and Repair Training, while specialised modules like Electric Vehicle Battery Management System and Turbocharging equip you with niche skills that are highly valued in the industry. Courses Are Included In this Bundle: Course 01: Automotive Engineering: Onboard Diagnostics Course 02: Automotive Design Course 03: Automotive Engineering: Electric and Hybrid Vehicles Engineering Course 04: Automotive Engineering: Car Mechanic and Repair Training Course 05: Automotive Engineering: Supercharger Automobile Engineering Course 06: Automotive Engineering: Engine Lubrication Systems Online Course Course 07: A complete course on Turbocharging Course 08: Car Maintenance and Safety Training Course 09: Motorbike Maintenance & Servicing Course 10: Electric Vehicle Battery Management System Course 11: Vehicle Routing Problem with Spreadsheet Course 12: Power Electronics for Electrical Engineering Course 13: MATLAB Simulink for Electrical Power Engineering Course 14: Large Goods Vehicle (LGV)/HGV Course 15: Hybrid Vehicle Expert Training Course 16: MET Technician Course 17: Energy Saving in Electric Motors Course 18: Mechanical Engineering Course 19: Engineering Mechanics Course for Beginners Course 20: Electrical Machines for Electrical Engineering Course 21: Electrical Engineering - Light Current System Course 22: Heating Ventilation and Air Conditioning (HVAC) Technician Course 23: Electrical Engineering With Electric Circuits Course 24: Electronic Device Maintenance and Troubleshooting Course Course 25: Trigonometry for Electrical Engineering Course 26: Robotics - Sensors Course 27: Manual Handling Course 28: Workshop Technology: Machine Shop Theory Course 29: Good Manufacturing Practices (GMP) Course 30: Fire Safety Step into the future of automotive technology by mastering the skills taught in the Automotive Engineering & Design Masterclass. This comprehensive training will not only elevate your technical and design capabilities but also enhance your career prospects in a sector that is integral to technological advancement and environmental sustainability. Enrol now to transform your passion for automotive technology into a rewarding career that helps shape the future of transportation! Learning Outcomes of this Bundle: Diagnose and troubleshoot with advanced onboard diagnostics skills. Design and engineer cutting-edge electric and hybrid vehicles. Master mechanical aspects of supercharging and turbocharging technologies. Effectively maintain and repair diverse automotive systems. Develop comprehensive skills in battery management for electric vehicles. Apply modern electrical engineering principles to automotive technology. But that's not all. When you enrol in Automotive Engineering & Design Masterclass Training, you'll receive 30 CPD-Accredited PDF Certificates, Hard Copy Certificates, and our exclusive student ID card, all absolutely free. Why Prefer this Course? Get a Free CPD Accredited Certificate upon completion of the course Get a Free Student ID Card with this training program (£10 postal charge will be applicable for international delivery) The course is Affordable and Simple to understand Get Lifetime Access to the course materials The training program comes with 24/7 Tutor Support Start your learning journey straight away! The Automotive Engineering & Design Masterclass is expertly designed to ensure that you emerge as a highly proficient professional, ready to tackle the challenges of the modern automotive industry. This course will empower you with advanced onboard diagnostics skills, a foundational aspect of automotive engineering that is critical in the era of high-tech vehicles. By understanding how to diagnose and troubleshoot vehicle systems effectively, you'll be able to offer invaluable insights and solutions in difficult scenarios, significantly enhancing your employability and career advancement opportunities. Furthermore, the masterclass dives deep into the design and engineering of electric and hybrid vehicles, placing you at the forefront of automotive innovation. As the industry shifts towards sustainable and eco-friendly solutions, your ability to engineer these advanced vehicles will position you as a key player in driving the future of transportation. This expertise not only boosts your career potential but also aligns you with global trends towards green technology. Moreover, this diploma offers learners the opportunity to acquire a Recognised Qualification that is highly valued in the field of Automotive Engineering. With this Certification, graduates are better positioned to pursue career advancement and higher responsibilities within the Automotive Engineering setting. The skills and knowledge gained from this course will enable learners to make meaningful contributions to Automotive Engineering related fields impacting their Automotive Engineering experiences and long-term development. Course Curriculum Course 01: Automotive Engineering: Onboard Diagnostics Module 01: Introduction Module 02: Brief history Basic working of OBD Module 03: Onboard diagnostic apps Module 04: Exhaust gas - Diagnostics Module 05: APPS on Onboard diagnostics Module 06: Engine - Diagnostics Module 07: Diagnostics - spark plug Module 08: Diagnostics - Fuel injection Module 09: Diagnosis - Lubrication Course 02: Automotive Design Module 01: Emotion and Flow: Secrets of Car Designer Line Quality Module 02: Get Inspired: Developing Your Style and Technique with Speed Forms Module 03: Master Your Wheels: Secrets of Drawing Circles Module 04: Talk the Talk: The Vocabulary of Automotive Design Module 05: In the Beginning: Secrets of Drawing Great Side Views Module 06: Coming and Going: Secrets of Drawing Great Front and Rear Views Module 07: A View from the Top: Secrets of Drawing a Tip-Up View Module 08: Toward the Within: Introduction to Interiors Module 09: In a Brilliant Light: Understanding Light and Shadows Module 10: Shine Like it does: Understanding Reflections Course 03: Automotive Engineering: Electric and Hybrid Vehicles Engineering Module 01: Introduction Module 02: Key Motivations for HEVs Rise Module 03: What is HEV & world famous models Module 04: Architecture of Hybrid Electric vehicles Module 05: Parallel Hybrid Vehicles Module 06: Other types of Architecture Module 07: Modes of Operation Module 08: Engine & Motor Module 09: Motor Efficiency Module 10: Generator & Power Split Device Module 11: Battery storage systems Module 12: Fundamentals of Regenerative Braking =========>>>>> And 27 More Courses <<<<<========= How will I get my Certificate? After successfully completing the course, you will be able to order your Certificates as proof of your achievement. PDF Certificate: Free (Previously it was £12.99*30 = £390) CPD Hard Copy Certificate: Free (For The First Course: Previously it was £29.99) CPD 300 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone interested in learning more about the topic is advised to take this bundle. This bundle is ideal for: Aspiring automotive engineers. Current auto mechanics. Electrical engineering students. Automotive design enthusiasts. Hybrid technology professionals. Manufacturing sector employees. Requirements You will not need any prior background or expertise to enrol in this course. Career path After completing this bundle, you are to start your career or begin the next phase of your career. Automotive Engineer: $68,000 - $110,000 Mechanical Engineer: $70,000 - $100,000 Electrical Engineer: $75,000 - $105,000 Automotive Technician: $40,000 - $65,000 Systems Designer: $85,000 - $120,000 Production Manager: $60,000 - $90,000 Certificates CPD Accredited Digital certificate Digital certificate - Included CPD Accredited e-Certificate - Free Enrolment Letter - Free Student ID Card - Free CPD Accredited Hard copy certificate Hard copy certificate - Included If you are an international student, then you have to pay an additional 10 GBP for each certificate as an international delivery charge.

Explore the world of Artificial Intelligence with our comprehensive Foundations Course. From understanding the basics of AI and essential mathematical principles to delving into advanced topics like Deep Learning, Natural Language Processing, and Robotics – this course equips you with the knowledge and skills needed to navigate the dynamic landscape of AI. Whether you're a student, professional, or enthusiast, join us on a journey to build a solid foundation in AI and develop practical applications that shape the future. Enroll now and empower yourself to contribute to the exciting field of Artificial Intelligence.

This Level 4 practitioner award encourages individuals in or working towards a leadership role (this could be an IT or technical based-role), and you want to demonstrate modern leadership behaviours to nurture a high-performing team, especially during a time of organisational change.

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

Duration 5 Days 30 CPD hours This course is intended for This course is designed for technology leaders, solution developers, project managers, organizational decision makers, and other individuals seeking to demonstrate a vendor-neutral, cross-industry understanding of ethics in emerging data-driven technologies, such as AI, robotics, IoT, and data science. This course is also designed for professionals who want to pursue the CertNexus Certification Exam CET-110: Certified Ethical Emerging Technologies. Overview In this course, you will incorporate ethics into data-driven technologies such as AI, IoT, and data science. You will: Describe general concepts, theories, and challenges related to ethics and emerging technologies. Identify ethical risks. Practice ethical reasoning. Identify and mitigate safety and security risks. Identify and mitigate privacy risks. Identify and mitigate fairness and bias risks. Identify and mitigate transparency and explainability risks. Identify and mitigate accountability risks. Build an ethical organization. Develop ethical systems in technology-focused organizations. Mutually reinforcing innovations in computing and engineering are catapulting advances in technological production. From blockchain and artificial intelligence (AI) to gene editing and the Internet of Things (IoT), these advances come with tremendous opportunities for improvement in productivity, efficiency, and human well-being. But as scandals increasingly demonstrate, these advances also introduce new and serious risks of conflict and harm.Technology professionals now face growing demands to identify and mitigate ethical risks to human rights and the environment, as well as to navigate ethical tradeoffs between qualities such as privacy and accuracy, fairness and utility, and safety and accountability. This course provides the tools to identify and manage common ethical risks in the development of emerging data-driven technologies. It distills ethical theory, public regulations, and industry best practices into concrete skills and guidelines needed for the responsible development of digital products and services. By following the course's practical, problems-based approach, learners will become adept at applying theories, principles, frameworks, and techniques in their own roles and organizations. Introduction to Ethics of Emerging Technologies Topic A: What?s at Stake Topic B: Ethics and Why It Matters Topic C: Ethical Decision-Making in Practice Topic D: Causes of Ethical Failures Identifying Ethical Risks Topic A: Ethical Reasons Topic B: Stumbling Blocks for Ethical Reasoning Topic C: Identify Ethical Risks in Product Development Topic D: Tools for Identifying Ethical Risks Topic E: Use Regulations, Standards, and Human Rights to Identify Ethical Risks Ethical Reasoning in Practice Topic A: Ethical Theories Topic B: Use Ethical Decision-Making Frameworks Topic C: Select Options for Action Topic D: Avoid Problems in Ethical Decision-Making Identifying and Mitigating Security Risks Topic A: What Is Security? Topic B: Identify Security Risks Topic C: Security Tradeoffs Topic D: Mitigate Security Risks Identifying and Mitigating Privacy Risks Topic A: What Is Privacy? Topic B: Identify Privacy Risks Topic C: Privacy Tradeoffs Topic D: Mitigate Privacy Risks Identifying and Mitigating Fairness and Bias Risks Topic A: What Are Fairness and Bias? Topic B: Identify Bias Risks Topic C: Fairness Tradeoffs Topic D: Mitigate Bias Risks Identifying and Mitigating Transparency and Explainability Risks Topic A: What Are Transparency and Explainability? Topic B: Identify Transparency and Explainability Risks Topic C: Transparency and Explainability Tradeoffs Topic D: Mitigate Transparency and Explainability Risks Identifying and Mitigating Accountability Risks Topic A: What Is Accountability? Topic B: Identify Accountability Risks Topic C: Accountability Tradeoffs Topic D: Mitigate Accountability Risks Building an Ethical Organization Topic A: What Are Ethical Organizations? Topic B: Organizational Purpose Topic C: Ethics Awareness Topic D: Develop Professional Ethics within Organizations Developing Ethical Systems in Technology-Focused Organizations Topic A: Policy and Compliance Topic B: Metrics and Monitoring Topic C: Communication and Stakeholder Engagement Topic D: Ethical Leadership