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CIEH Level 3 Food Safety in manufacturing. Delivered online (Zoom) by a live tutor. Exam and Certificate fee included in the price.

Duration 2 Days 12 CPD hours This course is intended for The target audience for the DevOps Foundation course includes Management, Operations, Developers, QA and Testing professionals such as: Individuals involved in IT development IT operations or IT service management. Individuals who require an understanding of DevOps principles. IT professionals working within, or about to enter, an Agile Service Design Environment The following IT roles: Automation Architects, Application Developers, Business Analysts, Business Managers, Business Stakeholders, Change Agents, Consultants, DevOps Consultants, DevOps Engineers, Infrastructure Architect, Integration Specialists, IT Directors, IT Managers, IT Operations, IT Team Leaders, Lean Coaches, Network Administrators, Operations Managers, Project Managers, Release Engineers, Software Developers, Software Tester/QA, System Administrators, Systems Engineers, System Integrators, Tool Providers. Overview The learning objectives for DevOps Foundation include an understanding of: DevOps objectives and vocabulary Benefits to the business and IT Principles and practices including Continuous Integration, Continuous Delivery, testing, security and the Three Ways DevOps relationship to Agile, Lean and ITSM Improved workflows, communication and feedback loops Automation practices including deployment pipelines and DevOps toolchains Scaling DevOps for the enterprise Critical success factors and key performance indicators Real-life examples and results The DevOps Foundation course provides a baseline understanding of key DevOps terminology to ensure everyone is talking the same language and highlights the benefits of DevOps to support organizational success. Learners will gain an understanding of DevOps, the cultural and professional movement that stresses communication, collaboration, integration, and automation to improve the flow of work between software developers and IT operations professionals. This course prepares you for the DevOps Foundation (DOFD) certification. Exploring DevOps Defining DevOps Why Does DevOps Matter? Core DevOps Principles The Three Ways The First Way The Theory of Constraints The Second Way The Third Way Chaos Engineering Learning Organizations Key DevOps Practices Continuous Testing, Integration, Delivery, Deployment Site Reliability & Resilience Engineering DevSecOps ChatOps Kanban Business and Technology Frameworks Agile ITSM Lean Safety Culture Learning Organizations Continuous Funding Culture, Behaviors & Operating Models Defining Culture Cultural Debt Behavioral Models Organizational maturity models Automation & Architecting DevOps Toolchains CI/CD Cloud, Containers, and Microservices AI and Machine Learning Automation DevOps Toolchains Measurement, Metrics, and Reporting The Importance of Measurement DevOps Metrics - Speed, Quality, Stability, Culture Change lead/cycle time Value Driven Metrics Sharing, Shadowing and Evolving DevOps in the Enterprise Roles DevOps Leadership Organizational Considerations Getting Started Challenges, Risks, and Critical Success Factors Additional course details: Nexus Humans DevOps Foundation (DevOps Institute) 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 DevOps Foundation (DevOps Institute) 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.

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is as follows: IT Solution Architects Network Security Architects Networking Admin and Operations Networking Field Engineers In this workshop you will learn why we are implementing Assurance, and what does looks like and key features. We will also discuss the Cisco DNA center appliance and workflow and tasks associated with an implementation. Module 1: Introduction to Cisco DNA Center Assurance Introduction to DNA Center System Architecture Key Features and Use Cases Introduction to Cisco ISE and DNAC-ISE integration Module 2: Design Network design options Sites Creating Enterprise and Sites Hierarchy Configuring General Network Settings Loading maps into the GUI IP Address Management Software Image Management ? Lab on Day 5 Network Device Profiles AAA SNMP Syslog IP address pools Creating Enterprise and Guest SSIDs ? Lab on Day 2 Creating the wireless RF Profile Cresting the Guest Portal for the Guest SSIDs Network profiles ? Lab on Day 2 Authentication templates Module 3: Discovery and Provision Device Discovery and Protocols Devices Onboarding Assigning Devices to a site Provisioning device with profiles Plug and Play Templates Templates for Day-0 Templates for Day-N operations Module 4: Monitoring Device, Client, and Application Health DNAC Telemetry Monitoring Network Device Health and Performance Monitoring Wired and Wireless Client Health and Performance Monitoring Application Health and Performance Module 5: Application Visibility and DNAC Integration with Umbrella Monitoring Application Visibility in DNA Center Umbrella Introduction DNA Center Umbrella Integration and Use Cases Module 6: Troubleshooting Issues, Observing Insights and Trends Detect Issues, Insights, and Trends in the Network DNA Center Integration with other tools for Monitoring and Management Module 7: Troubleshooting using Cisco DNA Center Assurance Tools DNAC Assurance Troubleshooting Tools Using Sensor Tests Using Intelligent Capture Spectrum Analysis Module 8: DNAC and Thousand Eyes Introduction to ThousandEyes ThousandEyes Use Cases DNA Center and ThousandEyes Integration Module 9: AI Analytics and Machine Learning in DNA Center Overview of AI Analytics and ML (Machine Learning) DNA Center AI and ML Use Cases Module 10: DNA Center Maintenance DNA Center Reports DNA Center Backup and Restore

This module aims to develop an understanding of supply chain management in international trade. This includes defining supply chain management, the relationship between supply chain and logistics, effective supply chain planning and responding to problems and issues associated with international trade.

Duration 1 Days 6 CPD hours For the better part of every day, we are communicating to and with others. Whether it?s the speech you deliver in the boardroom, the level of attention you give your spouse when they are talking to you, or the look you give the cat, it all means something. This workshop will help participants understand the different methods of communication and how to make the most of each of them. 1 - Getting Started Icebreaker Housekeeping Items The Parking Lot Workshop Objectives 2 - The Big Picture What is Communication? How Do We Communicate? Other Factors in Communication 3 - Understanding Communication Barriers An Overview of Common Barriers Language Barriers Cultural Barriers Differences in Time and Place 4 - Paraverbal Communication Skills The Power of Pitch The Truth about Tone The Strength of Speed 5 - Non-Verbal Communication Understanding the Mehrabian Study All About Body Language Interpreting Gestures 6 - Speaking Like a STAR S = Situation T = Task A = Action R = Result Summary 7 - Listening Skills Seven Ways to Listen Better Today Understanding Active Listening Sending Good Signals to Others 8 - Asking Good Questions Open Questions Closed Questions Probing Questions 9 - Appreciative Inquiry The Purpose of AI The Four Stages Examples and Case Studies 10 - 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 11 - Advanced Communication Skills Understanding Precipitating Factors Establishing Common Ground Using ?I? Messages 12 - Wrapping Up Words from the Wise Review of Parking Lot Lessons Learned Completion of Action Plans and Evaluations Additional course details: Nexus Humans Communication Strategies 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 Communication Strategies 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.

Why Choose Unity 3D Game Design Training Course? Course Link Unity transforms ideas into reality, offering limitless possibilities for 2D and 3D games, VR, AR, and AI experiences. From films to architecture, training videos, and interactive tutorials, Unity revolutionizes industries with its interactive engagement, making it the top choice for solutions. Duration: 10 hrs Method: 1-on-1, Personalized attention Schedule: Tailor your own hours of your choice, available from Mon to Sat between 9 am and 7 pm Is Unity Good for Beginners? Definitely! Unity is an ideal starting point for beginners in game development. It offers an accessible platform to learn state logic and C# programming, making it popular among new programmers. Whether you choose self-guided or structured learning, Unity provides a strong foundation for 3D game development. Coding in Unity? Coding is optional in Unity, thanks to the visual scripting tool, Bolt. Users can implement ideas without coding using flow graphs and state graphs for low-level and high-level logic. Paid tools like PlayMaker and Adventure Creator offer more advanced gameplay and AI behaviors. How Does Unity's Game Engine Work? Unity operates as a versatile scene player, initializing settings for graphics, audio, and input devices at game start. It loads scenes with assets and game objects, executing a cycle that renders scenes, runs physics simulations, and handles events, providing a seamless and dynamic game experience. Is Unity Good for Beginners? Definitely! Unity is an ideal starting point for beginners in game development. It offers an accessible platform to learn state logic and C# programming, making it popular among new programmers. Whether you choose self-guided or structured learning, Unity provides a strong foundation for 3D game development. 10-hour Unity 3D Game Design Training Course: Module 1: Introduction to Unity 3D (2 hours) - What is Unity 3D and why use it for game design? - Understanding the Unity 3D interface - Creating and managing projects in Unity 3D - Importing and managing assets in Unity 3D - Understanding game objects and components in Unity 3D Module 2: Game Mechanics (2 hours) - Basic game mechanics and concepts - Player movement and camera control - Creating and controlling game objects - Working with physics and collision detection - Creating interactive environments Module 3: Scripting with C# (2 hours) - Introduction to C# scripting language - Understanding variables and data types in C# - Creating and using functions in C# - Controlling game objects with C# - Understanding game loops and events Module 4: User Interfaces and Audio (2 hours) - Designing user interfaces in Unity 3D - Creating and using buttons, sliders, and input fields - Audio import and editing in Unity 3D - Creating and controlling game sound effects and background music Module 5: Optimization and Deployment (2 hours) - Understanding game optimization in Unity 3D - Optimizing game performance with scripting - Building and testing games for desktop and mobile platforms - Publishing games on the web or app stores Introduction to Unity: - Introduction to gaming and the game development process - Unity Basics - Interface - Inspector - Project and Hierarchy Starting Making a Game: - Working with Projects - Creating Projects - Importing Geometry - Importing Textures - Using the terrain generator to make the terrain - Creating basic primitives in Unity Materials: - Working with materials 1 - Working with materials 2 - Finishing materials on all objects Lighting: - Creating lights - Adjusting Lights - Creating Sunlight Animation: - Animating objects - Animating lights - Adjusting Animations Audio: - Adding Sound - Interacting with sound - Modifying sound Programming Tools: - JavaScript - Editor for JavaScript - Variables and functions - Simple programming Testing: - Testing the game - Fixing bugs - Making changes in games Building the Game: - Game authoring Settings - Building the game for windows - Playing the game Utilize Unity Pro, the ultimate real-time development platform, to craft 3D, 2D, VR, and AR experiences across diverse industries. From games to auto, AEC, and film, Unity Pro empowers you to create immersive content with multi-platform support. Visit https://www.unity.com/ to kickstart your journey today, enabling faster iterations and business growth through unparalleled development capabilities.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning on AWS 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 Deep Learning on AWS 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.

Duration 4 Days 24 CPD hours This course is intended for This course is geared for experienced skilled Java developers, software developers, data scientists, machine learning experts or others who wish to transtion their coding skills to Scala, learning how to code in Scala and apply it in a practical way. This is not a basic class. Overview Working in a hands-on learning environment led by our expert instructor you'll: Get comfortable with Scala's core principles and unique features, helping you navigate the language confidently and boosting your programming skills. Discover the power of functional programming and learn techniques that will make your code more efficient,maintainable, and enjoyable to write. Become proficient in creating dynamic web applications using the Play Framework, and easily connect to databases with the user-friendly Slick library. Master concurrency programming with Akka, empowering you to build scalable and fault-tolerant applications that excel in performance. Enhance your testing skills using ScalaTest and ScalaCheck, ensuring the reliability and quality of your Scala applications, while having fun in the process. Explore the fascinating world of generative AI and GPT technologies, and learn how to integrate them into your projects,adding a touch of innovation and intelligence to your Scala solutions. If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals. Discover the power of Scala programming in our comprehensive, hands-on technical training course designed specifically for experienced object-oriented (OO) developers. Scala is a versatile programming language that combines the best of both OO and functional programming paradigms, making it ideal for a wide range of projects, from web applications to big data processing and machine learning. By mastering Scala, you'll be able to develop more efficient, scalable, and maintainable applications. Fast Track to Scala Programming for OO / Java Developers is a four day hands-on course covers the core principles of Scala, functional programming, web application development, database connectivity, concurrency programming, testing, and interoperability between Scala and Java. Additionally, you'll explore cutting-edge generative AI and GPT technologies, learning how to integrate them into your Scala applications for intelligent suggestions or automation. Throughout the course you?ll explore the latest tools and best practices in the Scala ecosystem, gaining valuable knowledge and experience that can be directly applied to your day-to-day work. With 50% of the course content dedicated to hands-on labs, you'll gain practical experience applying the concepts you've learned across various projects, such as building functional web applications, connecting to databases, designing modular components, and implementing concurrency. Upon completing the course, you'll have a solid understanding of the language and its features, empowering you to confidently apply your new skills in data science and machine learning projects. You'll exit well-prepared to create efficient, scalable, and maintainable Scala applications, regardless of the complexity of your projects. Introduction to Scala Scala features and benefits Comparing Scala with Java and other OO languages Installing Scala and setting up the development environment Object-Oriented Programming in Scala Classes and objects Traits, mixins, and inheritance Companion objects and factories Encapsulation and polymorphism Functional Programming Basics Pure functions and referential transparency Higher-order functions and currying Immutability and persistent data structures Pattern matching and recursion Having Fun with Functional Data Structures Lists, sets, and maps in Scala Folding and reducing operations Stream processing and lazy evaluation For-comprehensions Building Web Applications in Functional Style Introduction to Play Framework Functional web routing and request handling JSON handling with Play-JSON Middleware and functional composition Connecting to a Database Introduction to Slick library Database configuration and setup Querying and updating with Slick Transactions and error handling Building Scalable and Extensible Components Modular architecture and design patterns Dependency injection with MacWire Type classes and type-level programming Implicit parameters and conversions Concurrency Programming & Akka Introduction to Akka framework and Actor model Actor systems and message passing Futures and Promises Supervision and fault tolerance Building Confidence with Testing Introduction to ScalaTest and ScalaCheck Unit testing and property-based testing Test-driven development in Scala Mocking and integration testing Interoperability between Scala and Java Calling Java code from Scala Using Java libraries in Scala projects Converting Java collections to Scala collections Writing Scala code that can be called from Java Using Generative AI and GPT Technologies in Scala Programming Overview of GPT and generative AI Integrating GPT with Scala applications Use cases and practical examples

Data modelling and visualisation skills are in demand! Create Interactive Reports and Dashboards.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies