1582 Improv courses in Cardiff delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This certification is appropriate for anyone interested in becoming familiar with the concepts and practices of Agile Project Delivery, and who wants to have a working knowledge of the various Agile methodologies. Overview Objectives are: To provide an understanding of Agile philosophy and practices To provide a working knowledge of various Agile methodologies To provide students with the ability to compare and choose which methodology is appropriate in a given situation To prepare participants to pass the SAMC™ exam Course outcomes: Participants will be familiar with the concepts and practices of Agile project delivery. Participants will be equipped with detailed knowledge and understanding of available Agile methodologies. Participants will be able to compare and choose the methodologies or parts of methodologies that are most relevant to their current and future situations. Participants will be armed with the proper tools to take the lead in Agile projects and to address and resolve Agile issues in their organizations. Participants will be SAMC certified. Agile relies on adaptive planning and iterative development and delivery. It focuses primarily on the value of people in getting the job done effectively.Successful candidates will be awarded the SCRUMstudy Agile Master Certified (SAMC?) certification by SCRUMstudy after passing the included certification exam. The certification exam voucher is included in this course so you can take the exam at your convenience. IntroductionAgile Overview Agile Defined Why Use Agile? Adaptive Project Management The Agile Manifesto Principles of the Agile Manifesto Declaration of Interdependence Difference between Waterfall and Agile Domains of Agile Practices Value-Driven Delivery Stakeholder Engagement Team Performance Practices Adaptive Planning Problem Detection and Resolution Continuous Improvement Agile Tools and Artifacts Lean Kanban Software Development Introduction Core Values Practices Understanding Lean Software Development Understanding Kanban Software Development Scrum Overview of Scrum Brief History of Scrum Why Use Scrum? Scalability of Scrum Scrum Principles Scrum Aspects Scrum Processes Scrum and Kanban Extreme Programming (XP) Introduction Core Values? Roles Practices XP Artifacts XP Events XP Release Adopting XP Test-Driven Development (TDD) Introduction The Process Dynamic Systems Development Methods (DSDM) Introduction Core Values Roles Practices Crystal Introduction Core Values Roles Practices The Process Feature Driven Development (FDD) Introduction Core Values Roles Practices The Process Comparison of Agile MethodsBest Fit Analysis ToolBlitz PlanningNote SCRUMstudy has authored the SBOK? Guide as a comprehensive guide to deliver successful projects using Scrum. SCRUMstudy works through its large global partner network of Authorized Training Providers (A.T.P.s) to deliver trainings and certifications. New Horizons is a proud Authorized Training Provider of SCRUMstudy. Additional course details: Nexus Humans SCRUMstudy Agile Master Certified (SAMC) 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 SCRUMstudy Agile Master Certified (SAMC) 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 3 Days 18 CPD hours This course is intended for This course is ideal for those who regularly deploy or manage Meraki networks and want to deepen their technical expertise and understanding of the full Meraki product suite and features. This may include professionals with job titles or in roles such as: Consulting Systems Engineer Deployment Engineer Network Administrator Network Manager Network Engineer Site Reliability Engineer Systems Engineer Technical Solutions Architect Wireless Design Engineer Wireless Engineer Overview After completing the course, you should be able to: Plan new Cisco Meraki architectures and expand existing deployments Design the network for scalable management and high availability Describe how to automate and scale Meraki deployments with dashboard tools Use dynamic routing protocols to expand networks and improve WAN performance Describe proper QoS, policy and performance-based routing configurations across a Cisco Meraki network and WAN optimization through traffic shaping Describe Virtual Private Network (VPN) and Wide Area Network (WAN) topologies and how to integrate them Secure, expand, and shape the network Implement switched network concepts and practices, and configure guests networks Implement wireless configurations concepts and practices Describe endpoint management concepts and practices using Cisco Meraki Systems Manager Describe physical security concepts and practices Gain network insight by monitoring applications Describe how to prepare monitoring, logging, and alerting services Set up reporting and auditing capabilities in the Cisco Meraki dashboard Monitor and troubleshoot issues using Cisco Meraki tools The course, Engineering Cisco Meraki Solutions Part 2 (ECMS2) v2.1 elevates your knowledge of Cisco© Meraki? technology suite. In this advanced technical training course, you?ll learn how to plan for network deployments and integrations using the Cisco Meraki platform. Through practical hands-on instruction and experiences, you will learn how to operate Meraki networks and troubleshoot complex network incidents using the Meraki Dashboard and analytics. You will also learn how to design Meraki architectures for redundancy, high-density, and scalability by implementing comprehensive Meraki product features to meet design objectives. This course is the second of two courses that prepares you for Cisco Meraki certification. Course Outline Planning new Cisco Meraki architectures and expanding existing deployments Designing for scalable management and high availability Automating and scaling Meraki deployments Designing routing and practices on the Meraki platform Describing Quality of Service (QoS) and traffic shaping design Building VPN and WAN topologies Securing, expanding, and shaping the network Describing network concepts and practices Implementing wireless configuration practices and concepts Describing Endpoint management concepts and practices Describing physical security concepts and practices Gaining network insight through monitoring applications Preparing monitoring, logging, and alerting services Setting up reporting and auditing capabilities in the Cisco Meraki Dashboard Gaining visibility and resolving issues using Meraki features and built-in troubleshooting tools Additional course details: Nexus Humans Cisco Engineering Cisco Meraki Solutions Part 2 (ECMS2) v2.1 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 Cisco Engineering Cisco Meraki Solutions Part 2 (ECMS2) v2.1 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 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 3 Days 18 CPD hours This course is intended for This class is intended for the following participants: Cloud architects, administrators, and SysOps/DevOps personnel Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform. Overview This course teaches participants the following skills: Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Platform Understand how pod networking works in Kubernetes Engine Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/ kubectl commands Launch, roll back and expose jobs in Kubernetes Manage access control using Kubernetes RBAC and Google Cloud IAM Managing pod security policies and network policies Using Secrets and ConfigMaps to isolate security credentials and configuration artifacts Understand GCP choices for managed storage services Monitor applications running in Kubernetes Engine This class introduces participants to deploying and managing containerized applications on Google Kubernetes Engine (GKE) and the other services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as pods, containers, deployments, and services; as well as networks and application services. This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring. Introduction to Google Cloud Platform Use the Google Cloud Platform Console Use Cloud Shell Define cloud computing Identify GCPs compute services Understand regions and zones Understand the cloud resource hierarchy Administer your GCP resources Containers and Kubernetes in GCP Create a container using Cloud Build Store a container in Container Registry Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE) Understand how to choose among GCP compute platforms Kubernetes Architecture Understand the architecture of Kubernetes: pods, namespaces Understand the control-plane components of Kubernetes Create container images using Google Cloud Build Store container images in Google Container Registry Create a Kubernetes Engine cluster Kubernetes Operations Work with the kubectl command Inspect the cluster and Pods View a Pods console output Sign in to a Pod interactively Deployments, Jobs, and Scaling Create and use Deployments Create and run Jobs and CronJobs Scale clusters manually and automatically Configure Node and Pod affinity Get software into your cluster with Helm charts and Kubernetes Marketplace GKE Networking Create Services to expose applications that are running within Pods Use load balancers to expose Services to external clients Create Ingress resources for HTTP(S) load balancing Leverage container-native load balancing to improve Pod load balancing Define Kubernetes network policies to allow and block traffic to pods Persistent Data and Storage Use Secrets to isolate security credentials Use ConfigMaps to isolate configuration artifacts Push out and roll back updates to Secrets and ConfigMaps Configure Persistent Storage Volumes for Kubernetes Pods Use StatefulSets to ensure that claims on persistent storage volumes persist across restarts Access Control and Security in Kubernetes and Kubernetes Engine Understand Kubernetes authentication and authorization Define Kubernetes RBAC roles and role bindings for accessing resources in namespaces Define Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources Define Kubernetes pod security policies Understand the structure of GCP IAM Define IAM roles and policies for Kubernetes Engine cluster administration Logging and Monitoring Use Stackdriver to monitor and manage availability and performance Locate and inspect Kubernetes logs Create probes for wellness checks on live applications Using GCP Managed Storage Services from Kubernetes Applications Understand pros and cons for using a managed storage service versus self-managed containerized storage Enable applications running in GKE to access GCP storage services Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and Bigquery from within a Kubernetes application

Duration 3 Days 18 CPD hours This course is intended for The target audience for the DevSecOps Practitioner course are professionals including: Anyone focused on implementing or improving DevSecOps practices in their organization Anyone interested in modern IT leadership and organizational change approaches Business Managers Business Stakeholders Change Agents Consultants DevOps Practitioners IT Directors IT Managers IT Team Leaders Product Owners Scrum Masters Software Engineers Site Reliability Engineers System Integrators Tool Providers Overview After completing this course, students will be able to: Comprehend the underlying principles of DevSecOps Distinguish between the technical elements used across DevSecOps practices Demonstrate how practical maturity concepts can be extended across multiple areas. Implement metric-based assessments tied to your organization. Recognize modern architectural concepts including microservice to monolith transitions. Recognize the various languages and tools used to communicate architectural concepts. Contrast the options used to build a DevSecOps infrastructure through Platform as a Service, Server-less construction, and event-driven mediums Prepare hiring practices to recognize and understand the individual knowledge, skills, and abilities required for mature Dev Identify the various technical requirements tied to the DevSecOps pipelines and how those impact people and process choices. Review various approaches to securing data repositories and pipelines. Analyze how monitoring and observability practices contribute to valuable outcomes. Comprehend how to implement monitoring at key points to contribute to actionable analysis. Evaluate how different experimental structures contribute to the 3rd Way. Identify future trends that may affect DevSecOps The DevSecOps Practitioner course is intended as a follow-on to the DevSecOps Foundation course. The course builds on previous understanding to dive into the technical implementation. The course aims to equip participants with the practices, methods, and tools to engage people across the organization involved in reliability through the use of real-life scenarios and case stories. Upon completion of the course, participants will have tangible takeaways to leverage when back in the office such as implementing DevSecOps practices to their organizational structure, building better pipelines in distributed systems, and having a common technological language. This course positions learners to successfully complete the DevSecOps Practitioner certification exam. DevSecOps Advanced Basics Why Advance Practices? General Awareness People-Finding Them Core Process Technology Overview Understanding Applied Metrics Metric Terms Accelerating People-Reporting and Recording Integrating Process Technology Automation Architecting and Planning for DevSecOps Architecture Basics Finding an Architect Reporting and Recording Environments Process Accelerating Decisions Creating a DevSecOps Infrastructure What is Infrastructure? Equipping the Team Design Challenges Monitoring Infrastructure Establishing a Pipeline Pipelines and Workflows Engineers and Capabilities Continuous Engagement Automate and Identify Observing DevSecOps Outcomes Observability vs. Monitoring Who gets which Report? Setting Observation Points Implementing Observability Practical 3rd Way Applications Revisiting 3rd Way Building Experiments Getting the Most from the Experiment The Future of DevOps Looking Towards the Future Staying Trained Innovation What, and from Who? Post-Class Assignments/Exercises Extended advanced reading associated with Case Stories from the course Additional course details: Nexus Humans DevSecOps Practitioner (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 DevSecOps Practitioner (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 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 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.This skills-focused ccombines 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. 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 Applied AI: 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 Applied AI: 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.

Duration 2 Days 12 CPD hours Overview This skills-focused course combines expert instructor-led discussions with practical hands-on labs that emphasize useful, current techniques, best practices and standards. Working in this hands-on lab environment, guided by our expert practitioner, you'll learn about and explore: Review of the File System Introduction to Shells: sh, bash, and ksh Shell Programming Advanced Shell Features Text Manipulation Utilities File Processing Utilities Multitasking and Batch Processing Regular Expressions Intermediate Linux: Shell, Bash, Text Manipulation, Multitasking & More is a two-day course designed to provide you with hands on experience using standard Linux commands and utilities used for day-to-day tasks including file manipulation, program execution and control, and effective use of the shell and desktop environments. Throughout the course you?ll explore key concepts to Linux core functionality, while learning the system's most commonly used commands. You?ll also learn the Bourne shell, Bash shell and Korn shell programming techniques you?ll need to read and modify existing shell scripts, and create your own. Data manipulation utilities and shell syntax for synthesizing command pipelines are also emphasized throughout the course. Review of the File System File System Organization File Types File and Directory Naming Rules and Conventions Commands for Navigating the File System Introduction to Inodes Ownership, Permissions, and Dates Manipulating Files and Links Manipulating Directories Determining Disk Usage Other File System Utilities Introduction to Shells: sh, bash, and ksh Shell Functions I/O Redirection and Pipes Command Separation and Grouping Background Execution Filename Expansion Shell Variables Command Substitution Quoting and Escaping Metacharacters Bash Shell Features Korn Shell Features Command Execution Startup Files Customizing the User Environment Shell Programming Shell Script Features and Capabilities Creating and Running a Script Working With Variables Environment Variables Working With Data Types Formatting Base Conversion Setting Special Attributes Input/Output Techniques Conditional Constructs if/then else/elif Looping Constructs for, while, until Math Operators Advanced Shell Features Manipulating Strings Writing and Calling Functions Controlling Process Priorities Interpreting Command Line Arguments Making Scripts Interactive Special Shell Variables Advanced I/O with Streams Improving Performance of Scripts Text Manipulation Utilities Editing a File from a Script Scripting with ed or sed UNIX and Linux Utilities to Manipulate Files Regular Expressions grep and egrep The Stream Editor sed Sorting in Scripts Generating Reports with awk Splitting Large Files Counting Words, Lines, and Characters Transforming File Contents File Processing Utilities Examining and Comparing Files Reporting Differences Between Files Comparing Files of Any Format Displaying Data in Octal and Hex Compressing Data Converting File Formats Extracting Text Strings Multitasking and Batch Processing Multitasking Scheduled Execution Using cron The at and batch Commands Regular Expressions Regular Expression Overview Regular Expression Implementations Regular Expressions RE Character Classes Regex Quantifiers RE Parenthesis Additional course details: Nexus Humans Intermediate Linux (TTLX2104) 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 Intermediate Linux (TTLX2104) 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 2 Days 12 CPD hours This course is intended for Data Protection Officers Data Protection Managers Auditors Legal Compliance Officers Security Manager Information Managers Anyone involved with data protection processes and programs Overview It will show the world that students know privacy laws and regulations and how to apply them, and that students know how to secure your place in the information economy. When students earn a CIPP credential, it means they've gained a foundational understanding of broad global concepts of privacy and data protection law and practice, including: jurisdictional laws, regulations and enforcement models; essential privacy concepts and principals; legal requirements for handling and transferring data and more. The Certified Information Privacy Professional/United States (CIPP/US) program, developed by the International Association of Privacy Professionals (IAPP) - the world?s largest comprehensive global information privacy community and resource, was the first professional certification ever to be offered in information privacy. The CIPP/US credential demonstrates a strong foundation in U.S. privacy laws and regulations and understanding of the legal requirements for the responsible transfer of sensitive personal data to/from the U.S., the EU and other jurisdictions.This course will provide you with a foundational understanding of broad global concepts of privacy and data protection law and practice, including: jurisdictional laws, regulations and enforcement models; essential privacy concepts and principals; legal requirements for handling and transferring data and more. Introduction to privacy Modern history of privacy Introduction to personal information Overview of data protection roles Summary of modern privacy frameworks Structure of U.S. law Structure and sources of U.S. law and relevant terms Governmental bodies having privacy and information security authority General Data Protection Regulation overview (GDPR) High-level overview of the GDPR Significance of the GDPR to U.S. organizations Roles and responsibilities outlined in the law California Consumer Privacy Act of 2018 (CCPA) High-level overview of the newly passed California Consumer Privacy Act of 2018 Scope Consumer rights Business obligations Enforcement Enforcement of U.S. privacy and security laws Distinguishing between criminal and civil liability Comparing federal and state authority Theories of legal liability Enforcement powers and responsibilities of government bodies, such as the FTC and state attorneys general Information management from a U.S. perspective Developing a privacy program Role of privacy professionals and accountability Employee training User preferences Managing vendors Data classification Federal versus state authority Differences between federal and state authority Preemption Healthcare Privacy laws in healthcare Major components of HIPAA Development of HITECH Privacy protections mandated by other significant healthcare laws Financial privacy Goals of financial privacy laws Key concepts of FCRA, FACTA and GLBA Red Flags Rule, Dodd-Frank and consumer protection laws Education Privacy rights and protections under FERPA Recent amendments provided by PPRA and NCLBA Telecommunications and marketing Rules and regulations of telecommunications entities Laws that govern marketing Addressing privacy in the digital advertising Law enforcement and privacy Privacy laws on intercepting communication Telecommunications industry and law enforcement Laws ensuring rights to financial privacy National security and privacy Rules and regulations on intercepting communication Evolution of the law Collaboration of government agencies and private companies to improve cybersecurity Civil litigation and privacy Privacy issues related to litigation Electronic discovery, redaction and protective orders U.S. discovery rules versus foreign laws Legal overview of workplace privacy Federal and state laws regulating and protecting employee privacy Federal laws prohibiting discrimination Privacy before, during and after employment Lifecycle of employee privacy Background screening Employee monitoring Investigating misconduct and termination Antidiscrimination laws ?Bring your own device? policies State data security laws State laws impacting data security Social Security number use regulation Laws governing data destruction Data breach notification laws Scope of state data breach notification law Nine elements of state data breach notification laws Major differences in state laws

Duration 5 Days 30 CPD hours This course is intended for This is a basic-level programming course designed for attendees with prior development experience in another language, such as COBOL, 4GL, Mainframe or other non-object oriented languages. This course is not geared for non-developers. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core OO coding and Java development skills, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working within in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand what OO programming is and what the advantages of OO are in today's world Work with objects, classes, and OO implementations Understand the basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction Understand not only the fundamentals of the Java language, but also its importance, uses, strengths and weaknesses Understand the basics of the Java language and how it relates to OO programming and the Object Model Work with the Modular system (Project Jigsaw) Understand and use classes, inheritance and polymorphism Understand and use collections, generics, autoboxing, and enumerations Process large amount of data using Lambda expressions and the Stream API Abstract, static and private methods in interfaces Take advantage of the Java tooling that is available with the programming environment being used in the class Java 11 features covered: Using the Local Variable Type in Lambda expressions; Updates made to the String API This course provides hands-on Java 11 training for developers who have little or no prior working knowledge of object-oriented programming languages such as C, COBOL, and 4GL. You will learn the best practices for writing great object-oriented programs in Java 11, using sound development techniques, new improved features for better performance, and new capabilities for addressing rapid application development. Special emphasis is placed on object oriented concepts and best practices. A First Look The Java Platform Using the JDK The Eclipse Paradigm Getting Started with Java Writing a Simple Class Adding Methods to the Class OO Concepts Object-Oriented Programming Inheritance, Abstraction, and Polymorphism Essential Java Programming Language Statements Using Strings Specializing in a Subclass Fields and Variables Using Arrays Local-Variable Type Inference Java Packages and Visibility Object Oriented Development Inheritance and Polymorphism Interfaces and Abstract Classes Introduction to Exception Handling Exceptions Java Developer's Toolboxÿ Utility Classes Java Date/Time Advanced Java Programming Introduction to Generics Lambda Expressions and Functional Interface Working with Collections Collections Using Collections Stream APIÿ Streams Collectors The Java Module System Introduction to the Module System Time Permitting Formatting Strings Introduction to Annotations Java 12 and beyond Additional course details: Nexus Humans Basic Java 11 and OO Programming for Developers New to OO (TT2120-J11) 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 Basic Java 11 and OO Programming for Developers New to OO (TT2120-J11) 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 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