1229 Systems courses delivered Live Online

For new users and the curious. Hello, For new users and the curious. IMPORTANT: Firstly, once you are signed up, send us your requests on what you would like to see within the demonstration and learn on the course. We will then cater for your needs and answer them during the session. This is designed to be an introduction into how to start a room by room survey using the Heat Engineer app, then sending this survey to the online dashboard. We will then go through the different steps to complete this heat loss report. Optional pages will also be worked through and shown. Examples of how to select the flow temperature and the heat source (heat pumps and boilers) will be presented once the heat loss result is completed.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for network and software engineers who hold the following job roles: Network engineer Systems engineer Wireless engineer Consulting systems engineer Technical solutions architect Network administrator Wireless design engineer Network manager Site reliability engineer Deployment engineer Sales engineer Account manager Overview After taking this course, you should be able to: Leverage the tools and APIs to automate Cisco ACI powered data centers. Demonstrate workflows (configuration, verification, healthchecking, monitoring) using Python, Ansible, and Postman. Leverage the various models and APIs of the Cisco Nexus OS platform to perform day 0 operations, improve troubleshooting methodologies with custom tools, augment the CLI using scripts, and integrate various workflows using Ansible and Python. Describe the paradigm shift of Model Driven Telemetry and understand the building blocks of a working solution. Describe how the Cisco Data Center compute solutions can be managed and automated using API centric tooling, by using the Python SDK, PowerTool, and Ansible modules to implement various workflows on Cisco UCS, Cisco IMC, Cisco UCS Manager, Cisco UCS Director, and Cisco Intersight. The Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.1 course teaches you how to implement Cisco© Data Center automated solutions including programming concepts, orchestration, and automation tools. Through a combination of lessons and hands-on practice, you will manage the tools and learn the benefits of programmability and automation in the Cisco-powered Data Center. You will examine Cisco Application Centric Infrastructure (Cisco ACI©), Software-Defined Networking (SDN) for data center and cloud networks, Cisco Nexus© (Cisco NX-OS) platforms for device-centric automation, and Cisco Unified Computing System (Cisco UCS©) for Data Center compute. You will study their current ecosystem of Application Programming Interfaces (APIs), software development toolkits, and relevant workflows along with open industry standards, tools, and APIs, such as Python, Ansible, Git, JavaScript Object Notation (JSON), Yaml Ain't Markup Language (YAML), Network Configuration Protocol (NETCONF), Representational State Transfer Configuration Protocol (RESTCONF), and Yet Another Generation (YANG).This course prepares you for the 300-635 Automating Cisco Data Center Solutions (DCAUTO) certification exam. Introducing Automation for Cisco Solutions (CSAU) is required prior to enrolling in Implementing Automation for Cisco Data Center Solutions (DCAUI) because it provides crucial foundational knowledge essential to success. This course also earns you 24 Continuing Education (CE) credits towards recertification. Course Outline Describing the Cisco ACI Policy Model Describing the Cisco APIC REST API Using Python to Interact with the ACI REST API Using Ansible to Automate Cisco ACI Introducing Cisco NX-OS Programmability Describing Day-Zero Provisioning with Cisco NX-OS Implementing On-Box Programmability and Automation with Cisco NX-OS Implementing Off-Box Programmability and Automation with Cisco NX-OS Automating Cisco UCS Using Developer Tools Implementing Workflows Using Cisco UCS Director Describing Cisco DCNM Describing Cisco Intersight Additional course details: Nexus Humans Cisco Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.1 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 Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.1 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 5 Days 30 CPD hours This course is intended for To fully benefit from this course, you should have three to five years of experience designing and implementing applications that are built on top of Cisco platforms. This course is appropriate for: Network engineers expanding their skill-base to include software and automation Developers expanding expertise in automation and DevOps Solution architects moving to the Cisco ecosystem Infrastructure developers designing hardened production environments The job roles best suited to the material in this course are: Senior network automation engineer Senior software developer Senior system integration programmer Additional job roles that could find this course useful are: Senior infrastructure architect Senior network designer Senior test development engineer Students preparing for Cisco Certified DevNet Professional and Cisco Certified DevNet Specialist - Core certification will also find this material useful. Overview After taking this course, you should be able to: Describe the architectural traits and patterns that improve application maintainability Describe the architectural traits and patterns that improve application serviceability Identify steps to design and build a ChatOps application Implement robust Representational State Transfer (REST) API integrations with network error handling, pagination, and error flow control Describe the necessary steps for securing user and system data in applications Describe the necessary steps for securing applications Identify common tasks in automated application release process Describe best practices for application deployment Describe methodologies for designing distributed systems Describe the concepts of infrastructure configuration management and device automation Utilize Yet Another Next Generation (YANG) data models to describe network configurations and telemetry Compare various relational and nonrelational database types and how to select the appropriate type based on requirements In this course, you will learn how to implement network applications using Cisco© platforms as a base, from initial software design to diverse system integration, as well as testing and deployment automation. The course gives you hands-on experience solving real world problems using Cisco Application Programming Interfaces (APIs) and modern development tools. This course helps you prepare for Cisco DevNet Professional certification and for professional-level network automation engineer roles. COURSE OUTLINE DESIGNING FOR MAINTAINABILITY (SELF-STUDY) DESIGNING FOR SERVICEABILITY (SELF-STUDY) IMPLEMENTING CHATOPS APPLICATION DESCRIBING ADVANCED REST API INTEGRATION SECURING APPLICATION DATA (SELF-STUDY) SECURING WEB AND MOBILE APPLICATIONS (SELF-STUDY) AUTOMATING APPLICATION-RELEASE DEPLOYING APPLICATIONS UNDERSTANDING DISTRIBUTED SYSTEMS ORCHESTRATING NETWORK AND INFRASTRUCTURE MODELING DATA WITH YANG USING RELATIONAL AND NON-RELATIONAL DATABASES (SELF-STUDY) PLEASE NOTE:This class includes lecture sections and self-study sections. In instructor-led classes, lectures are delivered in real-time, either in person or via video conferencing. In e-learning courses, the lectures are on recorded videos. In both versions, you will need to review self-study sections on your own before taking the certification exam. Additional course details: Nexus Humans Cisco Developing Applications Using Cisco Core Platforms and APIs v1.0 (DEVCOR) 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 Developing Applications Using Cisco Core Platforms and APIs v1.0 (DEVCOR) 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 for Network, IT security, and systems administration professionals in a Security Operations position who are tasked with configuring optimum security settings for endpoints protected by Symantec Endpoint Protection 14. Overview At the completion of the course, you will be able to: Protect against Network Attacks and Enforcing Corporate Policies using the Firewall Policy. Blocking Threats with Intrusion Prevention. Introducing File-Based Threats. Preventing Attacks with SEP. Layered Security. Securing Windows Clients. Secure Mac Clients. Secure Linux Clients. Controlling Application and File Access. Restricting Device Access for Windows and Mac Clients. Hardening Clients with System Lockdown. Customizing Policies based on Location. Managing Security Exceptions. This course is designed for the network, IT security, and systems administration professionals in a Security Operations position who are tasked with configuring optimum security settings for endpoints protected by Symantec Endpoint Protection 14. Introduction Course environment Lab environment Introducing Network Threats Describing how Symantec Endpoint Protection protects each layer of the network stack Discovering the tools and methods used by attackers Describing the stages of an attack Protecting against Network Attacks and Enforcing Corporate Policies using the Firewall Policy Preventing network attacks Examining Firewall Policy elements Evaluating built-in rules Creating custom firewall rules Enforcing corporate security policy with firewall rules Blocking network attacks using protection and stealth settings Configuring advanced firewall feature Blocking Threats with Intrusion Prevention Introducing Intrusion Prevention technologies Configuring the Intrusion Prevention policy Managing custom signatures Monitoring Intrusion Prevention events Introducing File-Based Threats Describing threat types Discovering how attackers disguise their malicious applications Describing threat vectors Describing Advanced Persistent Threats and a typical attack scenario Following security best practices to reduce risks Preventing Attacks with SEP Layered Security Virus and Spyware protection needs and solutions Describing how Symantec Endpoint Protection protects each layer of the network stack Examining file reputation scoring Describing how SEP protects against zero-day threats and threats downloaded through files and email Describing how endpoints are protected with the Intelligent Threat Cloud Service Describing how the emulator executes a file in a sandbox and the machine learning engine?s role and function Securing Windows Clients Platform and Virus and Spyware Protection policy overview Tailoring scans to meet an environment?s needs Ensuring real-time protection for clients Detecting and remediating risks in downloaded files Identifying zero-day and unknown threats Preventing email from downloading malware Configuring advanced options Monitoring virus and spyware activity Securing Mac Clients Touring the SEP for Mac client Securing Mac clients Monitoring Mac clients Securing Linux Clients Navigating the Linux client Tailoring Virus and Spyware settings for Linux clients Monitoring Linux clients Providing Granular Control with Host Integrity Ensuring client compliance with Host Integrity Configuring Host Integrity Troubleshooting Host Integrity Monitoring Host Integrity Controlling Application and File Access Describing Application Control and concepts Creating application rulesets to restrict how applications run Monitoring Application Control events Restricting Device Access for Windows and Mac Clients Describing Device Control features and concepts for Windows and Mac clients Enforcing access to hardware using Device Control Discovering hardware access policy violations with reports, logs, and notifications Hardening Clients with System Lockdown What is System Lockdown? Determining to use System Lockdown in Whitelist or Blacklist mode Creating whitelists for blacklists Protecting clients by testing and Implementing System Lockdown Customizing Policies based on Location Creating locations to ensure the appropriate level of security when logging on remotely Determining the criteria and order of assessment before assigning policies Assigning policies to locations Monitoring locations on the SEPM and SEP client Managing Security Exceptions Creating file and folder exceptions for different scan types Describing the automatic exclusion created during installation Managing Windows and Mac exclusions Monitoring security exceptions

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

Duration 3 Days 18 CPD hours This course is intended for This lecture and exercise-based course is for individuals who want to understand how to install, configure, and manage an IBM Spectrum Scale storage cluster. Overview After completing this course, you should be able to: Summarize the key features of IBM Spectrum Scale Describe IBM ESS and Spectrum Scale RAID Install IBM Spectrum Scale and configure a cluster Manage a cluster Implement information lifecycle management (ILM) Configure IBM Spectrum Scale high availability features Back up critical cluster data This course is intended for IT professionals tasked with administering an IBM Spectrum Scale storage cluster in environments running Linux and AIX nodes. The course includes information on installing, configuring, and monitoring an IBM Spectrum Scale cluster. Many Spectrum Scale features are described in lecture materials and then implemented in lab exercises. These features include: Storage management, high availability options, cluster management, and information lifecycle management (ILM) tools. Note: Although the lab environment is running the Linux operating system, the differences in Spectrum Scale compared with an AIX environment are minor. Therefore, the skills acquired during the course can be applied in both Linux and AIX environments. Welcome and course overview Unit 1 - IBM Spectrum Scale overview Exercise 1 - Cluster node preparation Unit 2 - Installation and cluster configuration Exercise 2 - Installation and cluster configuration Unit 3 - Cluster management Exercise 3 - Cluster management and configuration Unit 4 - Information Lifecycle Management (ILM) Exercise 4 - Storage pools, filesets, and policies Unit 5 - High availability and cluster data backups Exercise 5 - Replication and snapshots Course wrap-up and evaluation

Duration 2 Days 12 CPD hours This course is intended for The target audience for the DevSecOps Foundation course are professionals including: Anyone involved or interested in learning about DevSecOps strategies and automation Anyone involved in Continuous Delivery toolchain architectures Compliance Team Business managers Delivery Staff DevOps Engineers IT Managers IT Security Professionals, Practitioners, and Managers Maintenance and support staff Managed Service Providers Project & Product Managers Quality Assurance Teams Release Managers Scrum Masters Site Reliability Engineers Software Engineers Testers Overview You will learn: The purpose, benefits, concepts, and vocabulary of DevSecOps How DevOps security practices differ from other security approaches Business-driven security strategies and Best Practices Understanding and applying data and security sciences Integrating corporate stakeholders into DevSecOps Practices Enhancing communication between Dev, Sec, and Ops teams How DevSecOps roles fit with a DevOps culture and organization In this course, students will gain a solid understanding of how DevSecOps provides business value, enhancing your business opportunities, and improving corporate value. The core DevSecOps principles taught can support an organizational transformation, increase productivity, reduce risk, and optimize resource usage. This course explains how DevOps security practices differ from other approaches then delivers the education needed to apply changes to your organization. Participants learn the purpose, benefits, concepts, vocabulary and applications of DevSecOps. Most importantly, students learn how DevSecOps roles fit with a DevOps culture and organization. At the course?s end, participants will understand ?security as code? to make security and compliance value consumable as a service. This course prepares you for the DevSecOps Foundation (DSOF) certification. Realizing DevSecOps Outcomes Origins of DevOps Evolution of DevSecOps CALMS The Three Ways Defining the Cyberthreat Landscape What is the Cyber Threat Landscape? What is the threat? What do we protect from? What do we protect, and why? How do I talk to security? Building a Responsive DevSecOps Model Demonstrate Model Technical, business and human outcomes What?s being measured? Gating and thresholding Integrating DevSecOps Stakeholders The DevSecOps State of Mind The DevSecOps Stakeholders What?s at stake for who? Participating in the DevSecOps model Establishing DevSecOps Best Practices Start where you are Integrating people, process and technology and governance DevSecOps operating model Communication practices and boundaries Focusing on outcomes Best Practices to get Started The Three Ways Identifying target states Value stream-centric thinking DevOps Pipelines and Continuous Compliance The goal of a DevOps pipeline Why continuous compliance is important Archetypes and reference architectures Coordinating DevOps Pipeline construction DevSecOps tool categories, types and examples Learning Using Outcomes Security Training Options Training as Policy Experiential Learning Cross-Skilling The DevSecOps Collective Body of Knowledge Preparing for the DevSecOps Foundation certification exam Additional course details: Nexus Humans DevSecOps 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 DevSecOps 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 3 Days 18 CPD hours This course is intended for Cloud Solutions Architects, DevOps Engineers. Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with a focus on Google Compute Engine. Overview Configure VPC networks and virtual machines Administer Identity and Access Management for resources Implement data storage services in GCP Manage and examine billing of GCP resources Monitor resources using Stackdriver services Connect your infrastructure to GCP Configure load balancers and autoscaling for VM instances Automate the deployment of GCP infrastructure services Leverage managed services in GCP This class introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform, with a focus on Compute Engine. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems, and application services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring. Introduction to Google Cloud Platform List the different ways of interacting with GCP Use the GCP Console and Cloud Shell Create Cloud Storage buckets Use the GCP Marketplace to deploy solutions Virtual Networks List the VPC objects in GCP Differentiate between the different types of VPC networks Implement VPC networks and firewall rules Design a maintenance server Virtual Machines Recall the CPU and memory options for virtual machines Describe the disk options for virtual machines Explain VM pricing and discounts Use Compute Engine to create and customize VM instances Cloud IAM Describe the Cloud IAM resource hierarchy Explain the different types of IAM roles Recall the different types of IAM members Implement access control for resources using Cloud IAM Storage and Database Services Differentiate between Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Firestore and Cloud Bigtable Choose a data storage service based on your requirements Implement data storage services Resource Management Describe the cloud resource manager hierarchy Recognize how quotas protect GCP customers Use labels to organize resources Explain the behavior of budget alerts in GCP Examine billing data with BigQuery Resource Monitoring Describe the Stackdriver services for monitoring, logging, error reporting, tracing, and debugging Create charts, alerts, and uptime checks for resources with Stackdriver Monitoring Use Stackdriver Debugger to identify and fix errors Interconnecting Networks Recall the GCP interconnect and peering services available to connect your infrastructure to GCP Determine which GCP interconnect or peering service to use in specific circumstances Create and configure VPN gateways Recall when to use Shared VPC and when to use VPC Network Peering Load Balancing and Autoscaling Recall the various load balancing services Determine which GCP load balancer to use in specific circumstances Describe autoscaling behavior Configure load balancers and autoscaling Infrastructure Automation Automate the deployment of GCP services using Deployment Manager or Terraform Outline the GCP Marketplace Managed Services Describe the managed services for data processing in GCP Additional course details: Nexus Humans Architecting with Google Compute Engine 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 Architecting with Google Compute Engine 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

A high-impact programme designed to be fun and to get people fully involved. The first-class, jargon-free content is based on what people need to know in practice, not off-putting legal language. This introductory course covers: Introducing Working Safely: Accidents can happen to anyone. The realities of the human suffering behind the statistics. The importance of personal responsibility. Defining hazard and risk: Focusing on the six broad hazard groups, participants are asked to think about the hazards and risks they come across in their own work. 'Risk assessment' demystified. Identifying common hazards: All the main issues - aggression and violence, asbestos, bullying, chemicals and harmful substances, computer workstations, confined spaces, drugs and alcohol, electricity, fire, getting in and out, height, housekeeping, lighting, manual handling, noise, personal hygiene, plant and machinery, slips and trips, stress, temperature, vehicles and transport, and welfare facilities. Improving safety performance: Bridging the gap between management and workforce, encouraging participants to play their part. Also covered: contract work, inspections, safe systems and permits, protective equipment, signage, emergency procedures, reporting and health checks.