5655 Computing & IT courses in Cowdenbeath delivered Online

Duration 3 Days 18 CPD hours This course is intended for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary. Overview By the end of this course, you will be able to build your own marketing reporting and interactive dashboard solutions. The course starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation.As you make your way through the course, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding sections, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. Data Preparation and Cleaning Data Models and Structured Data pandas Data Manipulation Data Exploration and Visualization Identifying the Right Attributes Generating Targeted Insights Visualizing Data Unsupervised Learning: Customer Segmentation Customer Segmentation Methods Similarity and Data Standardization k-means Clustering Choosing the Best Segmentation Approach Choosing the Number of Clusters Different Methods of Clustering Evaluating Clustering Predicting Customer Revenue Using Linear Regression Understanding Regression Feature Engineering for Regression Performing and Interpreting Linear Regression Other Regression Techniques and Tools for Evaluation Evaluating the Accuracy of a Regression Model Using Regularization for Feature Selection Tree-Based Regression Models Supervised Learning: Predicting Customer Churn Classification Problems Understanding Logistic Regression Creating a Data Science Pipeline Fine-Tuning Classification Algorithms Support Vector Machine Decision Trees Random Forest Preprocessing Data for Machine Learning Models Model Evaluation Performance Metrics Modeling Customer Choice Understanding Multiclass Classification Class Imbalanced Data Additional course details: Nexus Humans Data Science for Marketing Analytics 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 Data Science for Marketing Analytics 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 technical professionals to gain skills in writing rules for Snort-based Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS). The primary audience includes: Security administrators Security consultants Network administrators System engineers Technical support personnel using open source IDS and IPS Channel partners and resellers Overview After taking this course, you should be able to: Describe the Snort rule development process Describe the Snort basic rule syntax and usage Describe how traffic is processed by Snort Describe several advanced rule options used by Snort Describe OpenAppID features and functionality Describe how to monitor the performance of Snort and how to tune rules The Securing Cisco Networks with Snort Rule Writing Best Practices (SSFRules) v2.1 course shows you how to write rules for Snort, an open-source intrusion detection and prevention system. Through a combination of expert-instruction and hands-on practice, this course provides you with the knowledge and skills to develop and test custom rules, standard and advanced rules-writing techniques, how to integrate OpenAppID into rules, rules filtering, rules tuning, and more. The hands-on labs give you practice in creating and testing Snort rules. Course Outline Introduction to Snort Rule Development Snort Rule Syntax and Usage Traffic Flow Through Snort Rules Advanced Rule Options OpenAppID Detection Tuning Snort

Duration 2 Days 12 CPD hours This course is intended for Software Test Engineers and Test Leaders with minimum two years of experience. Specialists who have experience in software testing and want to deepen both their theoretical and practical knowledge. Overview Please refer to Overview. Practical training that you will learn how to apply additional tools in your work which will help you to optimize it. You will be able to analyze requirements better and to prioritize your tasks. Requirements analysis Effective approaches in requirements analyze What does 'Good Requirement' mean? Change Management Subsystems and actors Practice - Analysis of an actual functional specification Applicable Models and Priorities Specifications of the extraordinary models software projects Prioritizing the tasks of the test team Practice case - Iteration and sprint specifications Test planning Test design approaches Applicable techniques Practice cases with different techniques Defects management Defect status management Applicable metrics Best practices Practical examples of extraordinary applications Additional course details: Nexus Humans Modern approaches and practical tips in software testing 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 Modern approaches and practical tips in software testing 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 advanced course is for IT professionals tasked with administering a Spectrum Scale system. Overview Please see Overview This course is intended for IT professionals tasked with administering a Spectrum Scale system. It includes information on installing, configuring and monitoring a Spectrum Scale cluster. Migrating to IBM Spectrum Scale 4.2Spectrum Scale 4.2 GUIMulti-clusterClustered NFSCluster Export Services for multi-protocol supportSMB Protocol SupportNFS Support in CES; Ganesha overview/performanceActive File ManagementAFM-Based Disaster Recovery (DR) and Asynchronous DRPlanning LTFS and GPFS environment for data archivingFile Placement OptimizerIBM© GPFS-FPO and integration with GPFS Hadoop connectorIBM© Spectrum Scale Call HomeMonitoring and performance tuningFlash Cache metadata migration

Duration 3 Days 18 CPD hours This course is intended for Information System Owners Analysts Ethical Hackers ISSOs Cyber Security Managers IT Engineers Overview Upon completion, the Certified Vulnerability Assessor candidate will be able to competently take the exam. This course provides a solid understanding of the tools an IT engineer needs to review an Information System. In this course, you will learn the importance of vulnerability assessments and how they are used to prevent serious cyber break-ins. Lessons include understanding malware and viruses and how they can infiltrate an organization?s network. After you take this course, you will be able to assess a company?s security posture and perform a basic vulnerability test.ÿPlus, you will be able to generate reports to guide new security implementation. Course Outline Why Vulnerability Assessment Vulnerability Types Assessing the Network Assessing Web Servers and Applications Assessing Remote and VPN Services Vulnerability Assessments & Tools of the Trade Output Analysis

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

Emotional Intelligence and Artificial Intelligence for Business Manager Boost your leadership with Emotional Intelligence. Integrate Artificial Intelligence for strategic advantage. Excel as a Business Manager with a balanced mastery of Emotional Intelligence and AI. Learning Outcomes: Explain the role of Emotional Intelligence in business management. Assess your Emotional Intelligence and Self-Awareness. Cultivate relationships using Emotional Intelligence techniques. Evaluate the impact of Artificial Intelligence on business processes. Innovate business models using Artificial Intelligence insights. More Benefits: LIFETIME access Device Compatibility Free Workplace Management Toolkit Key Modules from Emotional Intelligence and Artificial Intelligence for Business Manager: Introduction to Emotional Intelligence: Understand the fundamentals and significance of Emotional Intelligence in managerial roles. Emotional Intelligence Self-Awareness: Gauge and improve your self-awareness using Emotional Intelligence tools. Relationships in Emotional Intelligence: Build and manage professional relationships through Emotional Intelligence. Artificial Intelligence for Business: Learn how Artificial Intelligence can reshape traditional business paradigms. Artificial Intelligence on Business Models: Reconfigure your business models effectively using Artificial Intelligence. Creativity and Innovation on AI: Harness the power of AI to fuel creativity and innovation in business management.

Master the art of hybrid team management with our comprehensive course. Learn effective techniques for transitioning, team building, and driving high performance in a hybrid work environment. Elevate your leadership skills and optimize your team’s effectiveness in today’s dynamic work landscape.

Information Management Diploma Unlock the potential of effective data governance with our Information Management Diploma. This course is meticulously designed to equip you with the expertise needed in Information Management, focusing on IT Asset Management (ITAM), data security, compliance, and the legal landscape around data management, such as GDPR. Learning Outcomes: Master the essentials of ITAM Policies and delineate IT Management Responsibilities within the scope of Information Management. Understand the intricacies of setting up an effective ITAM Program as a pivotal part of your Information Management strategy. Be adept in IT Asset Procurement and Deployment, essential processes in Information Management. Gain comprehensive knowledge in IT Asset Security and Compliance, key components of Information Management. Become proficient in the Principles of GDPR, especially its implications on Information Management. Recognise the Rights of Data Subjects and learn how to safeguard them in your Information Management systems. More Benefits: LIFETIME access Device Compatibility Free Workplace Management Toolkit Key Modules from Information Management Diploma: ITAM Policies and IT Management Responsibilities in Information Management Learn the foundational policies that govern IT Asset Management and the responsibilities that IT managers bear in Information Management. Setting up an ITAM Program within Information Management Acquire the knowledge and tools required to initiate, plan, and manage an ITAM program, ensuring it complements your Information Management strategy effectively. IT Asset Procurement and Deployment in Information Management Delve into the processes that govern the acquisition and implementation of IT assets, understanding how these processes fit into Information Management. IT Asset Security and Compliance in Information Management Develop the acumen to secure IT assets effectively and understand the compliance parameters within the realm of Information Management. Principles of GDPR in Information Management Equip yourself with an in-depth understanding of GDPR principles and their critical importance to Information Management. Rights of Data Subjects in Information Management Comprehend the rights that data subjects possess under GDPR and learn how to implement mechanisms to protect these rights within your Information Management strategies.

Artificial Intelligence (AI) is the most disruptive technology since the internet came onto the scene. AI is transforming every aspect of how we manage projects from developing a business case, to planning the work, managing risk, and tracking performance. Because the technology and market are moving so fast, it can be difficult to know how to start using AI on projects. Generative AI for Project Management will engage you with diverse Generative AI tools to start, plan, and manage either your own project or a generic case study. We will embrace a tool agnostic approach to adopting, integrating, and scaling Generative AI without compromising data or trust. You will have hands-on practice utilizing AI tools to optimize your time and your outcomes. You will be accessing a variety of AI tools requiring you to register for a free account. A computer is required for all traditional classroom deliveries. None At the end of this program, you will be able to: Define essential terms and concepts related to artificial intelligence (AI) Illustrate how prompts facilitate interaction with Generative AI Recognize the capabilities of Large Language Models Craft prompts to develop project origination documents Create prompts to assist in planning a project Develop user stories with Generative AI Analyze project performance using Generative AI Identify the limitations of Generative AI Identify the risks associated with using Generative AI Articulate the need for governance and ethics when establishing an AI program in an organization Course Overview Getting Started Foundation Concepts Understanding essential terms and concepts related to AI Exploring various Generative AI Models Understanding Prompts Creating Prompts for Project Startup Prompts for starting a project Prompts for planning a project Best Practices for prompt engineering Creating Prompts for Managing Projects Creating agile user stories Measuring project performance Analyzing a schedule Using Generative AI Responsibly Limitations of AI Models Establishing an AI governance framework Future trends and next steps Summary and Next Steps