1676 Computing & IT courses delivered Live Online

Duration 5 Days 30 CPD hours This course is intended for Penetration Testers Microsoft Administrator Security Administrators Active Directory Administrators Anyone looking to learn more about security Overview The person who carries this certification should be able to analyze an organization's existing systems then plan and create an incident handling system that will prevent, detect, and respond to cyber attacks The Certified Incident Handling Engineer course, C)IHE, is designed to help Incident Handlers, System Administrators, and Security Engineers understand how to plan, create and utilize their systems. Prevent, detect and respond to attacks through the use of hands-on labs in our exclusive Cyber Range. With this in-depth training, you will learn to develop start to finish processes for establishing your Incident Handling team, strategizing for each type of attack, recovering from attacks and much more. Course Outline Incident Handling Explained Incident Response Policy, Plan and Procedure Creation Incident Response Team Structure Incident Response Team Services Incident Response Recommendations Preparation Detection and Analysis Containment, Eradication and Recovery GRR Rapid Response Request Tracker for Incident Response Post Incident Activity Incident Handling Checklist Incident Handling Recommendations Coordination and Information Sharing

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 5 Days 30 CPD hours This course is intended for This advanced course is for anyone responsible for implementing and managing virtualization features on a System p server including: AIX technical support individuals System administrators Systems engineers System Architects Overview Upon successful completion of this course, students will be able to: Describe the effect of the IBM PowerVM virtualization features on performance and monitoring, such as: Simultaneous multithreading (SMT), shared processors, multiple shared processor pools (MSPP), shared dedicated capacity, Active Memory Sharing (AMS), Active Memory Expansion (AME), Live Partition Mobility (LPM), and other virtualization features Interpret the outputs of AIX performance monitoring and tuning tools used to view the impact of features such as SMT, shared processors, additional shared processor pool activations, and device virtualization. Perform a Live Partition Mobility between two Power Systems servers Configure and monitor Active Memory Expansion Configure the Suspend and Resume and Active Memory Sharing features available with the Virtual I/O Server Implement the deduplication feature of Active Memory Sharing Students will learn how to implement advanced IBM PowerVM features, such as Active Memory Sharing, Active Memory Expansion, shared dedicated processors, multiple shared processor pools, and Live Partition Mobility. Students will learn how to implement advanced IBM PowerVM features, such as Active Memory Sharing, Active Memory Expansion, shared dedicated processors, multiple shared processor pools, and Live Partition Mobility. Additional course details: Nexus Humans AN31 IBM Power Systems for AIX - Virtualization II - Advanced PowerVM and Performance 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 AN31 IBM Power Systems for AIX - Virtualization II - Advanced PowerVM and Performance 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.

ChatGPT, along with other AI tools, aims not to replace the human touch in management, but to enhance it. By addressing repetitive, daily tasks, these tools free up managers to concentrate on core responsibilities like strategic decision-making, team development, and innovation. As we move further into the digital age, integrating tools such as ChatGPT isn't a luxury; it's the future of proactive leadership. In this guide, we'll delve into 10 practical ways through which AI can elevate your efficiency and refine the quality of your work. Gain familiarity with prominent AI tools in the market Efficiently compose and respond to emails Generate concise summaries of complex reports and data. Obtain quick insights, data, and research across varied topics Streamline the writing of articles, training notes, and posts Craft interview tests, form relevant questions, and design checklists for the hiring process 1 Streamlining emails An inbox can be a goldmine of information but also a significant time drain for managers. Here's how to optimise it: Drafting responses: Give the AI a brief, and watch it craft a well-structured response. Sorting and prioritising: By employing user-defined rules and keywords, ChatGPT can flag important emails, ensuring no vital communication slips through the cracks. 2 Efficient report writing Reports, especially routine ones, can be time-intensive. Here's a smarter approach: Automate content: Supply key data points to the AI, and let it weave them into an insightful report. Proofreading: Lean on ChatGPT for grammar checks and consistency, ensuring each report remains crisp and error-free. 3 Rapid research From competitor insights to market trends, research is a pivotal part of management. Data synthesis: Feed raw data to the AI and receive succinct summaries in return. Question-answering: Pose specific questions about a dataset to ChatGPT and extract swift insights without diving deep into the entire content. 4 Reinventing recruitment Hiring can be a lengthy process. Here's how to make it more efficient: Resume screening: Equip the AI to spot keywords and qualifications, ensuring that only the most fitting candidates are shortlisted. Preliminary interviews: Leverage ChatGPT for the initial rounds of interviews by framing critical questions and evaluating the responses. 5 Enhancing training Especially for extensive teams, training can be a monumental task. Here's how ChatGPT can assist: Customised content: Inform the AI of your training goals, and it will draft tailored content suitable for various roles. PowerPoint design: Create visually appealing slide presentations on any topic in minimal time.

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

Duration 5 Days 30 CPD hours This course is intended for NULL Overview Topics include: basic file manipulation; basic and advanced filesystem features; I/O redirection and pipes; text manipulation and regular expressions; managing jobs and processes; vi, the standard Unix editor; automating tasks with shell scripts; managing software; secure remote administration; and more. The GL120 is a challenging course that focuses on the fundamental tools and concepts of Linux and Unix. Students gain proficiency using the command line. Beginners develop a solid foundation in Unix, while advanced users discover patterns and fill in gaps in their knowledge. Like all Guru Labs courses, the course material is designed to provide extensive hands-on experience. The GL120 is a challenging course that focuses on the fundamental tools and concepts of Linux and Unix. Students gain proficiency using the command line. Beginners develop a solid foundation in Unix, while advanced users discover patterns and fill in gaps

Duration 5 Days 30 CPD hours This course is intended for Software Engineers and DevOps professionals working in an Enterprise developing mission critical line of business applications. Overview By the end of this course, students will be able to: Assess the advantages of a containerized software development & deployment Use Docker engine features necessary for running containerized applications Utilize Swarm and Kubernetes orchestrators to deploy, maintain, and scale a distributed application Describe the essential patterns used in a highly distributed EE application Understand how to configure EE applications for different environments without code changes Produce and containerize scalable, accessible, and fault-tolerant EE applications Apply different debugging and testing techniques to containerized EE applications The Docker Fundamentals + Enterprise Operations Bundle includes the full Docker for Enterprise Operations course as well as the prerequisite Docker Fundamentals course run back to back in a single intensive training experience. The Docker Fundamentals training course features the foundational concepts and practices of containerization on a single Docker node. The course offers learners the opportunity to assimilate basic container orchestration and how to scale Docker across multiple nodes in a simple swarm cluster. This course provides essential foundational knowledge for subsequent Docker courses. As the follow-on to the Docker Fundamentals course, Docker for Enterprise Operations is a role-based course is designed for Docker Operations teams to accelerate their Docker journey in the enterprise. The course covers in-depth core advanced features of Docker EE and best practices to apply these features at scale with enterprise workloads. Platform Availability: Linux, Windows (Fundamentals Only). Introducing Docker Containerization Fundamentals Creating Images Docker Volumes Docker Networking Basics Introduction to Docker Compose Introduction to Swarm Mode Introduction to Kubernetes Secrets Fundamentals Signature Assignment Distributed Application Architecture Sample Application Edit and Continue Debugging Docker Compose Testing Service Discovery Defensive Programming Logging and Error Handling Health Checks Secrets Configuration Management Development Pipeline Overview Universal Control Plane Docker Trusted Registry Repository Automation Build Server

Duration 3 Days 18 CPD hours This course is intended for The target audience for the SRE Practitioner course are professionals including: Anyone focused on large-scale service scalability and reliability 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 have learned: Practical view of how to successfully implement a flourishing SRE culture in your organization. The underlying principles of SRE and an understanding of what it is not in terms of anti-patterns, and how you become aware of them to avoid them. The organizational impact of introducing SRE. Acing the art of SLIs and SLOs in a distributed ecosystem and extending the usage of Error Budgets beyond the normal to innovate and avoid risks. Building security and resilience by design in a distributed, zero-trust environment. How do you implement full stack observability, distributed tracing and bring about an Observability-driven development culture? Curating data using AI to move from reactive to proactive and predictive incident management. Also, how you use DataOps to build clean data lineage. Why is Platform Engineering so important in building consistency and predictability of SRE culture? Implementing practical Chaos Engineering. Major incident response responsibilities for a SRE based on incident command framework, and examples of anatomy of unmanaged incidents. Perspective of why SRE can be considered as the purest implementation of DevOps SRE Execution model Understanding the SRE role and understanding why reliability is everyone's problem. SRE success story learnings This course introduces a range of practices for advancing service reliability engineering through a mixture of automation, organizational ways of working and business alignment. Tailored for those focused on large-scale service scalability and reliability. SRE Anti-patterns Rebranding Ops or DevOps or Dev as SRE Users notice an issue before you do Measuring until my Edge False positives are worse than no alerts Configuration management trap for snowflakes The Dogpile: Mob incident response Point fixing Production Readiness Gatekeeper Fail-Safe really? SLO is a Proxy for Customer Happiness Define SLIs that meaningfully measure the reliability of a service from a user?s perspective Defining System boundaries in a distributed ecosystem for defining correct SLIs Use error budgets to help your team have better discussions and make better data-driven decisions Overall, Reliability is only as good as the weakest link on your service graph Error thresholds when 3rd party services are used Building Secure and Reliable Systems SRE and their role in Building Secure and Reliable systems Design for Changing Architecture Fault tolerant Design Design for Security Design for Resiliency Design for Scalability Design for Performance Design for Reliability Ensuring Data Security and Privacy Full-Stack Observability Modern Apps are Complex & Unpredictable Slow is the new down Pillars of Observability Implementing Synthetic and End user monitoring Observability driven development Distributed Tracing What happens to Monitoring? Instrumenting using Libraries an Agents Platform Engineering and AIOPs Taking a Platform Centric View solves Organizational scalability challenges such as fragmentation, inconsistency and unpredictability. How do you use AIOps to improve Resiliency How can DataOps help you in the journey A simple recipe to implement AIOps Indicative measurement of AIOps SRE & Incident Response Management SRE Key Responsibilities towards incident response DevOps & SRE and ITIL OODA and SRE Incident Response Closed Loop Remediation and the Advantages Swarming ? Food for Thought AI/ML for better incident management Chaos Engineering Navigating Complexity Chaos Engineering Defined Quick Facts about Chaos Engineering Chaos Monkey Origin Story Who is adopting Chaos Engineering Myths of Chaos Chaos Engineering Experiments GameDay Exercises Security Chaos Engineering Chaos Engineering Resources SRE is the Purest form of DevOps Key Principles of SRE SREs help increase Reliability across the product spectrum Metrics for Success Selection of Target areas SRE Execution Model Culture and Behavioral Skills are key SRE Case study Post-class assignments/exercises Non-abstract Large Scale Design (after Day 1) Engineering Instrumentation- Instrumenting Gremlin (after Day 2)

Duration 3 Days 18 CPD hours This course is intended for This introduction to Spring development course requires that incoming students possess solid Java programming skills and practical hands-on Java experience. This class is geared for experienced Java developers who are new to Spring, who wish to understand how and when to use Spring in Java and JEE applications. Overview Working in a hands-on learning environment, students will review configuration basics of the Spring framework. The course then moves into Spring Boot, providing in-depth content and experience working with Spring Boot to accomplish a variety of tasks. In addition to working through the Spring Actuator, students work extensively at testing and debugging Spring Boot applications. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' application development and Spring experience into every classroom. Working in a hands-on learning environment, led by our expert practitioner, students will: Review the concept of Java-based configuration Become familiar with the conditionally loading bean definitions and Application Contexts Understand how to leverage the power of Spring Boot Use Spring Boot to create and work with JPA repositories Use Spring Boot to work in conjunction with Spring Cloud Understand the Spring Cloud project and how it relates to general Cloud concepts and practices Work with Spring Cloud configuration and the Config Client The Spring framework is an application framework that provides a lightweight container that supports the creation of simple-to-complex components in a non-invasive fashion. Spring's flexibility and transparency is congruent and supportive of incremental development and testing. The framework's structure supports the layering of functionality such as persistence, transactions, view-oriented frameworks, and enterprise systems and capabilities. Introduction to Spring Boot and Spring Cloud is a hands-on Spring training course geared for experienced Java developers who need to understand what the Spring Boot is in terms of today's systems and architectures, and how to use Spring in conjunction with other technologies and frameworks. This course targets Spring Boot 2, which includes full support for Java 8 and JEE 7 (earlier versions of Java and JEE continue to be supported). Spring supports the use of lambda expressions and method references in many of its APIs. Spring makes enterprise development easier. Spring simplifies common tasks and encourages good design based on programming to interfaces. Spring makes your application easier to configure and reduces the need for many JEE design patterns. Spring puts the OO design back into your enterprise application, and it integrates nicely with many view technologies and the new features of HTML5. Introduction to Spring The Spring Framework Configuring Spring Managed Beans Defining Bean dependencies Spring Cloud Spring Boot Additional Configuration Spring Cloud Project Introduction to Spring Boot Working with Spring Boot Spring AOP Introduction to Aspect Oriented Programming Spring Cloud Config Spring Cloud Registry and Discovery Spring AOP Spring Boot 2 Spring Boot Actuator Developing in Spring Boot Thymeleaf Spring Cloud GateWay Additional course details: Nexus Humans Introduction to Spring Boot and Spring Cloud (TT3324) 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 Introduction to Spring Boot and Spring Cloud (TT3324) 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 is an introductory-level course, designed for anyone wanting to learn Linux. Attendees should be comfortable working with computers and the command line, but no other specific skills are required to attend. Overview This skills-focused course is about 50% lab to lecture ratio, combining expert instructor-led discussions with practical hands-on labs that emphasize current techniques, best practices and standards. Working in a hands-on lab environment, guided by our expert practitioner, attendees will explore The Design of Linux Basic Operations File System Basics Wildcards File and Directory Permissions Working with files Executing Programs Using find Filters and other useful commands The vi editor Customizing the user environment Networking/Communications Backups and archiving This hands-on course provides you with an essentials-level foundation in core skills for using any version of Linux. This course focuses on essential skills that ordinary users might use daily when working with Linux. The Design of Linux A brief history of Linux The Linux design philosophy Linux architecture Basic Operations Logging in and out The general form of a Linux command Common commands Using man pages Essential commands File System Basics The Linux directory structure Standard directories Relative and absolute pathnames Legal file names Navigating the filesystem Wildcards Matching one character Matching many characters Shortcuts Wildcard gotchas Wildcards and ls File and Directory Permissions Viewing permissions File permissions Directory permissions Setting defaults Changing permissions Keeping data secure Working with files Viewing contents Identifying file contents Copying and moving Deleting Using symbolic links Executing Programs Redirecting STDOUT Redirecting STDERR Redirecting STDIN Creating pipelines Processes attributes Listing processes Killing processes Foreground & background processes Using find Syntax Finding by name, type, or size Combining tests Finding by size, owner, or timestamps Using xargs with find Other find options Filters and other useful commands What is a filter? cat: a generic filter head and tail grep sort wc other interesting filters The vi editor Why vi? Basic vi operations: navigating, adding, deleting Advanced operations: buffer management, search and replace, configuration options Customizing the user environment About shells Shell startup files Shell variables Search path Aliases Simple shell scripts Networking/Communications Reading and sending mail Remote login Remote file transfer Other network utilities (ping, finger, etc) Backups and archiving Checking space used or available Creating tar archives Viewing and extracting files from archives Compression utilities Working with windows