425 Engineering courses in Kimberley delivered Live Online

Management of Portfolios (MoP®) Foundation: In-House Training In this MoP® Foundation course, participants will acquire the sufficient knowledge and understanding of the principles, cycles, practices, techniques, roles, responsibilities, documents, and organizational context within which portfolio management operates. MoP helps organizations ensure if the investments are done in the right change initiatives and implementing them correctly. This is achieved by: Prioritizing the programs and projects in terms of their contribution to the organization's strategic objectives and overall level of risk Managing the programs and projects consistently to ensure efficient and effective delivery Maximizing the benefit by providing the greatest return from the investment made What You Will Learn Individuals certified at the MoP Foundation level will be able to: Define the scope and objectives of portfolio management and how it differs from program and project management List the benefits of applying portfolio management Explain the context it operates in List the principles upon which successful portfolio management is based on List the different approaches to implement MoP List the factors required to maintain the progress and assess the success of portfolio management State the purpose and key content of the major portfolio documents Define the scope of key portfolio management roles Introduction: MoP Scenario Background of the Methodology The MoP Principles Senior Management Commitment Governance Alignment Strategy Alignment Portfolio Office Energized Change Culture The MoP Definition Cycle Roles and Responsibilities The MoP Delivery Cycle Management control Benefits management Financial management Risk management Stakeholder engagement Organizational governance Resource management The MoP Framework Recap

Management of Portfolios (MoP®) Foundation: Virtual In-House Training In this MoP® Foundation course, participants will acquire the sufficient knowledge and understanding of the principles, cycles, practices, techniques, roles, responsibilities, documents, and organizational context within which portfolio management operates. MoP helps organizations ensure if the investments are done in the right change initiatives and implementing them correctly. This is achieved by: Prioritizing the programs and projects in terms of their contribution to the organization's strategic objectives and overall level of risk Managing the programs and projects consistently to ensure efficient and effective delivery Maximizing the benefit by providing the greatest return from the investment made What You Will Learn Individuals certified at the MoP Foundation level will be able to: Define the scope and objectives of portfolio management and how it differs from program and project management List the benefits of applying portfolio management Explain the context it operates in List the principles upon which successful portfolio management is based on List the different approaches to implement MoP List the factors required to maintain the progress and assess the success of portfolio management State the purpose and key content of the major portfolio documents Define the scope of key portfolio management roles Introduction: MoP Scenario Background of the Methodology The MoP Principles Senior Management Commitment Governance Alignment Strategy Alignment Portfolio Office Energized Change Culture The MoP Definition Cycle Roles and Responsibilities The MoP Delivery Cycle Management control Benefits management Financial management Risk management Stakeholder engagement Organizational governance Resource management The MoP Framework Recap

This highly interactive program focuses on building the business focus on value to be achieved from initiatives. The practices in this program apply equally to projects and programs. Participants will gain insight into the capabilities needed to develop the culture, processes, and tools behind validation, what true initiatives' success looks like, which can be closely linked to achieving value. They will learn and experiment with a variety of value definition and management techniques. Working in small groups, they will collaborate with others to brainstorm, share experiences, and apply concepts to the ongoing value confirmation goal. Participants will also discover the importance of designing metrics around value and addressing blind spots that could happen when the focus is on the wrong metrics and how that could lead to the wrong behaviors being practiced. Participants will also gain insights into key skills for leading and working in the future. Hands-on experimentation activities enhance the theoretical learning, grounding it in real life and giving opportunities to practice creativity in capturing value.

Our excellent value long-term support option for RICS APC candidates, covering all RICS APC routes, pathways and world regions. This is one of our most popular packages providing you with your own personal APC support team. This can include a Counsellor sign-off, subject to separate agreement between you and Property Elite. This includes: Submission Review APC Question Pack E-mock Interview 2 hours of 1-2-1 or small group online/telephone mentoring per month with a current RICS APC assessor. If you wish, this can be saved up to use at any time during your sign-up period with Property Elite. Full suite of online revision quizzes Full revision guide package Our minimum sign up period is 4 months - minimum £350 + VAT per month over 4 months = total of £1,400 + VAT. You will need to sign up at least 1 month before you submit your final assessment documents to ensure you are able to take full advantage of this package.

Duration 3 Days 18 CPD hours This course is intended for This class is intended for the following customer job roles: Cloud architects, administrators, and SysOps personnel Cloud developers and DevOps personnel Overview This course teaches participants the following skills: Plan and implement a well-architected logging and monitoring infrastructure Define Service Level Indicators (SLIs) and Service Level Objectives (SLOs) Create effective monitoring dashboards and alerts Monitor, troubleshoot, and improve Google Cloud infrastructure Analyze and export Google Cloud audit logs Find production code defects, identify bottlenecks, and improve performance Optimize monitoring costs This course teaches you techniques for monitoring, troubleshooting, and improving infrastructure and application performance in Google Cloud. Guided by the principles of Site Reliability Engineering (SRE), and using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage. Introduction to Google Cloud Monitoring Tools Understand the purpose and capabilities of Google Cloud operations-focused components: Logging, Monitoring, Error Reporting, and Service Monitoring Understand the purpose and capabilities of Google Cloud application performance management focused components: Debugger, Trace, and Profiler Avoiding Customer Pain Construct a monitoring base on the four golden signals: latency, traffic, errors, and saturation Measure customer pain with SLIs Define critical performance measures Create and use SLOs and SLAs Achieve developer and operation harmony with error budgets Alerting Policies Develop alerting strategies Define alerting policies Add notification channels Identify types of alerts and common uses for each Construct and alert on resource groups Manage alerting policies programmatically Monitoring Critical Systems Choose best practice monitoring project architectures Differentiate Cloud IAM roles for monitoring Use the default dashboards appropriately Build custom dashboards to show resource consumption and application load Define uptime checks to track aliveness and latency Configuring Google Cloud Services for Observability Integrate logging and monitoring agents into Compute Engine VMs and images Enable and utilize Kubernetes Monitoring Extend and clarify Kubernetes monitoring with Prometheus Expose custom metrics through code, and with the help of OpenCensus Advanced Logging and Analysis Identify and choose among resource tagging approaches Define log sinks (inclusion filters) and exclusion filters Create metrics based on logs Define custom metrics Link application errors to Logging using Error Reporting Export logs to BigQuery Monitoring Network Security and Audit Logs Collect and analyze VPC Flow logs and Firewall Rules logs Enable and monitor Packet Mirroring Explain the capabilities of Network Intelligence Center Use Admin Activity audit logs to track changes to the configuration or metadata of resources Use Data Access audit logs to track accesses or changes to user-provided resource data Use System Event audit logs to track GCP administrative actions Managing Incidents Define incident management roles and communication channels Mitigate incident impact Troubleshoot root causes Resolve incidents Document incidents in a post-mortem process Investigating Application Performance Issues Debug production code to correct code defects Trace latency through layers of service interaction to eliminate performance bottlenecks Profile and identify resource-intensive functions in an application Optimizing the Costs of Monitoring Analyze resource utilization cust for monitoring related components within Google Cloud Implement best practices for controlling the cost of monitoring within Google Cloud

Duration 3 Days 18 CPD hours This course is intended for This course is targeted for Juniper Networks system engineers, partner sales engineers (including Champions), and services partners who are interested in learning network design introductory concepts. However, the course is also applicable to a general audience of Juniper customers with a desire to learn more about network design. Overview Provide an overview of network design needs and common business requirements.Describe key product groups related to campus, WAN, data center, and security architectures.Analyze and interpret common RFP requirements.Scope a network design by gathering data and working with key stakeholders.Describe ways of processing customer data and design requests.Identify boundaries and scope for the design proposal.List some considerations when creating a design proposal.Provide an overview of network security design principles and common vulnerabilities.List high-level design considerations and best practices for securing the network.List the components of the campus network design.Describe best practices and design considerations for the campus.Describe architectural design options for the campus.List the components of the WAN.Describe best practices and design considerations for the WAN.Describe design options for the WAN.List the components of the data center design.Describe best practices and design considerations for the data center.Describe architectural design options for the data center.Define business continuity and its importance in a network design.Describe high availability design considerations and best practices.Provide an overview of high availability offerings and solutions.Describe Class of Service design considerations.Provide an overview of environmental considerations in network design.List design considerations and best practices for managing the network.Provide an overview of Juniper Networks and third party options for network management.List design considerations and best practices for network automation.Provide an overview of automation tools.Explain the foundational topics that have been taught throughout the course.Create a network design proposal that satisfies customer requirements and business needs.Provide an overview of the steps involved in migrating a network.Describe best practices used in network migration.List the various campus network topographies.Describe sample design options for the campus. This three-day course is designed to cover best practices, theory, and design principles for overall network design and will serve as the prerequisite course for other design subject areas ƒ?? data center, security, and WAN. Course IntroductionNetwork Design Fundamentals A Need for Design Knowledge is King A Proposed Design Methodology A Reference Network Understanding Customer Requirements RFP Requirements Scoping the Design Project Analyzing the Data Lab: Understanding Customer Requirements Organizing the Data Processing the Data and Requests Understanding Boundaries and Scope Design Proposal Considerations Securing the Network Why Secure the Network? Security Design Considerations Creating the Design Campus The Campus Network: An Overview Best Practices and Considerations Architectural Design Options Lab: Creating the Design Campus Creating the Design Wide Area Network The WAN: An Overview Best Practices and Considerations WAN Design Examples Lab: Creating the Design WAN Creating the Design Data Center The Data Center: An Overview Best Practices and Considerations Data Center Design Examples Lab: Creating the Design Data Center Business Continuity & Network Enhancements Business Continuity Planning High Availability Design Considerations and Best Practices Offerings and Solutions CoS and Traffic Engineering Considerations Environmental Design Network Management Designing for Network Management Automation Designing for Network Automation Lab: Enhancing the Design Putting Network Design Into Practice Network Design Recap Responding to the RFP Final Lab Introduction Lab: Putting Network Design into Practice

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Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 4 Days 24 CPD hours This course is intended for If you're a developer with a keen interest in providing automated solutions for your organization, this certification could be a great fit for you. You automate time-consuming and repetitive tasks by using Microsoft Power Automate. You review solution requirements, create process documentation, and design, develop, deploy, integrate, troubleshoot, and evaluate solutions. Working with business stakeholders, you help to improve and automate business workflows. Overview After completing this course, students will be able to: Design RPA solutions Develop RPA solutions Deploy and manage RPA solutions Candidates for this course automate time-consuming and repetitive tasks by using Microsoft Power Automate. They review solution requirements, create process documentation, and design, develop, troubleshoot, and evaluate solutions. Candidates work with business stakeholders to improve and automate business workflows. They collaborate with administrators to deploy solutions to production environments, and they support solutions. Module 1: Get started with Power Automate for desktop Get started with Power Automate for desktop by learning about flows, creating automated steps, and flow development essentials. Module 2: Automate processes with Robotic Process Automation and Power Automate for desktop Work with Power Automate for desktop to record Windows and Web applications, but also use out of box actions such as manipulating Excel documents as part of an end to end invoice processing solution. Module 3: Work with Power Automate for desktop Work with Power Automate for desktop options, flows, recording features, conditions, loops, variables, images, and error and exception handling. Module 4: Work with different technologies in Power Automate for desktop Learn how to automate email handling, Excel, user interface, and system services with Power Automate for desktop. Module 5: Implement advanced logic in Power Automate for desktop Learn how to work with system flows, control flows, mimic mouse actions, as well as operations used to manipulate text, date, and time in Power Automate for desktop. Module 6: Build expertise with Power Automate for desktop Learn how to use Power Automate for desktop to work with Power Automate, OCR technologies, and scripting. Module 7: Build custom connectors for Power Automate This Learning Path explores custom connectors and explains how to configure them and use them with Microsoft Power Automate Module 8: Use best practices to secure and govern Microsoft Power Platform environments This module focuses on introducing Microsoft Power Platform environments and their role in creating Data Loss Prevention (DLP) policies by using examples and use cases. A brief introduction and overview of tools will also be discussed, including Microsoft Power Platform and Power Automate Admin experiences and Microsoft Power Platform Center of Excellence (COE) toolkit. Additional course details: Nexus Humans PL-500T00 Microsoft Power Automate RPA Developer 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 PL-500T00 Microsoft Power Automate RPA Developer 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.

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.