27694 Development courses delivered Online

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts. Students should have skills at least equivalent to the Python for Data Science courses we offer. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to Understand the main concepts and principles of predictive analytics Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms w with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This course provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. Hands-on Predictive Analytics with Python is a three-day, hands-on course that guides students through a step-by-step approach to defining problems and identifying relevant data. Students will learn how to perform data preparation, explore and visualize relationships, as well as build models, tune, evaluate, and deploy models. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seabor, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. The Predictive Analytics Process Technical requirements What is predictive analytics? Reviewing important concepts of predictive analytics The predictive analytics process A quick tour of Python's data science stack Problem Understanding and Data Preparation Technical requirements Understanding the business problem and proposing a solution Practical project ? diamond prices Practical project ? credit card default Dataset Understanding ? Exploratory Data Analysis Technical requirements What is EDA? Univariate EDA Bivariate EDA Introduction to graphical multivariate EDA Predicting Numerical Values with Machine Learning Technical requirements Introduction to ML Practical considerations before modeling MLR Lasso regression KNN Training versus testing error Predicting Categories with Machine Learning Technical requirements Classification tasks Credit card default dataset Logistic regression Classification trees Random forests Training versus testing error Multiclass classification Naive Bayes classifiers Introducing Neural Nets for Predictive Analytics Technical requirements Introducing neural network models Introducing TensorFlow and Keras Regressing with neural networks Classification with neural networks The dark art of training neural networks Model Evaluation Technical requirements Evaluation of regression models Evaluation for classification models The k-fold cross-validation Model Tuning and Improving Performance Technical requirements Hyperparameter tuning Improving performance Implementing a Model with Dash Technical requirements Model communication and/or deployment phase Introducing Dash Implementing a predictive model as a web application Additional course details: Nexus Humans Hands-on Predicitive Analytics with Python (TTPS4879) 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 Hands-on Predicitive Analytics with Python (TTPS4879) 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 Operators, administrators, and architects responsible for the creation, maintenance, or delivery of remote and virtual desktop services. Overview By the end of the course, you should be able to meet the following objectives: Recognize the features and benefits of Horizon Use VMware vSphere to create VMs to be used as desktops for Horizon Create and optimize Windows VMs to create Horizon desktops Install and configure Horizon Agent on Horizon desktop Configure and manage the VMware Horizon Client™ systems and connect the client to a VMware Horizon desktop Configure, manage, and entitle desktop pools of full VMs Configure, manage, and entitle pools of instant-clone desktops Create and use Remote Desktop Services (RDS) desktops and application pools Monitor the Horizon environment using Horizon Console Dashboard and Horizon Help Desk Tool Implement a structured approach to troubleshooting Resolve common issues that occur in a Horizon environment Troubleshoot issues with linked and instant clones Configure the Windows client Identify the correct log level for gathering logs Optimize protocols for the best end-user experience VMware Horizon© 8: Virtual Desktop Bootcamp is a five-day combination course of VMware Horizon 8: Skills for Virtual Desktop Management and VMware Horizon 8: Virtual Desktop Troubleshooting. This training combination gives you the skills to deliver virtual desktops and applications through a single virtual desktop infrastructure platform. You build skills in configuring and managing VMware Horizon 8 through a combination of lecture and hands-on labs. You learn how to configure and deploy pools of virtual machines and how to provide a customized desktop environment to end-users. Additionally, you learn how to resolve common issues that occur in a VMware Horizon environment. You engage in a series of lab exercises to bring existing environment issues to resolution. The exercises mirror real-world troubleshooting use cases. These exercises equip learners with the knowledge and practical skills to manage typical challenges faced by virtual desktop administrators and operators. Course Introduction Introductions and course logistics Course objectives Introduction to VMware Horizon Recognize the features and benefits of VMware Horizon Describe the conceptual and logical architecture of VMware Horizon Introduction to Use Case Define a use case for your virtual desktop and application infrastructure Convert customer requirements to use-case attributes vSphere for Horizon 8 Explain basic virtualization concepts Use VMware vSphere© Client? to access your vCenter Server system and VMware ESXi? hosts Create, provision, and remove a virtual machine VMware Horizon Desktops Create a Windows and a Linux virtual machine using vSphere Optimize and prepare Windows and Linux virtual machines to set up VMware Horizon desktop VMs VMware Horizon Agents Outline the configuration choices when installing Horizon Agent on Windows and Linux virtual machines Create a gold master for Windows Horizon desktops VMware Horizon Pools Identify the steps to set up a template for desktop pool deployment List the steps to add desktops to the VMware Horizon© Connection Server? inventory Compare dedicated-assignment and floatingassignment pools Outline the steps to create an automated pool Define user entitlement Explain the hierarchy of global, pool-level, and userlevel policies VMware Horizon Client Options Describe the different clients and their benefits Access Horizon desktop using various Horizon clients and HTML Configure integrated printing, USB redirection, and the shared folders option Configure session collaboration and media optimization for Microsoft Teams Creating and Managing Instant-Clone Desktop Pools List the advantages of instant clones Explain the provisioning technology used for instant-clone desktop pools Set up an automated pool of instant clones Push updated images to instant-clone desktop pools Creating RDS Desktop and Application Pools Explain the difference between an RDS desktop pool and an automated pool Compare and contrast an RDS session host pool, a farm, and an application pool Create an RDS desktop pool and an application ool Access RDS desktops and application from Horizon Client Use the instant clone technology to automate the build-out of RDSH farms Configure load-balancing for RDSHs on a farm Monitoring VMware Horizon Monitor the status of the VMware Horizon components using the Horizon Administrator console dashboard Monitor desktop sessions using the HelpDesk tool Overview of Virtual Desktop Troubleshooting Structured approach to troubleshooting configuration and operational problems Applying troubleshooting methods

Duration 2 Days 12 CPD hours This course is intended for System Engineers/Administrators; Backup/Virtualization Administrators; Solution Architects/Consultants Overview By the end of the course, students should be able to:Maximize your expertise on consulting/professional services for the Veeam Availability Suite solutionAim for the VMCA title and comply with some of the certifications requirements for Platinum ProPartners and Veeam Accredited Service Partners (VASPs)Gain professional advantage with the highest level of Veeam technical certification This course covers Veeam Availability Suite? design and optimization and is based on best practices from Veeam solutions architects. IntroductionDesign & Sizing DNS and name resolution Veeam backup server Backup and replication database Proxy server Transport modes Repository server WAN accelerator Interaction with hypervisors Infrastructure Stages of Proof of Concept Assessment using Veeam ONE? Important data to collect (Veeam ONE + infrastructure accounts) Security Permissions Design Scenario: Part 1 Discovery Create a design based on the customer environment Optimizations Backup and replication database Proxy server Repository server WAN accelerator Tape Veeam Backup Enterprise Manager Indexing Antivirus on Veeam servers and guest VM (if VSS is used) Protecting Veeam Backup & Replication? configuration Design Scenario: Part 2 Create a design based on the customer?s evolving environment Automation Veeam backup server VMware vSphere tags Audit & Compliance Auditing Compliance SureBackup© and SureReplica Troubleshooting Deep dive into reading log files Common issues Troubleshooting mode (SureBackup/SureReplica)

Duration 0.75 Days 4.5 CPD hours This course is intended for Making Microsoft Word documents accessible. Overview Please refer to Overview. During this course students will interact with a variety of Word documents and review components that would render the document inaccessible. Students will enable the Accessibility Checker and the Speak feature and progress through the processes and procedures to meet the AODA mandate. Students will ultimately create an accessible set of styles and use those styles within the document. Adding the Accessibility Checker and the Speak feature Discussions will follow as to the limitations of the checker When the checker won?t run Document Metadata Students will review where and why to add metadata to a Word Document Setting the application language and setting the document language Setting the document title Adding the Author and subject metadata fields Creating Accessible Paragraphs and Columns Students will see the perils of incorrect use of hard returns and text boxes within a document Exercises will have students work with paragraph formatting and column formatting for accessibility Creating Accessible Tables Students will interact with tables that are poorly designed and restricted them to still maintain content but that are now accessible Discussions will surround, changes to how tables are handled when sending to PDF Accessible Imagery Students will discuss the need to images with a document The Alternate text feature will be used and the rationale for adding specific types of descriptions Students will see and understand the rationale for ?in-line- imagery Styles for Navigation Students will use and modify the built-in styles feature of Microsoft Word and create a table of contents Students will see with the use of the navigation pane, how styles impact accessibility Students will also understand the importance of proper styles nesting Headers, Footers and Footnotes Students will discuss and then implement accessible headers and footers Students will discuss footnotes and alternative methods to provide footnotes Verifying Reading Order Students will ?listen? to their documents using the Speak feature Students will enable the selection pane as an accessibility tools and discuss its limitations Creating an Accessible Style Template Students will create several accessible styles including headings and paragraphs Students will save the style within a template Additional course details: Nexus Humans Accessible Documents 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 Accessible Documents 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 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Architects and operators who build and manage data analytics pipelines Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a batch data analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Introduction to Amazon EMR Using Amazon EMR in analytics solutions Amazon EMR cluster architecture Interactive Demo 1: Launching an Amazon EMR cluster Cost management strategies Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage Storage optimization with Amazon EMR Data ingestion techniques Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR Apache Spark on Amazon EMR use cases Why Apache Spark on Amazon EMR Spark concepts Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell Transformation, processing, and analytics Using notebooks with Amazon EMR Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive Using Amazon EMR with Hive to process batch data Transformation, processing, and analytics Practice Lab 2: Batch data processing using Amazon EMR with Hive Introduction to Apache HBase on Amazon EMR Module 5: Serverless Data Processing Serverless data processing, transformation, and analytics Using AWS Glue with Amazon EMR workloads Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions Module 6: Security and Monitoring of Amazon EMR Clusters Securing EMR clusters Interactive Demo 3: Client-side encryption with EMRFS Monitoring and troubleshooting Amazon EMR clusters Demo: Reviewing Apache Spark cluster history Module 7: Designing Batch Data Analytics Solutions Batch data analytics use cases Activity: Designing a batch data analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Recordings of all past webinars run by Reel Resilience on aspects of tape and tape-recorders. for you to watch again.

The often-used phrase, 'just the receptionist', completely misrepresents the role. An excellent receptionist is a most valuable resource for any organisation. This programme has been designed specifically to deal with the essential skills necessary to represent the organisation to the best possible effect. It will also help you get the most out of your working day. There are six key reasons to take part in this workshop. It will help you: See your role in a new light Develop your communication skills Deal with different types of customer and situation Boost your confidence Cope in a pressurised environment Get more satisfaction from your working day 1 Introduction Workshop objectives and personal objectives The challenges of 21st century communication What makes an excellent point of Reception? And why is it so important? Who and where are our customers? As a customer, how do you like to be treated? What makes people feel valued? Objective and subjective aspects of customer service 'Micro moments' that shape the relationship 2 Communication on reception Definition of communication Barriers to good communication The 'recipe' of verbal, vocal and visual aspects of communication Differences between communicating face-to-face and on the telephone Communication 'leaks' The primitive human response The impact of visual communication - body language, gesture and facial expression Voice - tone, speed, volume, pitch, clarity, inflection, pacing Words - positive words and phrases compared with negative terminology Professional greetings face-to-face Steering the conversation with effective questioning 3 Telephone excellence How we use the telephone Qualities of the telephone Non-verbal communication on the telephone - what aspects can be 'seen' by the other person? Professional telephone etiquette Taking and leaving messages - key points that can help customers, colleagues and the organisation Clarifying information 4 Listening skills for accuracy and relationship building How accurate are your listening skills? What are the challenges for accurate listening? Active / empathetic listening 5 Creating a rapport by 'style flexing' Understanding how different people communicate Shaping our message to the other person so that they feel understood How changing situations can alter communication needs 6 Confidence and assertiveness Recognising different styles of behaviour - aggressive, passive and assertive Qualities of assertive communication - verbal, vocal and visual Assertive techniques - basic, persistence, negotiation / empathetic Demonstrating confidence 7 Coping in a pressurised environment Words - the most useful ones to use with stressed people and identifying the 'red rag' words Challenging situations - what do you find difficult and how do you respond? Dealing with outbursts of anger Bringing non-stop talkers back from their tangent Constructive ways to say 'no' 8 Pulling it all together Action plans Summary of key learning points

A webinar in which we explore the true cost of pointless stress and worry on our health, our happiness and our time and present the possibility of a future with more balance, more joy and better outcomes.

A free, interactive session for women, about trauma and how to heal from it.

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