5467 Software courses delivered Online

Duration 5 Days 30 CPD hours This course is intended for This course is designed for students who want to learn the R programming language, particularly students who want to leverage R for data analysis and data science tasks in their organization. The course is also designed for students with an interest in applying statistics to real-world problems. A typical student in this course should have several years of experience with computing technology, along with a proficiency in at least one other programming language. Overview In this course, you will use R to perform common data science tasks.You will: Set up an R development environment and execute simple code. Perform operations on atomic data types in R, including characters, numbers, and logicals. Perform operations on data structures in R, including vectors, lists, and data frames. Write conditional statements and loops. Structure code for reuse with functions and packages. Manage data by loading and saving datasets, manipulating data frames, and more. Analyze data through exploratory analysis, statistical analysis, and more. Create and format data visualizations using base R and ggplot2. Create simple statistical models from data. In our data-driven world, organizations need the right tools to extract valuable insights from that data. The R programming language is one of the tools at the forefront of data science. Its robust set of packages and statistical functions makes it a powerful choice for analyzing data, manipulating data, performing statistical tests on data, and creating predictive models from data. Likewise, R is notable for its strong data visualization tools, enabling you to create high-quality graphs and plots that are incredibly customizable. This course will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business. Lesson 1: Setting Up R and Executing Simple Code Topic A: Set Up the R Development Environment Topic B: Write R Statements Lesson 2: Processing Atomic Data Types Topic A: Process Characters Topic B: Process Numbers Topic C: Process Logicals Lesson 3: Processing Data Structures Topic A: Process Vectors Topic B: Process Factors Topic C: Process Data Frames Topic D: Subset Data Structures Lesson 4: Writing Conditional Statements and Loops Topic A: Write Conditional Statements Topic B: Write Loops Lesson 5: Structuring Code for Reuse Topic A: Define and Call Functions Topic B: Apply Loop Functions Topic C: Manage R Packages Lesson 6: Managing Data in R Topic A: Load Data Topic B: Save Data Topic C: Manipulate Data Frames Using Base R Topic D: Manipulate Data Frames Using dplyr Topic E: Handle Dates and Times Lesson 7: Analyzing Data in R Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Identify Missing Values Lesson 8: Visualizing Data in R Topic A: Plot Data Using Base R Functions Topic B: Plot Data Using ggplot2 Topic C: Format Plots in ggplot2 Topic D: Create Combination Plots Lesson 9: Modeling Data in R Topic A: Create Statistical Models in R Topic B: Create Machine Learning Models in R

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 1 Days 6 CPD hours Apple?s Keynote is the equivalent of Microsoft?s PowerPoint. With it?s powerful set of tools and effects, Keynote makes it easy to create stunning presentations. In this one-day class you will learn how to design and customize slides, add media and music, animate text and images, record voice over narration and the best tips and tricks for presenting the final presentation. Course covers working with a Mac, iPhone and/or iPad and demonstrates how to collaborate in real time with other users Creating a Presentation Opening Keynote Choosing a Theme and Slide Size Selecting a Master Slide Outlining a Presentation Using the Inspector Working with the Format Bar Pasting Text into an Outline Formatting Text Customizing a Slide Layout Copying Styles Between Slides Fixing Spelling Errors Working in Outline View Reordering Slides Creating Object Effects Dragging Files to Create New Slides Using the Light Table Creating a Custom Theme Creating an Empty Theme Creating Backgrounds and Formatting Text Creating a Title Slide Creating a Master Slide Saving and Sharing Themes Applying a Custom Theme Dragging Files to Create New Slides Using the Light Table Working with Tables and Charts Tables and Charts Working with Tables and Charts Chart and Table options Understanding Axis and Series 2D and 3D Charts Animating Tables and Charts Adding content from Microsoft Office or PDF Files Adding Media to Your Presentation Adding Photos and Graphics Enhancing Photos in Keynote Customizing Photo or Graphic Layouts Making Part of a Photo or Graphic Transparent Masking Photos and Shapes Instant Alpha Adding Hyperlinks and Navigation Adding a Chart or Table Adding Audio or Soundtrack Adding a Global Transition Adding Video and Animation Creating Builds to Reveal Text Creating a Sequence Build to Reveal a Table Creating a Smart Build Creating Custom Animation Animating Charts Animating Your Presentation Previewing the Presentation 2D and 3D Transitions Between Slides Creating Object Effects Running and Pausing your Presentation Animating a Title Slide Adding HyperLinks to your Presentation Using Magic Move Recording a Narrated, Self Playing Presentation Rehearsing and Delivering Your Presentation Reviewing your Presentation Adding Comments to your Presentation Adding and Printing Presenter Notes Rehearsing your Presentation Creating a Self-running Slideshow Troubleshooting your Presentation Indexing with Spotlight Importing from PowerPoint Animating a Title Slide Cleaning Up a Presentation Enhancing a Presentation Using an iOS Device as a Remote Control - Sharing Your Presentation Printing handouts Export for Email Exporting to PDFs Exporting to PowerPoint Exporting to Quicktime Sending to YouTube or the web Exporting Export For Email, PDFs Uploading to iCloud or Moving between Computer and iCloud Exporting to PowerPoint Exporting to QuickTime Sending to YouTube Troubleshooting & Cleaning Up Your PresentationTips and Tricks Working with Keynote on an iOS mobile device Additional course details: Nexus Humans Apple Keynote 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 Apple Keynote 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 day-long workshop gives participants a thorough understanding of the iPad iOS operating system. This course is designed for both those who want to learn more about their iPads, those who work in business environments and who want to integrate the iPad into their existing company?s infrastructure, as well as personnel who are responsible for supporting other iPad users. Setting Up The iPad iPad Essentials The Home Screen Launching and Running Apps Changing Screen Orientation Locking the Rotation The Control Center Creating Folders Accessibility and Voice Over Settings General Settings Parameters Passcode Setting Up Notifications Location Services iCloud and Synching your iPad Other Application Settings Multi-Touch Gestures Tap, Touch and Hold Drag, Flick and Swipe Pinch, Rotate and Shake Switching Between Applications Using the Apple Applications Showing and Hiding Applications Closing Documents vs. Quitting Applications Working With Documents Type, Select, Cut, Copy, Paste and Replace Understanding the iPad Keyboard Opening Pages, Numbers and Keynote Accessing Files and Documents Copying files between the iPad and Computer Working with Microsoft Office Connecting To The Internet WI-FI and Bluetooth Devices Through Servers Browsing and Searching The Web Enterprise Network The iPad In Business iOS Security Deployment Seamless Integration Mobile Device Management Printing with AirPrint Creating Passcodes Working with Photos and Camera Photos and Video Recording Video Integrating Photos or Video Into Documents or Presentations Mirroring Video Finding and Installing Apps The App Store Apps for Enterprise Installing and Deleting Apps Resetting the iPad Connecting and Mirroring with the iPhone Battery Issues Tips for Improving Battery Use Rebooting the iPad Hidden Keystrokes Troubleshooting Connectivity Issues ReInstalling Apps Preserving Batter Power Accessibility Functions Additional course details: Nexus Humans iPad For Business 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 iPad For Business 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 geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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 0.5 Days 3 CPD hours This course is intended for This course is intended for: Line of Business (LoB) owners, IT leaders, and executives Overview In this course, you will learn to: Explain the role of information technology (IT) in an organization for business transformation Explain the customer value proposition for using the cloud across industries Define key characteristics of cloud computing Explain the cloud business model Identify key security practices of cloud computing Frame the cloud business value using the Cloud Value Framework In this course, you will learn the fundamental concepts of cloud computing and how a cloud strategy can help companies meet business objectives. It explores the advantages and possibilities of cloud computing. It also introduces addresses concepts such as security and compliance to help facilitate better discussions with line of business (LOB) professionals, information technology (IT) LoB, IT leaders, and executives. Module 1: Course Introduction Course Introduction Module 2: Information Technology for Business Transformation Role of IT in an organization for business transformation Brief history of IT Legacy approach to IT What drives customers to move from traditional infrastructure to the cloud Module 3: Cloud Computing Define cloud computing Key characteristics of cloud technology The cloud business model Key security practices within the cloud Module 4: Business Value of the Cloud The customer value proposition Identify who is using cloud computing Industry trends Customer examples Module 5: The Cloud Value Framework Introduction to the Cloud Value Framework Cost Savings Staff Productivity Operational Resilience Business Agility Module 6: Business Value Activity Business Value Activity Additional course details: Nexus Humans AWS Cloud Essentials for Business Leaders 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 AWS Cloud Essentials for Business Leaders 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

Duration 1 Days 6 CPD hours This course is intended for Learners taking this course are interested in employee experiences or Microsoft Viva and want to learn how to assess, plan, strategize, design, and manage digital employee experiences that use Microsoft Viva, Microsoft Teams, SharePoint, and Power Platform. A learner in this role will collaborate with multiple teams to scope, design, and implement new digital employee experiences, such as onboarding, career and skill development, rewards and recognition, employee wellbeing, and employee retention. Learners should have a foundational understanding of Microsoft technologies, including Microsoft 365, Teams, SharePoint, and a deep understanding of Microsoft Viva features and capabilities. They may have experience in one or more of the following disciplines: human resources, people development, change management, information technology, or culture development. Overview By the end of this module, you'll be able to: Evaluate existing systems and identify requirements Identify stakeholders and users Recommend employee experience solutions and strategies Describe the four experience areas of Connection, Growth, Purpose, and Insights supported by Viva. Explain what Microsoft Viva apps are. Identify resources needed to set up each Viva app. Create an adoption plan to use Viva to solve business scenarios for the four employee experience areas of Connection, Insight, Purpose, and Growth. Describe the main features of Viva Connections List technical requirements/prerequisites for Viva Connections implementation Explain the differences between desktop and mobile experiences Identify 2-3 business use cases for Viva Connections Identify key stakeholders for the deployment of Viva Connections Align and prioritize scenarios for Viva Connections Plan and design for the Dashboard, the Feed, and Resources by scenarios and audiences Consider how your organization will scale adoption Assess your organization's existing learning experiences. Plan and strategize for Viva Learning. Coordinate the implementation of Viva Learning. Recommend an adoption strategy for Viva Learning. In this course, you'll learn how to bring people together to create an optimal employee experience that enables your organization to improve productivity, develop empathetic leadership, and transform how employees feel about their work. In your organization today, are people being treated well, or are their needs neglected? Are your teams aligned on goals with a sense of purpose? Are you driving the business outcomes that you need? The Microsoft Viva employee experience platform provides the infrastructure to create the culture of trust, collaboration, well-being, and active listening that you envision. This training course will provide Microsoft Employee Experience Platform Specialists with a comprehensive overview of Microsoft Viva, as well as Microsoft 365, Teams, and SharePoint. It will cover how to identify requirements for designing experiences for employee onboarding, career and skill development, rewards and recognition, compensation and benefits, employee wellbeing, and employee retention. It will also cover how to design solutions to meet these requirements, and how to collaborate with senior executive leadership, human resources, IT, adoption and change management, and learning and organizational development departments. Finally, it will cover how to continuously improve employee experiences based on data-driven insights and feedback. Design digital employee experiences Introduction Case study - Tailwind Traders Evaluate current employee experiences Consider employee privacy and data requirements Assemble business stakeholders and define goals Explore Viva experience areas Understand Viva licensing Knowledge check Summary and resources Introduction to the Microsoft Viva suite Introduction to Microsoft Viva Understand Viva apps Get started with Microsoft Viva Use Viva to keep everyone informed, included, and inspired Use Viva to get actionable insights to foster well-being and productivity Use Viva to align people's work to team and organization goals Use Viva to help employees learn, grow, and succeed Knowledge check Summary Introduction to Viva Connections Introduction What do users experience? When to use Viva Connections? What technical requirements must be met to deploy Viva Connections? Knowledge check Summary Plan for Viva Connections Introduction Build your team and meet requirements Analyze tasks and scenarios for Viva Connections Plan for Viva Connections Dashboard, Feed and Resources Plan to announce, launch, and scale adoption Knowledge check Summary Design skilling and growth experiences with Viva Learning Introduction Case study - Tailwind Traders Plan for Viva Learning Assemble Viva Learning admins and stakeholders Understand content sources with Viva Learning Coordinate setup and configuration of Viva Learning Develop adoption strategies for Viva Learning Develop an org-wide learning culture Knowledge check Summary and resources Additional course details: Nexus Humans MS-080T00: Employee Experience Platform Specialist 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 MS-080T00: Employee Experience Platform Specialist 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 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 3 Days 18 CPD hours This course is intended for This class is designed for individuals who are (or will soon be) supporting a Salesforce implementation in a decision-making capacity. This includes, but is not limited to, business analysts, IT managers, project managers, executive leaders, and executive sponsors. This class is not recommended for individuals tasked with solution-building. Overview When you complete this course, you will be able to: Identify key stakeholders needed for a successful Salesforce implementation. Describe the Salesforce data model as it relates to Customer 360, Salesforce Clouds, and the Salesforce Platform. Communicate the appropriate security measures needed to control org and data access. Discuss which standard or custom objects and applications should be implemented based on specific requirements and use cases. Effectively strategize how to migrate data into your Salesforce org while maintaining high data quality. Understand Salesforce automation tools and how they solve for various business challenges. Analyze Salesforce data with Reports and Dashboards. Navigate the key phases and milestones of a Salesforce implementation. Explore Salesforce features and functionality and gain the knowledge to make Salesforce implementation decisions with confidence. In this 3-day, heavily discussion-based class, learn about standard and custom objects and applications, data management, data visualization, flow automation tools, security mechanisms, and more. Successfully navigate the key phases and milestones of a Salesforce implementation, effectively communicate business needs, and provide directives to team members tasked with solution-building to deliver a robust Salesforce solution that achieves business goals. Salesforce Data Model Discover the Customer 360 Platform Examine Salesforce Clouds Navigate the Salesforce Platform Review the Salesforce Platform Data Model Understand Data Visualization Security & Access Create Users Access the Org Control Data Objects & Applications Review Standard Objects Understand Custom Objects Explore Standard Applications Discover Custom Applications Salesforce Customizations Work with Fields Design Page Layouts Understand Record Types Review Dynamic Capabilities Successful Data Management Determine Data Strategy Create Data Ensure Data Quality Process Automation Streamline Business Processes Using Automation Tools Learn Purpose-Driven Automation Automate With Flow Data Analysis Using Reports & Dashboards Organize Reports and Dashboards Build Reports Create Dashboards Create an Analytics Strategy Adoption & Continued Improvement Adopt Your Implementation Evaluate Continued Improvements Additional course details: Nexus Humans Understand and Drive Your Salesforce Implementation ( BSX101 ) 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 Understand and Drive Your Salesforce Implementation ( BSX101 ) 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.