5595 Computing & IT courses delivered Online

Duration 5 Days 30 CPD hours This course is intended for Technical Administrator Java EE Developer System Administrator Overview Configure WebLogic Server's authentication provider Deploy applications to WebLogic Server Backup and restore a WebLogic Server domain Create a WebLogic Server domain Configure and monitor WebLogic Server Configure WebLogic Server database resources Create and configure a WebLogic Server cluster Install WebLogic Server 12c This Oracle WebLogic Server 12c: Administration I training teaches administrators to install and configure Oracle WebLogic Server 12c. It gives administrators an overview of the basic concepts and architecture of WebLogic Server. This Oracle WebLogic Server 12c: Administration I training teaches administrators to install and configure Oracle WebLogic Server 12c. It gives administrators an overview of the basic concepts and architecture of WebLogic Server.

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 1 Days 6 CPD hours This course is intended for This course is designed for students who already have experience creating Modern SharePoint sites and populating them with content, who want to learn advanced features to extend SharePoint's capabilities, make information easier to find and manage, use SharePoint features to improve governance and compliance, and improve the security of information and services within the SharePoint environment. Overview In this course, you will perform advanced site-building and administration tasks. You will: Create a custom site template to reduce the time spent creating similarly configured SharePoint sites. Configure managed metadata, including custom term sets, content types, and metadata-based navigation. Control access through permissions. Improve overall security of sites, lists, libraries, folders, list items, and documents. Microsoft© SharePoint©, in conjunction with the Microsoft 365? productivity and office automation suite, provides tools to create and manage a corporate intranet, facilitate content sharing and collaboration, and enable users to create, access, store, and track documents and data in a central location.Users who already have experience as SharePoint site members and owners may be ready to move on to more advanced site-building tasks such as using custom site templates, custom themes, applying advanced permissions settings, improving security, and preparing sites to support governance and compliance.Advanced site builders may be ready to undertake more advanced site management tasks, working in conjunction with their SharePoint Administrator to create and use custom site templates, term sets and metadata, manage information governance and compliance, and get deeper into SharePoint security configuration.This course focuses on these advanced site-building and administration tasks. Lesson 1: Creating Custom Site Templates Topic A: Prepare a Site Script Topic B: Generate and Use a Custom Site Template Lesson 2: Managing Content Services Topic A: Plan and Configure Managed Metadata Topic B: Create and Manage Content Types Topic C: Use Managed Metadata for Navigation and Filtering Lesson 3: Controlling Access Through Permissions Topic A: Assign Permissions Topic B: Manage Permissions Inheritance Lesson 4: Improving Security Topic A: Manage Access at the Site Level Topic B: Manage Access at the Tenant Level

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 4 Days 24 CPD hours This course is intended for This basic course is intended for anyone who requires basic AIX/UNIX user skills to be able to work in an AIX environment. This course is also a prerequisite for many courses in the AIX Systems Administration curriculum. Overview Log in to an AIX system and set a user password Use AIX online documentation Manage AIX files and directories Describe the purpose of the shell Use the vi editor Execute common AIX commands and manage AIX processes Customize the working environment Use common AIX utilities Write simple shell scripts Use the AIXWindows Environment Use the Common Desktop Environment This course enables you to perform everyday tasks using the AIX operating system. Day 1 Introduction to AIX Using the System AIX Documentation Files and Directories Using Files Day 2 File Permissions The vi Editor Shell Basics Using Shell Variables Day 3 Processes Controlling Processes Customizing the User Environment AIX Utilities, Part I AIX Utilities, Part I (Continued) AIX Utilities, Part II Day 4 AIX Utilities, Part II (Continued) Additional Shell Features The AIX Graphical User Interface

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 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 5 Days 30 CPD hours This course is intended for The audience for this course includes enterprise-level messaging administrators on Exchange Server. IT generalists and helpdesk professionals who want to learn about Exchange Server may also take this course. Students taking this course are expected to have at least two years of experience working in the IT field-typically in the areas of Windows Server administration, network administration, helpdesk, or system administration. They are also expected to have some experience with Exchange Server concepts but previous experience managing Exchange Server is not a requirement. Overview After completing this course, students will be able to: Deploy Exchange Server. Plan and configure storage for Exchange Server. Create and manage various recipient objects in Exchange Server. Perform recipient management and Exchange server management tasks by using Exchange Server cmdlets. Deploy Client Access services in Exchange Server. Manage high availability in Exchange Server. Implement disaster recovery for Exchange Server. Configure and manage message transport in Exchange Server. Configure message security in Exchange Server. Monitor and troubleshoot Exchange Server. Configure Exchange Server role-based access control permissions and configure audit logging for both administrators and users. Implement and manage integration with Exchange Online. This course teaches IT professionals how to administer and support Exchange Server. The course covers how install and configure Exchange Server. It also covers how to manage mail recipients and public folders, including how to perform bulk operations by using Exchange Management Shell. In addition, the course covers how to manage client connectivity, message transport and hygiene, and highly available Exchange Server deployments. It also covers how to implement disaster recovery solutions. Finally, the course covers how to maintain and monitor an Exchange Server deployment and how to administer Exchange Online in a Office 365 deployment. Deploying Microsoft Exchange Server 2016 Overview of Exchange Server Exchange Server architecture Requirements for Exchange Server Deploying Exchange Server Exchange Server Exchange Server Management Tools Lab : Deploying Exchange Server Managing Exchange Server 2016 storage Exchange Server mailbox databases Exchange Server storage Configuring Exchange Server mailbox databases and storage Lab : Configuring Exchange Server storage Managing recipient objects Managing user mailboxes Managing other types of mailboxes Managing other recipients objects Configuring policies and address lists Lab : Managing recipient objects Lab : Configuring address lists and policies Managing recipients and Exchange servers by using Exchange Server cmdlets Overview of the Exchange Management Shell Managing Exchange Servers by using Exchange Management Shell cmdlets Managing Exchange servers by using scripts Lab : Managing Exchange Server and recipient objects by using Exchange Management Shell Implementing client connectivity Configuring client access services Managing client access services Client connectivity in Exchange Server Configuring Outlook on the web Configuring mobile messaging Lab : Configuring client access services Lab : Deploying and configuring client access services on Exchange Server Managing high availability in Exchange Server High availability on Exchange Server Configuring highly available mailbox databases Configuring high availability of Client Access services Lab : Implementing DAGs Lab : Implementing and testing high availability Implementing disaster recovery for Exchange Server Implementing Exchange Server backup Implementing Exchange Server recovery Lab : Backing up Exchange Server data Lab : Restoring Exchange Server data Configuring and managing message transport Overview of message transport Configuring message transport Managing transport rules Lab : Configuring and managing message transport Configuring message security Deploying and managing an Edge Transport server for message security Implementing an antivirus solution for Exchange Server Implementing an antispam solution for Exchange Server Lab : Configuring message security in Exchange Server Monitoring and troubleshooting Exchange Server Monitoring Exchange Server Troubleshooting Exchange Server Lab : Monitoring and troubleshooting Exchange Server Securing and maintaining Exchange Server Securing Exchange Server by using RBAC Configuring audit logging in Exchange Server Maintaining Exchange Server Lab : Securing and maintaining Exchange Server Implementing and managing Exchange Online deployments Overview of Exchange Online and Office 365 Managing Exchange Online Implementing the migration to Exchange Online Managing a hybrid environment Lab : Managing Exchange Online Additional course details: Nexus Humans 20345-1 Administering Microsoft Exchange Server 2016/2019 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 20345-1 Administering Microsoft Exchange Server 2016/2019 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 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 2 Days 12 CPD hours This course is intended for There is no specific prerequisite for the CDRP© course. However, participants who have at least three years' experience in a data centre and/or IT infrastructures will be best suited. Overview After completion of the course, the participant will be able to: 1. Understand the different standards and methodologies for risk management and assessment 2. Establish the required project team for risk management 3. Perform the risk assessment, identifying current threats, vulnerabilities and the potential impact based on customised threat catalogues 4. Report on the current risk level of the data centre both quantitative and qualitative 5. Anticipate and minimise potential financial impacts 6. Understand the options for handling risk 7. Continuously monitor and review the status of risk present in the data centre 8. Reduce the frequency and magnitude of incidents 9. Detect and respond to events when they occur 10. Meet regulatory and compliance requirements 11. Support certification processes such as ISO/IEC 27001 12. Support overall corporate and IT governance Introduction to Risk Management Risk management concepts Senior management and risk Enterprise Risk Management (ERM) Benefits of risk management Data Centre Risk and Impact Risk in facility, power, cooling, fire suppression, infrastructure and IT services Impact of data centre downtime Main causes of downtime Cost factors in downtime Standards, Guidelines and Methodologies ISO/IEC 27001:2013, ISO/IEC 27005:2011, ISO/IEC 27002:2013 NIST SP 800-30 ISO/IEC 31000:2009 SS507:2008 ANSI/TIA-942 Other methodologies (CRAMM, EBIOS, OCTAVE, etc.) Risk Management Definitions Asset Availability/Confidentiality/Integrity Control Information processing facility Information security Policy Risk Risk analysis/Risk assessment/Risk evaluation/ Risk treatment Threat/Vulnerability Types of risk Risk Assessment Software The need for software Automation Considerations Risk Management Process The risk management process Establishing the context Identification Analysis Evaluation Treatment Communication and consultation Monitoring and review Project Approach Project management principles Project management methods Scope Time Cost Cost estimate methods Context Establishment General considerations Risk evaluation, impact and acceptance criteria Severity rating of impact Occurrence rating of probability Scope and boundaries Scope constraints Roles & responsibilities Training, awareness and competence Risk Assessment - Identification The risk assessment process Identification of assets Identification of threats Identification of existing controls Identification of vulnerabilities Identification of consequences Hands-on exercise: Identification of assets, threats, existing controls, vulnerabilities and consequences Risk Assessment - Analysis and Evaluation Risk estimation Risk estimation methodologies Assessment of consequences Assessment of incident likelihood Level of risk estimation Risk evaluation Hands-on exercise: Assessment of consequences, probability and estimating level of risk Risk Treatment The risk treatment process steps Risk Treatment Plan (RTP) Risk modification Risk retention Risk avoidance Risk sharing Constraints in risk modification Control categories Control examples Cost-benefit analysis Control implementation Residual risk Communication Effective communication of risk management activities Benefits and concerns of communication Risk Monitoring and Review Ongoing monitoring and review Criteria for review Risk scenarios Risk assessment approach Data centre site selection Data centre facility Cloud computing UPS scenarios Force majeure Organisational shortcomings Human failure Technical failure Deliberate acts Exam: Certified Data Centre Risk Professional Actual course outline may vary depending on offering center. Contact your sales representative for more information.