8513 Network courses

A hybrid community learning event for all ORSC members and ORSC curious! We'll be using the Deep Democracy process to explore what community means to us.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

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.

Effective communication in the workplace is part and parcel of our daily lives, but not everyone is a natural.  Do you find it tough standing up in front of people? Does the thought of engaging with audiences in any setting fill you with anxiety? Is doing a remote video message to colleagues on Zoom or Teams a tough call? Do you do it regularly but need some professional guidance on whether it’s working? At CoComms we can improve every aspect of your performance and offer a range of tips and techniques to help manage these environments and keep your audience engaged and interested. Public Speaking and Presentation Training In a professional setting it’s vital to come across as dynamic, trustworthy, credible and real. You want people to trust you and in turn get behind your vision or plan or proposal. If you can achieve this you can improve your confidence, your engagement and your prospects. Our training is designed to hone your presentation skills so whether you are pitching for work, taking colleagues through change or speaking to a new audience, you can do it with a clarity and confidence that makes your messages clear and insightful. The training includes: Perfecting your slides Working to produce a clean, easy to navigate slide deck that give logic and flow to your presentation. Developing your storytelling We use our journalistic techniques to show you how to build a story to keep your audience engaged with a well-structured and entertaining presentation. Calls to Action Make sure it is clear what you want to achieve and what you want from your audience. Rehearse and Review We film and then playback a range of practical presentation exercises so we can review your performance and work to make any improvements. Conference and Panel Training The audience at a conference may be a captive one, but that doesn’t mean they are always listening and engaging with what you have to say. We can make sure your keynote speech or panel contribution is memorable, appreciated by your audience and beneficial to your business. Our training looks at preparing for and delivering a speech from start to finish and includes: Defining your big ideas What is it you want to say and what do you want your audience to remember? Develop your narrative and script How can you get across your message using storytelling. Choosing the right language How vibrant and energised language can make the difference in your speech. The tips and tricks to make sure your speech is memorable How vocabulary and delivery techniques ensure your words are heard. Controlling the message How to deal with unhelpful questions and return to the main aspects of your story. Stakeholder Communication Training Engaging effectively with stakeholders with clarity and confidence can make all the difference to your relationships. A successful “town hall” meeting can win over your sceptics, convince those who are unsure and build a common goal between your business and stakeholders. Our stakeholder communication training prepares you for these vital meetings and includes: Focusing the meeting We look at how to control the meeting so the important business is covered and how to prepare for any questions or comments you may receive. Keep control of the conversation We teach you conversational techniques to focus on the main points without being too assertive or dismissive. Rehearse and Review We use video and practical role-play exercises to assess your performance and look for ways to improve. Breaking down the information We look at how to present facts and figures without overwhelming (or boring!) your audience. Our techniques will help you narrate the message in a clear and comprehensive way. Making an impact Using our journalistic experience we will work with you to develop your presentation skills to make the biggest impact and demonstrate credibility and authority. Video Calls for Business The world has changed. Now is the time to ensure your business is changing too. Many in-person meetings, conferences, networking events and clients hosting are, for now, a thing of the past. These face-to-face interactions have been replaced by video calls, webinars and online events. So, how do you develop contacts, maintain relationships and manage your team in this new virtual world? How do you look and sound confident, be heard, and build trust and credibility through a computer screen? At CoComms, we are online communications experts and our years of experience in broadcasting mean we understand how to engage a virtual audience. Interactive and practical training We work with you through a variety of scenarios to analyse your performance on video calls. Feedback on your performance We offer supportive, positive feedback and share our tried and tested techniques so you can improve. Make Video Calls work for you Through our training you will become more confident, more productive and more dynamic on video calls. Contact us If you have a query regarding any of our services or would like to book a consultation for free initial advice and guidance please get in touch

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

Duration 5 Days 30 CPD hours This course is intended for This course is intended for: Solutions Architects who are new to designing and building cloud architectures Data Center Architects who are migrating from on-premises environment to cloud architectures Other IT/cloud roles who want to understand how to design and build cloud architectures Overview Make architectural decisions based on AWS architectural principles and best practices Use AWS services to make your infrastructure scalable, reliable, and highly available Use AWS Managed Services to enable greater flexibility and resiliency in an infrastructure Make an AWS-based infrastructure more efficient to increase performance and reduce costs Use the Well Architected Framework to improve architectures with AWS solutions This course combines Architecting on AWS and Advanced Architecting on AWS to offer a comprehensive, immersive course in cloud architecture. It covers all aspects of how to architect for the cloud over 5 days. You will learn how to design cloud architectures, starting small and working to large-scale enterprise level designs?and everything in between. Starting with the Well Architected Framework, you will be immersed in AWS services like compute, storage, database, networking, security, monitoring, automation, optimization, benefits of de-coupling applications and serverless, building for resilience, and understanding costs. Using hands-on labs, you will apply knowledge from lectures to gain skills. Course Outline The Well-Architected Framework Networking with AWS Core AWS concepts, knowledge, and services, including designing your environment and making your environment highly available Event-driven scaling Automation Decoupling Building for resilience Optimization Serverless designs Data security Advance networking topics Migration How to grow your architecture from small to extremely large Additional course details: Nexus Humans Architecting on AWS Accelerator 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 Architecting on AWS Accelerator 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 is an intermediate course for anyone with system administrative duties implementing and managing an AIX operating system in a multiuser POWER (System p) partitioned environment. Overview Install and the AIX operating system, filesets, and RedHat Package Manager (RPM) packages Perform system startup and shutdown Discuss and use system management tools such as System Management Interface Tool (SMIT) and IBM systems director console for AIX Manage physical and logical devices Discuss the purpose of the logical volume manager Perform logical volume, paging space and file system management Create and manage user administration Manage AIX user security including enhanced RBAC and implement customized access of file and directories Perform and restore system backups Utilize administrative subsystems, including cron to schedule system tasks Configure TCP/IP networking Define and run basic Workload Partitions (WPAR) Learn to install, customize, and administer the AIX operating system in a POWER (System p) partitioned environment. This course is based on AIX 7.1 running on a Power7 system managed by HMC version 7. Day 1 Introduction to IBM POWER systems, AIX and system administration AIX system management tools System startup and shutdown AIX installation Day 2 AIX software installation and maintenance System configuration and devices System storage overview Working with the Logical Volume Manager Day 3 File systems administration Paging space Backup and restore Day 4 Security and user administration: Part 1 Security and user administration: Part 2 Scheduling and time TCP/IP networking Day 5 TCP/IP networking (continued) Introduction to workload partitions Additional course details: Nexus Humans AN12 IBM Power Systems for AIX II - AIX Implementation and Administration 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 AN12 IBM Power Systems for AIX II - AIX Implementation and Administration 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 Overview Our engaging instructors and mentors are highly-experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working within in a hands-on learning environment, guided by our expert team, attendees will explore: New Features Overview Multitenant New Features Security Features Cloud Services Networking Globalization Big Data Support Database Installation and Configuration Database Tuning Backup and Recovery Oracle 19c New Features is a hands-on course that explores the newest features such as Big Data Enhancements, Security, Multitenant features, Oracle Cloud Services, Networking, and much more. Oracle is one of the leading databases in industry today. Learn what their latest flagship product has to offer from industry experts. Oracle 19c New Features Overview Introduction to Oracle 19c New Features Oracle 19c Multitenant New Features Refreshable PDB Switchover PDB Integration with Data Guard PDB Snapshot Carousel CDB Fleet Management Oracle 19c Security Features Profile Lockdown Create a User Defined Master Encryption Key Encrypted Passwords in Database Links and Data Pump Create Keystores for Pluggable Databases Datapump and Unified Auditing Schema Only Accounts Oracle 19c Cloud Services Oracle IaaS Oracle Saas Oracle PaaS Oracle 19c Networking Database Connection Manager Database Proxy Support Tenant Isolation Oracle 19c Globalization New globalization for Bind Variables New Database Local Support Additional Unicode Support Big Data Support New Analytic Support Data Mining Data Warehouse Additional Parallel Processing Support Inline External Tables Database Installation and Configuration Zero Downtime Upgrades Dry Run Command implementation New location for Password File Improved Bulk Operations Database Tuning SQL Tuning Advisor and Exadata New SQL Tuning Set API Concurrent SQL and Sql Performance Analyzer Database In Memory Features In Memory Support for External Tables In Memory Features for Analytics Oracle 19c Backup and Recovery Active Pluggable Cloning Pluggable and non Pluggable Database Migration Additional course details: Nexus Humans Oracle 19c New Features (TTOR20019) 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 Oracle 19c New Features (TTOR20019) 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 4.875 Days 29.25 CPD hours This course is intended for VMware vSphere: Install, Configure, Manage features intensive hands-on training that focuses on installing, configuring, and managing VMware vSphere. This course prepares you to administer a vSphere infrastructure for an organization of any size and forms the foundation for most otherVMware technologies in the software-defined data center. Overview Describe the software-defined data center (SDDC) Explain the vSphere components and their function in the infrastructure Describe the benefits and capabilities of VMware Skyline Install and configure ESXi hosts Deploy and configure VMware vCenter Server Appliance™ Use VMware vSphere Client™ to manage the vCenter Server inventory and the vCenter Server configuration Manage, monitor, back up, and protect vCenter Server Appliance Create virtual networks with vSphere standard switches Describe the storage technologies supported by vSphere Configure virtual storage using iSCSI and NFS storage Create and manage VMware vSphere VMFS datastores Use the vSphere Client to create virtual machines, templates, clones, and snapshots Create a content library and deploy virtual machines from templates in the library Manage virtual machine resource use Migrate virtual machines with VMware vSphere vMotion and VMware vSphere Storage vMotion Create and manage a vSphere cluster that is enabled with VMware vSphere High Availability and VMware vSphere Distributed Resource Scheduler ™ Discuss solutions for managing the vSphere life cycle Use VMware vSphere Lifecycle Manager™ to perform upgrades to ESXi hosts and virtual machines This is an official VMware IT Academy course with official courseware and labs. Course introduction Introductions and course logistics Course objectives Introduction to vSphere and the Software-Defined Data Center Explain basic virtualization concepts Describe how vSphere fits into the software-defined data center and the cloud infrastructure Explain how vSphere interacts with CPUs, memory, networks, and storage Recognize the user interfaces for accessing the vCenter Server system and ESXi hosts Describe the ESXi host architecture Navigate the Direct Console User Interface (DCUI) to configure an ESXi host Recognize ESXi host user account best practices Install an ESXi host Use VMware Host Client? to configure ESXi host settings Describe how to proactively manage your vSphere environment using VMware Skyline Virtual Machines Create and provision a virtual machine Explain the importance of VMware Tools? Install VMware Tools Identify the files that make up a VM Recognize the components of a VM Recognize virtual devices supported by a VM Describe the benefits and use cases for containers Identify the parts of a container system vCenter Server Describe the vCenter Server architecture Discuss how ESXi hosts communicate with vCenter Server Deploy and configure vCenter Server Appliance Use vSphere Client to manage the vCenter Server inventory Add data center, organizational objects, and hosts to vCenter Server Use roles and permissions to enable users to access objects in the vCenter Server inventory Back up vCenter Server Appliance Monitor vCenter Server tasks, events, and appliance health Use VMware vCenter Server© High Availability to protect a vCenter Server Appliance Configuring and Managing Virtual Networks Create and manage standard switches Describe the virtual switch connection types Configure virtual switch security, traffic-shaping, and load-balancing policies Compare vSphere distributed switches and standard switches Configuring and Managing Virtual Storage Identify storage protocols and storage device types Discuss ESXi hosts using iSCSI, NFS, and Fibre Channel storage Create and manage VMFS and NFS datastores Explain how multipathing works with iSCSI, NFS, and Fibre Channel storage Recognize the components of a VMware vSAN? configuration Virtual Machine Management Use templates and cloning to deploy new virtual machines Modify and manage virtual machines Create a content library and deploy virtual machines from templates in the library Use customization specification files to customize a new virtual machine Perform vSphere vMotion and vSphere Storage vMotion migrations Describe the Enhanced vMotion Compatibility feature Create and manage virtual machine snapshots Examine the features and functions of VMware vSphere© Replication? Describe the benefits of VMware vSphere© Storage APIs ? Data Protection Resource Management and Monitoring Discuss CPU and memory concepts in a virtualized environment Describe what overcommitment of a resource means Describe methods for optimizing CPU and memory usage Use various tools to monitor resource use Create and use alarms to report certain conditions or events vSphere Clusters Describe the functions of a vSphere DRS cluster Create a vSphere DRS cluster Monitor a vSphere cluster configuration Describe options for making a vSphere environment highly available Explain the vSphere HA architecture Configure and manage a vSphere HA cluster Examine the features and functions of VMware vSphere© Fault Tolerance Describe the function of the vSphere© Cluster Service vSphere Lifecycle Management Recognize the importance of vCenter Server Update Planner Describe how VMware vSphere© Lifecycle Manager? works Describe how to update ESXi hosts using baselines Validate ESXi host compliance using a cluster image Describe how to upgrade VMware Tools and VM hardware Describe VMware vSphere© Lifecycle Manager? and VMware vSAN? integration

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: System administrators and operators who are operating in the AWS Cloud Informational technology workers who want to increase the system operations knowledge. Overview In this course, you will learn to: Recognize the AWS services that support the different phases of Operational Excellence, a WellArchitected Framework pillar. Manage access to AWS resources using AWS Accounts and Organizations and AWS Identity and Access Management (IAM). Maintain an inventory of in-use AWS resources using AWS services such as AWS Systems Manager, AWS CloudTrail, and AWS Config. Develop a resource deployment strategy utilizing metadata tags, Amazon Machine Images, and Control tower to deploy and maintain an AWS cloud environment. Automate resource deployment using AWS services such as AWS CloudFormation and AWS Service Catalog. Use AWS services to manage AWS resources through SysOps lifecycle processes such as deployments and patches. Configure a highly available cloud environment that leverages AWS services such as Amazon Route 53 and Elastic Load Balancing to route traffic for optimal latency and performance. Configure AWS Auto Scaling and Amazon Elastic Compute Cloud auto scaling to scale your cloud environment based on demand. Use Amazon CloudWatch and associated features such as alarms, dashboards, and widgets to monitor your cloud environment. Manage permissions and track activity in your cloud environment using AWS services such as AWS CloudTrail and AWS Config. Deploy your resources to an Amazon Virtual Private Cloud (Amazon VPC), establish necessary connectivity to your Amazon VPC, and protect your resources from disruptions of service. State the purpose, benefits, and appropriate use cases for mountable storage in your AWS cloud environment. Explain the operational characteristics of object storage in the AWS cloud, including Amazon Simple Storage Service (Amazon S3) and Amazon S3 Glacier. Build a comprehensive costing model to help gather, optimize, and predict your cloud costs using services such as AWS Cost Explorer and the AWS Cost & Usage Report. This course teaches systems operators and anyone performing system operations functions how to install, configure, automate, monitor, secure, maintain and troubleshoot the services, networks, and systems on AWS necessary to support business applications. The course also covers specific AWS features, tools, andbest practices related to these functions. Module 1: Introduction to System Operations on AWS Systems operations AWS Well-Architected Framework AWS Well-Architected Tool Module 2a: Access Management Access management Resources, accounts, and AWS Organizations Module 2b: System Discovery Methods to interact with AWS services Introduction to monitoring services Tools for automating resource discovery Inventory with AWS Systems Manager and AWS Config Troubleshooting scenario Hands-On Lab: Auditing AWS Resources with AWS Systems Manager and AWS Config Module 3: Deploying and Updating Resources Systems operations in deployments Tagging strategies Deployment using Amazon Machine Images (AMIs) Deployment using AWS Control Tower Troubleshooting scenario Module 4: Automating Resource Deployment Deployment using AWS CloudFormation Deployment using AWS Service Catalog Troubleshooting scenario Hands-On Lab: Infrastructure as Code Module 5: Manage Resources AWS Systems Manager Troubleshooting scenario Hands-On Lab: Operations as Code Module 6a: Configure Highly Available Systems Distributing traffic with Elastic Load Balancing Amazon Route 53 Module 6b: Automate Scaling Scaling with AWS Auto Scaling Scaling with Spot Instances Managing licenses with AWS License Manager Troubleshooting scenario Module 7: Monitor and Maintaining System Health Monitoring and maintaining healthy workloads Monitoring distributed applications Monitoring AWS infrastructure Monitoring your AWS account Troubleshooting scenario Hands-On Lab: Monitoring Applications and Infrastructure Module 8: Data Security and System Auditing Maintain a strong identity and access foundation Implement detection mechanisms Automate incident remediation Troubleshooting scenario Hands-On Lab: Securing the Environment Module 9: Operate Secure and Resilient Networks Building a secure Amazon Virtual Private Cloud (Amazon VPC) Networking beyond the VPC Troubleshooting scenario Module 10a : Mountable Storage Configuring Amazon Elastic Block Storage (Amazon EBS) Sizing Amazon EBS volumes for performance Using Amazon EBS snapshots Using Amazon Data Lifecycle Manager to manage your AWS resources Creating backup and data recovery plans Configuring shared file system storage Module 10b: Object Storage Deploying Amazon Simple Storage Service (Amazon S3) with Access Logs, Cross-Region Replication, and S3 Intelligent-Tiering Hands-On Lab: Automating with AWS Backup for Archiving and Recovery Module 11: Cost Reporting, Alerts, and Optimization Gain AWS expenditure awareness Use control mechanisms for cost management Optimize your AWS spend and usage Hands-On Lab: Capstone lab for SysOps Additional course details: Nexus Humans Systems Operations on AWS 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 Systems Operations on AWS 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.