3800 Courses

Duration 0.5 Days 3 CPD hours This course is intended for This course is designed for students who have experience using the Windows 10 operating system and need to start using the Windows 11 operating system. Overview In this course, you will use the new and updated features of Windows 11. You will: Navigate the Windows environment. Use apps available in Windows 11. Manage available apps. Configure Windows 11 settings. As an experienced Windows© 10 user, when you are ready to move to Windows 11, you might like some guidance in using the new and updated features. This course will help you identify and use those features efficiently and effectively. Navigating the Windows 11 Environment Topic A: Log in to Windows 11 Topic B: Use the Start Menu Topic C: Use the Taskbar Using Apps Topic A: Use Built-In Apps Topic B: Use the Updated File Explorer Managing Apps Topic A: Use Virtual Desktops Topic B: Obtain Apps from the Microsoft Store Configuring Windows 11 Settings Topic A: Use the Configuration Apps Topic B: Configure Accessibility Features

Duration 4 Days 24 CPD hours This course is intended for This course is designed for technical professionals who require the skills to administer IBM© MQ queue managers on distributed operating systems, in the Cloud, or on the IBM© MQ Appliance. Overview After completing this course, you should be able to:Describe the IBM© MQ deployment optionsPlan for the implementation of IBM© MQ on-premises or in the CloudUse IBM© MQ commands and the IBM© MQ Explorer to create and manage queue managers, queues, and channelsUse the IBM© MQ sample programs and utilities to test the IBM© MQ networkEnable a queue manager to exchange messages with another queue managerConfigure client connections to a queue managerUse a trigger message and a trigger monitor to start an application to process messagesImplement basic queue manager restart and recovery proceduresUse IBM© MQ troubleshooting tools to identify the cause of a problem in the IBM© MQ networkPlan for and implement basic IBM© MQ security featuresUse accounting and statistics messages to monitor the activities of an IBM© MQ systemDefine and administer a simple queue manager cluster This course provides technical professionals with the skills that are needed to administer IBM© MQ queue managers on distributed operating systems and in the Cloud. In addition to the instructor-led lectures, you participate in hands-on lab exercises that are designed to reinforce lecture content. The lab exercises use IBM© MQ V9.0, giving you practical experience with tasks such as handling queue recovery, implementing security, and problem determination. Note: This course does not cover any of the features of MQ for z/OS or MQ for IBM© i. Course introductionIBM© MQ reviewIBM© MQ installation and deployment optionsCreating a queue manager and queuesExercise: Using commands to create a queue manager and queuesIntroduction to IBM© MQ ExplorerExercise: Using IBM© MQ Explorer to create queue managers and queuesTesting the IBM© MQ implementationExercise: Using IBM© MQ sample programs to test the configurationImplementing distributed queuingExercise: Connecting queue managersIBM© MQ clientsExercise: Connecting an IBM© MQ clientImplementing trigger messages and monitorsExercise: Implementing a trigger monitorDiagnosing problemsExercise: Running an IBM© MQ traceImplementing basic security in IBM© MQExercise: Controlling access to IBM© MQBacking up and restoring IBM© MQ messages and object definitionsExercise: Using a media image to restore a queueExercise: Backing up and restoring IBM© MQ object definitionsIntroduction to queue manager clustersExercise: Implementing a basic clusterMonitoring and configuring IBM© MQ for performanceExercise: Monitoring IBM© MQ for performanceCourse summary

Duration 1 Days 6 CPD hours This course is intended for IT professionals interested in understanding the capabilities of the MDS 9000 Series, including: Data center architects Data center engineers IT directors IT managers Network architects Network engineers Solutions architects Systems engineers Overview After taking this course, you should be able to: Describe Cisco MDS SAN features and advantages Define fixed and modular platforms Understand Cisco MDS architecture and high-availability mechanisms Identify technologies used in modern SANs Describe SAN management with Cisco Data Center Network Manager (DCNM) Explain key value-add features that distinguish Cisco MDS switches The Cisco MDS 9000 Series Switches Overview (DCMDSO) v1.5 course gives you a technical overview of how Cisco Multilayer Director Switch (MDS) 9000 Series, can be used to build highly available and scalable storage networks with advanced security and unified management. The course is for technical decision makers and IT professionals who architect, implement, and manage data center Storage Area Network (SAN) environments. In this course, you?ll learn about key capabilities of the MDS 9000 Series, including platforms, architecture, software, management, and key features that contribute to performance, high availability, flexibility, and operational simplicity of storage environments. Define Cisco MDS Platform Overview Introduction and Advantages of Cisco MDS Fixed Platforms Modular Platforms Describe Cisco MDS Architecture Store-and-Forward Architecture High Availability Redundancy Explore Cisco MDS Key Features Virtual Storage Area Networks Port Channels Slow Drain Device and Path Analysis Using Congestion Control Mechanisms Cisco DCNM SAN Insights for SAN Analytics Zoning Smart Zoning Other Differentiating Features Examine Cisco MDS Management Cisco Data Center Network Manager Additional course details: Nexus Humans Cisco MDS 9000 Series Switches Overview v1.5 (DCMDSO) 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 Cisco MDS 9000 Series Switches Overview v1.5 (DCMDSO) 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 The primary audience for this course is database developers who plan to migrate their MySQL or Postgres DB workloads to Azure SQL DB. The secondary audience for this course is MySQL/Postgres administrators to raise awareness of the features and benefits of Azure SQL DB. Overview At the end of this course, the students will have learned: Migrate on-premises MySQL to Azure SQL DB for MySQL Migrate on-premises PostgreSQL to Azure SQL DB for PostgreSQL This course will enable the students to understand Azure SQL Database, and educate the students on what is required to migrate MySQL and PostgreSQL workloads to Azure SQL Database. Migrate to Azure SQL DB for MySQL & PostgreSQL OSS databases overview Common OSS database workloads Customer challenges in migration Migrate on-premises MySQL to Azure SQL DB for MySQL Configure and Manage Azure SQL DB for MySQL Migrate on-premises MySQL to SQL DB for MySQL Application Migration Post-migration considerations Migrate on-premises PostgreSQL to Azure SQL DB for PostgreSQL Configure and Manage Azure SQL DB for PostgreSQL Migrate on-premises MySQL to SQL DB for PostgreSQL Application Migration Post-migration considerations

Duration 2 Days 12 CPD hours This course is intended for The audience for this course includes professionals who are new to Looker who are interested in leveraging Looker for data analysis, visualization, and reporting. The course is designed for individuals seeking to gain a comprehensive understanding of Looker's functionalities and apply these skills in their organizations to drive data-driven decision-making. Overview This course combines expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert facilitator, you'll explore and gain: Comprehensive understanding of Looker's platform: Gain a solid foundation in Looker's key features, functionality, and interface, enabling you to navigate and utilize the platform effectively for your data analysis and visualization needs. Mastery of LookML and data modeling: Develop proficiency in Looker's unique data modeling language, LookML, to create customized and efficient data models that cater to your organization's specific requirements. Expertise in creating insightful Explores: Learn to build, customize, and save Explores with dimensions, measures, filters, and calculated fields, empowering you to analyze your data and uncover valuable insights. Proficiency in dashboard design and sharing: Acquire the skills to design visually appealing and informative dashboards, share them with different user roles, and schedule exports to keep stakeholders informed and up-to-date. Enhanced content organization with folders and boards: Understand how to effectively use folders and boards to organize, manage, and discover content within Looker, making it easily accessible for you and your team. Optional: Advanced visualization techniques for impactful storytelling: Master advanced visualization techniques, including customizations with HTML, CSS, and JavaScript, and interactive visualizations using Looker's API, to create compelling data stories that resonate with your audience. Discover the power of data analytics and visualization with our hands-on, two-day introductory course Looker Bootcamp: Analyzing and Visualizing Data with Looker. Designed for professionals who want to unlock valuable insights from their data, this immersive training experience will guide you through Looker's cutting-edge features and provide you with the essential skills to create engaging, interactive, and insightful reports and dashboards. Our experienced trainers will take you on a journey from the fundamentals of Looker and its unique data modeling language, LookML, to advanced visualization techniques and content organization strategies, ensuring you leave the course equipped to make data-driven decisions with confidence. Throughout the course, you will have the opportunity to participate in practical exercises and workshops that will help you apply the concepts and techniques learned in real-world scenarios. You will explore the potential of Looker's Explores, dive into LookML's capabilities, and master the art of dashboard design and sharing. Learn how to organize and manage your content with folders and boards and harness the power of advanced visualization techniques to make your data come alive. Getting Started with Looker Overview of Looker and its key features Navigating the Looker interface Looker terminology and basic concepts Connecting to Data Sources Setting up and managing data connections Exploring database schemas Understanding LookML: Looker's data modeling language Creating and Customizing Explores Building and customizing Explores Adding dimensions, measures, and filters Creating calculated fields Saving and organizing Explores Data Visualization Creating visualizations using Looker's visualization library Customizing chart types, colors, and labels Displaying visualizations in dashboards Introduction to Looker's API for custom visualizations Advanced Explores and LookML LookML refresher and best practices Creating derived tables and data transformations Managing access controls and data permissions Organizing and Sharing Content with Folders and Boards Introduction to folders and boards in Looker Creating and managing folders for organizing content Setting up boards for easy content discovery Sharing folders and boards with different user roles and permissions Dashboard Design and Sharing Best practices for dashboard design Adding, arranging, and resizing visualizations Scheduling and exporting dashboard data Advanced Visualization Techniques Customizing visualizations with HTML, CSS, and JavaScript Creating interactive visualizations using Looker's API Integrating Looker visualizations with other tools Hands-on Workshop and Project Participants work on a guided project to apply the skills learned Trainer provides individual support and guidance Project Presentations, Q&A, and Training Wrap-up Additional course details: Nexus Humans Looker Bootcamp: Analyzing and Visualizing Data with Looker (TTDVLK02) 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 Looker Bootcamp: Analyzing and Visualizing Data with Looker (TTDVLK02) 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 Software Engineers Overview The objective of this course is to learn the key language concepts to machine learning, Spark MLlib, and Spark ML. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume.

Duration 3 Days 18 CPD hours This course is intended for Individuals preparing for the Cisco Customer Success ManagerSpecialist certification Individuals who have experience working with customers to determine, measure, and deliver business outcomes through the implementation of technology Overview After taking this course, you should be able to: Describe the role of the Customer Success Manager Describe the tools that the Customer Success Manager uses to ensure customer experience Describe the lifecycle approach to customer experience The Cisco Customer Success Manager (DTCSM) v2.2 course gives you the confidence and competence to fulfill the Customer Success Manager (CSM) role successfully, helping your customers realize value from their solutions and achieve their business outcomes. The course offers experiential learning through practical exercises using situations based on real-life use cases and case studies. In this highly interactive course, you can practice and gain confidence in fulfilling core tasks using best-practice tools and methodologies while receiving feedback from the facilitator and your peers.This course is based on understanding the customer lifecycle and how to optimize that journey, increasing the value realized by the customer, and maximizing your likelihood to maintain their loyalty and renew or expand their business opportunities. The course helps you prepare for the 820-605 Cisco Customer Success Manager (CSM) exam. By passing this exam, you earn the Cisco Customer Success Manager Specialist certification. Course Outline Transition to Subscription Economy Customer and Industry Trends Defining Customer Success and the CSM Role Engaging the Customer for Success Engaging the Customer for Success Addressing Barriers Customer Success Management Activities Success Plan Elements Customer Success Management Activities Additional course details: Nexus Humans Cisco Customer Success Manager v2.2 (DTCSM) 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 Cisco Customer Success Manager v2.2 (DTCSM) 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 Data Warehouse AdministratorDatabase AdministratorsDatabase DesignersSupport EngineerTechnical Administrator Overview Monitor the DatabaseManage Database PerformanceImplement Database AuditingConfigure the Database Instance Such That Resources Are Appropriately Allocated Among Sessions and TasksSchedule Jobs to Run Inside or Outside of the DatabaseConfigure Oracle Net ServicesConfigure your Database For Backup and Recovery OperationsDescribe Oracle Database ArchitectureManage the Oracle Database InstanceManage Oracle Database Storage structuresCreate and Administer User Accounts The Oracle Database 12c: Administration Workshop will teach you about the Oracle Database architecture. You will discover how to effectively manage an Oracle Database instance, configure the Oracle Network Environment and perform database maintenance. The Oracle Database 12c: Administration Workshop will teach you about the Oracle Database architecture. You will discover how to effectively manage an Oracle Database instance, configure the Oracle Network Environment and perform database maintenance.

Duration 1 Days 6 CPD hours This course is intended for The audience for this course includes professionals who are new to Looker who are interested in leveraging Looker for data analysis, visualization, and reporting. The course is designed for individuals seeking to gain a comprehensive understanding of Looker's functionalities and apply these skills in their organizations to drive data-driven decision-making. Overview Working in a hands-on learning environment led by our expert facilitator, you'll explore and gain: Solid foundation in Looker's platform: Acquire a comprehensive understanding of Looker's key features, functionality, and interface, enabling you to effectively utilize the platform for your data analysis and visualization needs. Proficiency in LookML and data modeling: Develop essential skills in Looker's unique data modeling language, LookML, to create efficient and customized data models tailored to your organization's specific requirements. Expertise in creating Explores: Learn how to build, customize, and save Explores with dimensions, measures, filters, and calculated fields, empowering you to analyze your data and uncover valuable insights in a short amount of time. Mastery of dashboard design and visualization: Gain the skills to design visually appealing and informative dashboards, create various types of visualizations, and customize them to effectively communicate your data story. Improved content organization with folders and boards: Understand how to effectively use folders and boards in Looker to organize, manage, and discover content, making your data insights easily accessible for you and your team. Looker Basics: Quick Start to Analyzing and Visualizing Data using Looker is a one day, hands-on course designed to equip professionals from a variety of backgrounds with the knowledge and skills needed to harness the full potential of their data using Looker's powerful platform. With the guidance of our expert trainers, you will gain a basic understanding of Looker's features, enabling you to create visually engaging, interactive, and insightful reports and dashboards to drive informed decision-making. Throughout this interactive workshop, you will explore Looker's key functionalities, including connecting to data sources, mastering LookML, building custom Explores, and designing captivating dashboards. With about 40% of the course dedicated to hands-on labs and a guided project, you will have ample opportunity to apply the skills you've learned in real world scenarios. Don't miss this opportunity to elevate your data analysis and visualization capabilities, enhance your professional skill set, and unlock the power of data-driven decision making. Getting Started with Looker Overview of Looker and its key features Navigating the Looker interface Connecting to Data Sources and LookML Basics Setting up and managing data connections Exploring database schemas Understanding LookML: Looker's data modeling language Creating and Customizing Explores Building and customizing Explores Adding dimensions, measures, and filters Creating calculated fields Data Visualization and Dashboard Design Creating visualizations using Looker's visualization library Customizing chart types, colors, and labels Displaying visualizations in dashboards Organizing Content with Folders and Boards Introduction to folders and boards in Looker Creating and managing folders for organizing content Setting up boards for easy content discovery Hands-on Workshop and Project Participants work on a guided project to apply the skills learned Wrap-up and Q&A Additional course details: Nexus Humans Looker Basics: Quick Start to Analyzing and Visualizing Data using Looker (TTDVLK01) 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 Looker Basics: Quick Start to Analyzing and Visualizing Data using Looker (TTDVLK01) 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 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