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Duration 5 Days 30 CPD hours This course is intended for Network designers Network administrators Network engineers Systems engineers Data center engineers Consulting systems engineers Technical solutions architects Field engineers Cisco integrators and partners Server administrator Network manager Overview After taking this course, you should be able to: Implement routing and switching protocols in Data Center environment Implement overlay networks in data center Introduce high-level Cisco Application Centric Infrastructure (Cisco ACI™) concepts and Cisco Virtual Machine manager (VMM) domain integration Describe Cisco Cloud Service and deployment models Implement Fibre Channel fabric Implement Fibre Channel over Ethernet (FCoE) unified fabric Implement security features in data center Implement software management and infrastructure monitoring Implement Cisco UCS Fabric Interconnect and Server abstraction Implement SAN connectivity for Cisco Unified Computing System™ (Cisco UCS) Describe Cisco HyperFlex™ infrastructure concepts and benefits Implement Cisco automation and scripting tools in data center Evaluate automation and orchestration technologies The Implementing and Operating Cisco Data Center Core Technologies (DCCOR) v1.1 course helps you prepare for the Cisco© CCNP© Data Center and CCIE© Data Center certifications for advanced-level data center roles. In this course, you will master the skills and technologies you need to implement data center compute, LAN and SAN infrastructure. You will also learn the essentials of automation and security in data centers. You will gain hands-on experience deploying, securing, operating, and maintaining Cisco data center infrastructure including: Cisco MDS Switches and Cisco Nexus Switches; Cisco Unified Computing System? (Cisco UCS©) B-Series Blade Servers, and Cisco UCS C-Series Rack Servers. Implementing Data Center Switching Protocols Spanning Tree Protocol Port Channels Overview Implementing First-Hop Redundancy Protocols Hot Standby Router Protocol (HSRP) Overview Virtual Router Redundancy Protocol (VRRP) Overview Implementing Routing in Data Center Open Shortest Path First (OSPF) v2 and Open Settlement Protocol (OSP) v3 Border Gateway Protocol Implementing Multicast in Data Center IP Multicast in Data Center Networks Internet Group Management Protocol (IGMP) and Multicast Listener Discovery (MLD) Implementing Data Center Overlay Protocols Cisco Overlay Transport Virtualization Virtual Extensible LAN Implementing Network Infrastructure Security User Accounts and Role Based Access Control (RBAC) Authentication, Authorization, and Accounting (AAA) and SSH on Cisco NX-OS Describing Cisco Application-Centric Infrastructure Cisco ACI Overview, Initialization, and Discovery Cisco ACI Management Describing Cisco ACI Building Blocks and VMM Domain Integration Tenant-Based Components Cisco ACI Endpoints and Endpoint Groups (EPG) Describing Packet Flow in Data Center Network Data Center Traffic Flows Packet Flow in Cisco Nexus Switches Describing Cisco Cloud Service and Deployment Models Cloud Architectures Cloud Deployment Models Describing Data Center Network Infrastructure Management, Maintenance, and Operations Time Synchronization Network Configuration Management Explaining Cisco Network Assurance Concepts Need for Network Assurance Cisco Streaming Telemetry Overview Implementing Fibre Channel Fabric Fibre Channel Basics Virtual Storage Area Network (VSAN) Overview Implementing Storage Infrastructure Services Distributed Device Aliases Zoning Implementing FCoE Unified Fabric Fibre Channel over Ethernet Describing FCoE Implementing Storage Infrastructure Security User Accounts and RBAC Authentication, Authorization, and Accounting Describing Data Center Storage Infrastructure Maintenance and Operations Time Synchronization Software Installation and Upgrade Describing Cisco UCS Server Form Factors Cisco UCS B-Series Blade Servers Cisco UCS C-Series Rack Servers Implementing Cisco Unified Computing Network Connectivity Cisco UCS Fabric Interconnect Cisco UCS B-Series Connectivity Implementing Cisco Unified Computing Server Abstraction Identity Abstraction Service Profile Templates Implementing Cisco Unified Computing SAN Connectivity iSCSI Overview Fibre Channel Overview Implementing Unified Computing Security User Accounts and RBAC Options for Authentication Introducing Cisco HyperFlex Systems Hyperconverged and Integrated Systems Overview Cisco HyperFlex Solution Describing Data Center Unified Computing Management, Maintenance, and Operations Compute Configuration Management Software Updates Implementing Cisco Data Center Automation and Scripting Tools Cisco NX-OS Programmability Scheduler Overview Describing Cisco Integration with Automation and Orchestration Software Platforms Cisco and Ansible Integration Overview Cisco and Puppet Integration Overview Describing Cisco Data Center Automation and Orchestration Technologies (Self-study) Power On Auto Provisioning Cisco Data Center Network Manager Overview Additional course details: Nexus Humans Cisco Implementing Cisco Data Center Core Technologies v1.1 (DCCOR) 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 Implementing Cisco Data Center Core Technologies v1.1 (DCCOR) 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 Candidates for this exam are IT professionals who perform installation, configuration, general local management and maintenance of Windows 10 core services. The Modern Desktop Administrator deploys, configures, secures, manages, and monitors devices and client applications in an enterprise environment. Overview After completing this course, learners should be able to: Prepare to install Windows 10. Install Windows 10. Configure Updates for Windows. Perform post-installation configuration tasks. Configure devices and drivers for Windows. Configure storage for Windows. Configure network settings in Windows. Configure remote management of Windows. Configure and manage applications in Windows. Configure Internet Explorer. Describe the methods for securing Windows 10. Configure account access and authentication. Configure file and folder permissions. Create security policies. Describe common threats and methods for mitigating against them. Use Windows troubleshooting and monitoring tools. Troubleshoot Windows installations. Troubleshoot application installation issues. Troubleshoot web browser settings. Troubleshoot Windows authentication. Troubleshoot hardware issues related to Windows machines. Develop an Operating System deployment and upgrade strategy. Understand the different methods of deployment. Understand on-premise and cloud-based solutions. Deploy and migrate desktops to Windows 10. Plan and configure Windows Update policies. Describe the benefits and capabilities of Azure AD. Manage users using Azure AD with Active Directory DS. Implement Windows Hello for Business. Configure conditional access rules based on compliance policies. Describe the various tools used to secure devices and data. Implement Windows Defender Advanced Threat Protection. This five day accelerated course will cover topics necessary to prepare attendees with the baseline knowledge to take the MD-100 and MD-101 exams for the Modern Desktop Administrator Associate certification. Installing Windows Introducing Windows 10 Installation Options Requirements for Windows Features Installation Process and Media Upgrading to Windows 10 Updating Windows Windows Servicing Model Updating Windows Applying Applications and Windows Updates Post-Instalation Configuration and Personalization Customize the Windows 10 UI Configure device specific settings such as power plans and mobile device options Use the Windows control panel and setting app to configure settings Describe using Windows PowerShell Configuring Peripherals and Drivers Managing Devices and Drivers Managing Printers Configuring Networking Configure IP Network Connectivity Implement Name Resolution Implement Wireless Network Connectivity Remote Access Overview Remote Management Configuring Storage Overview of storage options Using OneDrive Managing Disks, Partitions, and Volumes Maintaining Disks and Volumes Managing Storage Spaces Managing Apps in Windows 10 Providing Apps to Users Managing Universal Windows Apps The Windows Store Web browsers in Windows 10 Configuring Authorization and Authentication Using Security Settings to Mitigate Threats Configuring User Account Control Implementing Device Registration Authentication Configuring Data Access and Usage Overview of File Systems Configuring and Managing File Access Configuring and Managing Shared Folders Managing Security with Policies Configuring Advanced Management Tools Configuring Tenant Roles Managing Tenant Health and Services Supporting the Windows 10 Environment Troubleshooting Windows Troubleshooting Tools Troubleshooting the Windows OS Troubleshooting Windows Startup Troubleshooting Operating System Service Issues Troubleshooting Sign-In Issues Troubleshooting Files and Applications File Recovery in Windows 10 Application Troubleshooting Troubleshooting Hardware and Drivers Troubleshooting Device Driver Failures Overview of Hardware Troubleshooting Troubleshooting Physical Failures Planning an Operating System Deployment Strategy Overview of Windows as a service Windows 10 Deployment options Considerations for Windows 10 deployment Implementing Windows 10 Implementing Windows 10 by using dynamic deployment Implementing Windows 10 by using Windows Autopilot Upgrading devices to Windows 10 Managing Updates for Windows 10 Implementing Windows 10 by using dynamic deployment Implementing Windows 10 by using Windows Autopilot Upgrading devices to Windows 10 Device Enrollment Device management options Manage Intune device enrollment and inventory Configuring Profiles Configuring device profiles Managing user profiles Monitoring devices Application Management Implement Mobile Application Management (MAM) Deploying and updating applications Administering applications Managing Authentication in Azure Ad MANAGING AUTHENTICATION IN AZURE AD Managing Devices and Device Policies Microsoft Intune Overview Managing devices with Intune Implement device compliance policies Managing Security Implement device data protection Managing Windows Defender ATP Managing Windows Defender in Windows 10 Additional course details: Nexus Humans Windows 10 Modern Desktop Administrator Associate Bootcamp 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 Windows 10 Modern Desktop Administrator Associate Bootcamp 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 2 Days 12 CPD hours This course is intended for Experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek techniques for working with complex types of data resources. Overview Use Connector stages to read from and write to database tables Handle SQL errors in Connector stages Use Connector stages with multiple input links Use the File Connector stage to access Hadoop HDFS data Optimize jobs that write to database tables Use the Unstructured Data stage to extract data from Excel spreadsheets Use the Data Masking stage to mask sensitive data processed within a DataStage job Use the Hierarchical stage to parse, compose, and transform XML data Use the Schema Library Manager to import and manage XML schemas Use the Data Rules stage to validate fields of data within a DataStage job Create custom data rules for validating data Design a job that processes a star schema data warehouse with Type 1 and Type 2 slowly changing dimensions This course is designed to introduce you to advanced parallel job data processing techniques in DataStage v11.5. In this course you will develop data techniques for processing different types of complex data resources including relational data, unstructured data (Excel spreadsheets), and XML data. In addition, you will learn advanced techniques for processing data, including techniques for masking data and techniques for validating data using data rules. Finally, you will learn techniques for updating data in a star schema data warehouse using the DataStage SCD (Slowly Changing Dimensions) stage. Even if you are not working with all of these specific types of data, you will benefit from this course by learning advanced DataStage job design techniques, techniques that go beyond those utilized in the DataStage Essentials course. Accessing databases Connector stage overview - Use Connector stages to read from and write to relational tables - Working with the Connector stage properties Connector stage functionality - Before / After SQL - Sparse lookups - Optimize insert/update performance Error handling in Connector stages - Reject links - Reject conditions Multiple input links - Designing jobs using Connector stages with multiple input links - Ordering records across multiple input links File Connector stage - Read and write data to Hadoop file systems Demonstration 1: Handling database errors Demonstration 2: Parallel jobs with multiple Connector input links Demonstration 3: Using the File Connector stage to read and write HDFS files Processing unstructured data Using the Unstructured Data stage in DataStage jobs - Extract data from an Excel spreadsheet - Specify a data range for data extraction in an Unstructured Data stage - Specify document properties for data extraction. Demonstration 1: Processing unstructured data Data masking Using the Data Masking stage in DataStage jobs - Data masking techniques - Data masking policies - Applying policies for masquerading context-aware data types - Applying policies for masquerading generic data types - Repeatable replacement - Using reference tables - Creating custom reference tables Demonstration 1: Data masking Using data rules Introduction to data rules - Using the Data Rules Editor - Selecting data rules - Binding data rule variables - Output link constraints - Adding statistics and attributes to the output information Use the Data Rules stage to valid foreign key references in source data Create custom data rules Demonstration 1: Using data rules Processing XML data Introduction to the Hierarchical stage - Hierarchical stage Assembly editor - Use the Schema Library Manager to import and manage XML schemas Composing XML data - Using the HJoin step to create parent-child relationships between input lists - Using the Composer step Writing Hierarchical data to a relational table Using the Regroup step Consuming XML data - Using the XML Parser step - Propagating columns Topic 6: Transforming XML data - Using the Aggregate step - Using the Sort step - Using the Switch step - Using the H-Pivot step Demonstration 1: Importing XML schemas Demonstration 2: Compose hierarchical data Demonstration 3: Consume hierarchical data Demonstration 4: Transform hierarchical data Updating a star schema database Surrogate keys - Design a job that creates and updates a surrogate key source key file from a dimension table Slowly Changing Dimensions (SCD) stage - Star schema databases - SCD stage Fast Path pages - Specifying purpose codes - Dimension update specification - Design a job that processes a star schema database with Type 1 and Type 2 slowly changing dimensions Demonstration 1: Build a parallel job that updates a star schema database with two dimensions Additional course details: Nexus Humans KM423 IBM InfoSphere DataStage v11.5 - Advanced Data Processing 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 KM423 IBM InfoSphere DataStage v11.5 - Advanced Data Processing 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 intended for: Those who will provide container orchestration management in the AWS Cloud including: DevOps engineers Systems administrators Overview In this course, you will learn to: Review and examine containers, Kubernetes and Amazon EKS fundamentals and the impact of containers on workflows. Build an Amazon EKS cluster by selecting the correct compute resources to support worker nodes. Secure your environment with AWS Identity and Access Management (IAM) authentication by creating an Amazon EKS service role for your cluster Deploy an application on the cluster. Publish container images to ECR and secure access via IAM policy. Automate and deploy applications, examine automation tools and pipelines. Create a GitOps pipeline using WeaveFlux. Collect monitoring data through metrics, logs, tracing with AWS X-Ray and identify metrics for performance tuning. Review scenarios where bottlenecks require the best scaling approach using horizontal or vertical scaling. Assess the tradeoffs between efficiency, resiliency, and cost and impact for tuning one over the other. Describe and outline a holistic, iterative approach to optimizing your environment. Design for cost, efficiency, and resiliency. Configure the AWS networking services to support the cluster. Describe how EKS/Amazon Virtual Private Cloud (VPC) functions and simplifies inter-node communications. Describe the function of VPC Container Network Interface (CNI). Review the benefits of a service mesh. Upgrade your Kubernetes, Amazon EKS, and third party tools Amazon EKS makes it easy for you to run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane. In this course, you will learn container management and orchestration for Kubernetes using Amazon EKS. You will build an Amazon EKS cluster, configure the environment, deploy the cluster, and then add applications to your cluster. You will manage container images using Amazon Elastic Container Registry (ECR) and learn how to automate application deployment. You will deploy applications using CI/CD tools. You will learn how to monitor and scale your environment by using metrics, logging, tracing, and horizontal/vertical scaling. You will learn how to design and manage a large container environment by designing for efficiency, cost, and resiliency. You will configure AWS networking services to support the cluster and learn how to secure your Amazon EKS environment. Module 0: Course Introduction Course preparation activities and agenda Module 1: Container Fundamentals Best practices for building applications Container fundamentals Components of a container Module 2: Kubernetes Fundamentals Container orchestration Kubernetes objects Kubernetes internals Preparing for Lab 1: Deploying Kubernetes Pods Module 3: Amazon EKS Fundamentals Introduction to Amazon EKS Amazon EKS control plane Amazon EKS data plane Fundamentals of Amazon EKS security Amazon EKS API Module 4: Building an Amazon EKS Cluster Configuring your environment Creating an Amazon EKS cluster Demo: Configuring and deploying clusters in the AWS Management Console Working with eksctl Preparing for Lab 2: Building an Amazon EKS Cluster Module 5: Deploying Applications to Your Amazon EKS Cluster Configuring Amazon Elastic Container Registry (Amazon ECR) Demo: Configuring Amazon ECR Deploying applications with Helm Demo: Deploying applications with Helm Continuous deployment in Amazon EKS GitOps and Amazon EKS Preparing for Lab 3: Deploying App Module 6: Configuring Observability in Amazon EKS Configuring observability in an Amazon EKS cluster Collecting metrics Using metrics for automatic scaling Managing logs Application tracing in Amazon EKS Gaining and applying insight from observability Preparing for Lab 4: Monitoring Amazon EKS Module 7: Balancing Efficiency, Resilience, and Cost Optimization in Amazon EKS The high level overview Designing for resilience Designing for cost optimization Designing for efficiency Module 8: Managing Networking in Amazon EKS Review: Networking in AWS Communicating in Amazon EKS Managing your IP space Deploying a service mesh Preparing for Lab 5: Exploring Amazon EKS Communication Module 9: Managing Authentication and Authorization in Amazon EKS Understanding the AWS shared responsibility model Authentication and authorization Managing IAM and RBAC Demo: Customizing RBAC roles Managing pod permissions using RBAC service accounts Module 10: Implementing Secure Workflows Securing cluster endpoint access Improving the security of your workflows Improving host and network security Managing secrets Preparing for Lab 6: Securing Amazon EKS Module 11: Managing Upgrades in Amazon EKS Planning for an upgrade Upgrading your Kubernetes version Amazon EKS platform versions Additional course details: Nexus Humans Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) 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 Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) 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 The ideal audience for this course includes database enthusiasts, IT professionals, and developers who are eager to expand their knowledge and skill set in database management and optimization. Roles that would greatly benefit from attending this course include: Database Developers: Those who design, implement, and maintain databases as part of their primary responsibilities and want to improve their expertise in schema design, query optimization, and advanced database features. Backend Developers: Professionals who work on server-side application logic and require a strong understanding of database management to integrate data storage and retrieval processes into their applications. Overview Upon completing this course, database developers will be able to: Design and implement efficient database schemas by employing normalization techniques, appropriate indexing strategies, and partitioning methods to optimize data storage and retrieval processes. Develop advanced SQL queries, including joining multiple tables, utilizing subqueries, and aggregating data, to extract valuable insights and facilitate decision-making processes. Implement stored procedures, functions, and triggers to automate common database tasks, enforce data integrity, and improve overall application performance. Apply database performance tuning techniques, such as query optimization, index management, and transaction control, to ensure optimal resource usage and enhanced system responsiveness. Integrate databases with various programming languages and platforms, enabling seamless data access and manipulation for web, mobile, and desktop applications. PostgreSQL is a powerful, open-source object-relational database management system that emphasizes extensibility, data integrity, and high performance. Its versatility and robust feature set make it an ideal choice for developers working on projects of all sizes, from small-scale applications to enterprise-level systems. By learning PostgreSQL, developers can tap into its advanced capabilities, such as full-text search, spatial data support, and customizable data types, allowing them to create efficient and scalable solutions tailored to their unique needs. PostgreSQL for Database Developers is a three-day hands-on course that explores the fundamentals of database management, covering everything from installation and management to advanced SQL functions. Designed for beginners and enthusiasts alike, this course will equip you with the knowledge and skills required to effectively harness the power of PostgreSQL in today's data-driven landscape. Throughout the course you?ll be immersed in a variety of essential topics, such as understanding data types, creating and managing indexes, working with array values, and optimizing queries for improved performance. You?ll gain valuable hands-on experience with real-world exercises, including the use of the psql client, writing triggers and stored procedures with PL/pgSQL, and exploring advanced SQL functions like Common Table Expressions (CTE), Window Functions, and Recursive Queries. You?ll exit this course with a solid foundation in PostgreSQL, enabling you to confidently navigate and manage your databases with ease and efficiency. Installing & Managing PostgreSQL PostgreSQL installation process Optimal configuration settings User and role management Database backup and restoration Overview of PostgreSQL Database PostgreSQL architecture overview Understanding database objects Efficient data storage Transaction management basics Using the psql client Introduction to psql Essential psql commands Executing queries effectively Managing databases with psql Understanding PostgreSQL data types Numeric data types explored Character and binary types Date, time, and boolean values Array and other types Understanding sequences Sequence creation and usage Customizing sequence behavior Implementing auto-increment columns Sequence manipulation and control Creating & managing indexes PostgreSQL index fundamentals Designing partial indexes Utilizing expression-based indexes Index management techniques Using COPY to load data COPY command overview Importing and exporting data Handling CSV and binary formats Performance considerations Working with Array Values Array value basics Array manipulation functions Querying arrays efficiently Multidimensional array handling Advanced SQL Functions Mastering Common Table Expressions Utilizing Window Functions Regular Expressions in SQL Crafting Recursive Queries Writing triggers & stored procedures with PL/pgSQL PL/pgSQL variables usage Implementing loop operations PERFORM and EXECUTE statements Developing PostgreSQL triggers Using the PostgreSQL query optimizer Query analysis and optimization EXPLAIN command insights PostgreSQL query operators Identifying performance bottlenecks Improving query performance Query performance tuning Index optimization strategies Efficient database partitioning Connection and resource management Wrap Up & Additional Resources Further learning opportunities Staying up-to-date with PostgreSQL Community engagement and support Additional course details: Nexus Humans PostgreSQL for Database Developers (TTDB7024) 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 PostgreSQL for Database Developers (TTDB7024) 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 primary audience for this course is as follows: Network Video Engineer Voice/UC/Collaboration/Communications Engineer Collaboration Tools Engineer Collaboration Sales/Systems Engineer Overview Implement and Configure Cisco Endpoints Implement and Configure Cisco Unified Communications Manager for Video Endpoints Implement and Configure Cisco IMP for Jabber Implement and Configure Cisco Expressway Implement and Configure Cisco Video Communications Server (VCS) Control Implement and Configure Cisco Video Communications Server (VCS) Expressway Implement and Configure connectivity between a Cisco VCS and Cisco UCM Implement and Configure a Cisco Conductor Implement, Configure, and Operate Cisco TelePresence Management Suite (TMS) and provision devices using Cisco TMS Provisioning Extension (TMSPE) Implement and Configure Cisco Meeting Server This one of kind Cisco Collaboration in-depth course takes student from initial endpoint configuration to a full solution deployment using all of the Cisco Collaboration Components. Students will have extensive labs in which they will configure and troubleshoot a full Cisco Telepresence Deployment. Participants will gain in-depth practical knowledge with exercises on installing, configuring, maintaining and troubleshooting of all Cisco Telepresence Components.The software applications that are covered in this course include:Cisco Unified Communications Manager (CUCM)Cisco Unified Communications Manager IM and PresenceCisco ExpresswayCisco Video Communication Server (VCS)Cisco ConductorCisco Telepresence Server (TS)Cisco Meeting Server (CMS)Cisco Telepresence Management Suite (TMS)Cisco TMS Extensions Understanding Cisco TelePresence Endpoints Cisco TelePresence Endpoint Solutions Overview Cisco DX Series Endpoint Characteristics Cisco TelePresence TC Software-Based Endpoint Characteristics Cisco TelePresence EX60 and EX90 Cisco TelePresence MX Series Cisco TelePresence SX Series Endpoints Cisco TelePresence Room Kits Cisco Intelligent Proximity Cisco TelePresence TC Software-Based Endpoint Peripherals Cisco TelePresence TC Software-Based Endpoint Deployments Cisco TelePresence Integrator C Series-Based Endpoints Cisco Jabber Video for TelePresence Characteristics Cisco Jabber Understanding the Cisco Video Network Network Overview H323 Overview SIP Overview VCS vs Unified Communications Manager Internetworking QOS Overview Implementing and Configuring Unified Communication Manager Unified Communications Manager Initial Settings Service Activation Enterprise and Service Parameters SIP Domains Configure IMP for Jabber Configure Jabber Settings Registering Endpoints Verifying Network Registration Cisco VCS / Expressway Overview and Configuration Configuring Initial VCS Setting Configuring Authentication Registration Conflict Policy Registration Restriction Policy Local Zone Components Membership Rules Transforms Purpose of Zones Search Priority Neighbor Zones Creating Neighbor Zones Need for Traversal Zones H.460 and Assent Protocols Traversal Zone Configuration Domain Name System Dialing E.164 Number Mapping Bandwidth Management Pipes Subzones and Zones Subzone Call Failure Call Processing Order Certificates Certificate Installation Clustering and the Cisco VCS Clustering Configuration Collecting Information Log Files Search History Connecting VCS-C to CUCM Connect VCS-C to VCS-E Connecting CUCM to VCS-C Understanding the Cisco TelePresence Conductor What is Conductor? Conductor ? How it works Installing Cisco Conductor Configuring Conductor Network Settings Configuring Conductor for a CUCM Configuration MCU Configuration Telepresence Server Telepresence Conductor Server Configuration Configuring TelePresence Conductor for ad hoc conferences Configuring TelePresence Conductor for rendezvous conferences Configuring Unified CM Configuring general settings on Unified CM Locations in Unified CM Unified CM trusts TelePresence Conductor's server certificate SIP trunk security profile Configuring Unified CM for rendezvous conferences Sip Trunk Configuration Conference Bridge Configuration MRG and MRGL Configuration Unified CM normalization scripts Configuring Unified CM for ad hoc conferences Sip Trunk Configuration Route pattern to match the SIP Trunk Configuration Unified CM normalization scripts Configuring the Cisco VCS with TelePresence Conductor Designing a Dial Plan MCU Configuration Telepresence Server Configuring the Cisco VCS Telepresence Conductor Server Configuration Backing Up Conductor Troubleshooting Conductor Overview of Cisco Telepresence Management Server (TMS) Windows Server Installation SQL Server Installation Server Pre-requisites and configuration Installing TMS Installing TMS Provisioning Extensions Initial Configuration Endpoint Configuration Adding Systems to TMS Configuration Templates Setting Configuration VCS Configuration for TMS Direct Endpoint Management VCS/TMS CUCM Configuration for TMS Direct Endpoint Management?CUCM Phonebooks & Phonebook Sources Conference Creation Advanced Conference Settings Booking & Scheduling Participant Types Methods Conference Monitoring Dial Plans, Configuration Templates Scheduler/Smart Scheduler Managing and Troubleshooting Cisco TMS Using the Logs Cisco TMS Ticketing System Troubleshooting VCS Registrations Troubleshooting CUCM Registrations System Maintenance Configuring Cisco Meeting Server (formerly Acano) Setting up CMS Installing Certificates Configuring CUCM with CMS Provision the RTC Client Configuring Meeting Spaces Additional course details: Nexus Humans Advanced TP-CT - Implementing and Configuring Cisco TelePresence Video Suite 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 Advanced TP-CT - Implementing and Configuring Cisco TelePresence Video Suite course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for Cloud Solutions Architects, Site Reliability Engineers, Systems Operations professionals, DevOps Engineers, IT managers. Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform. Overview Apply a tool set of questions, techniques and design considerations Define application requirements and express them objectively as KPIs, SLO's and SLI's Decompose application requirements to find the right microservice boundaries Leverage Google Cloud developer tools to set up modern, automated deployment pipelines Choose the appropriate Google Cloud Storage services based on application requirements Architect cloud and hybrid networks Implement reliable, scalable, resilient applications balancing key performance metrics with cost Choose the right Google Cloud deployment services for your applications Secure cloud applications, data and infrastructure Monitor service level objectives and costs using Stackdriver tools This course features a combination of lectures, design activities, and hands-on labs to show you how to use proven design patterns on Google Cloud to build highly reliable and efficient solutions and operate deployments that are highly available and cost-effective. This course was created for those who have already completed the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine course. Defining the Service Describe users in terms of roles and personas. Write qualitative requirements with user stories. Write quantitative requirements using key performance indicators (KPIs). Evaluate KPIs using SLOs and SLIs. Determine the quality of application requirements using SMART criteria. Microservice Design and Architecture Decompose monolithic applications into microservices. Recognize appropriate microservice boundaries. Architect stateful and stateless services to optimize scalability and reliability. Implement services using 12-factor best practices. Build loosely coupled services by implementing a well-designed REST architecture. Design consistent, standard RESTful service APIs. DevOps Automation Automate service deployment using CI/CD pipelines. Leverage Cloud Source Repositories for source and version control. Automate builds with Cloud Build and build triggers. Manage container images with Google Container Registry. Create infrastructure with code using Deployment Manager and Terraform. Choosing Storage Solutions Choose the appropriate Google Cloud data storage service based on use case, durability, availability, scalability and cost. Store binary data with Cloud Storage. Store relational data using Cloud SQL and Spanner. Store NoSQL data using Firestore and Cloud Bigtable. Cache data for fast access using Memorystore. Build a data warehouse using BigQuery. Google Cloud and Hybrid Network Architecture Design VPC networks to optimize for cost, security, and performance. Configure global and regional load balancers to provide access to services. Leverage Cloud CDN to provide lower latency and decrease network egress. Evaluate network architecture using the Cloud Network Intelligence Center. Connect networks using peering and VPNs. Create hybrid networks between Google Cloud and on-premises data centers using Cloud Interconnect. Deploying Applications to Google Cloud Choose the appropriate Google Cloud deployment service for your applications. Configure scalable, resilient infrastructure using Instance Templates and Groups. Orchestrate microservice deployments using Kubernetes and GKE. Leverage App Engine for a completely automated platform as a service (PaaS). Create serverless applications using Cloud Functions. Designing Reliable Systems Design services to meet requirements for availability, durability, and scalability. Implement fault-tolerant systems by avoiding single points of failure, correlated failures, and cascading failures. Avoid overload failures with the circuit breaker and truncated exponential backoff design patterns. Design resilient data storage with lazy deletion. Analyze disaster scenarios and plan for disaster recovery using cost/risk analysis. Security Design secure systems using best practices like separation of concerns, principle of least privilege, and regular audits. Leverage Cloud Security Command Center to help identify vulnerabilities. Simplify cloud governance using organizational policies and folders. Secure people using IAM roles, Identity-Aware Proxy, and Identity Platform. Manage the access and authorization of resources by machines and processes using service accounts. Secure networks with private IPs, firewalls, and Private Google Access. Mitigate DDoS attacks by leveraging Cloud DNS and Cloud Armor. Maintenance and Monitoring Manage new service versions using rolling updates, blue/green deployments, and canary releases. Forecast, monitor, and optimize service cost using the Google Cloud pricing calculator and billing reports and by analyzing billing data. Observe whether your services are meeting their SLOs using Cloud Monitoring and Dashboards. Use Uptime Checks to determine service availability. Respond to service outages using Cloud Monitoring Alerts. Additional course details: Nexus Humans Architecting with Google Cloud: Design and Process 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 with Google Cloud: Design and Process 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 introductory-level Python course is geared for experienced users who want to use Python in web development projects, or system administrators and web site administrators who want to use Python to support their server installations, as well as anyone else who wants to automate or simplify common tasks with the use of Python scripts. Basic familiarity with any programming or scripting language would be helpful, along with a working, user-level knowledge of Unix/Linux, Mac, or Windows. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to write essential Python scripts using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Create working Python scripts following best practices Use python data types appropriately Read and write files with both text and binary data Search and replace text with regular expressions Get familiar with the standard library and its work-saving modules Use lesser known but powerful Python data types Create 'real-world', professional Python applications Work with dates, times, and calendars Know when to use collections such as lists, dictionaries, and sets Understand Pythonic features such as comprehensions and iterators Write robust code using exception handling Mastering Python Programming is an introductory and beyond-level practical, hands-on Python training course that leads the student from the basics of writing and running Python scripts to more advanced features such as file operations, regular expressions, working with binary data, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as tuples, array slices, and output formatting. This comprehensive, practical course provides an in-depth exploration of working with the programming language, not an academic overview of syntax and grammar. Students will immediately be able to use Python to complete tasks in the real world. An overview of Python What is python? Python Timeline Advantages/Disadvantages of Python Getting help with pydoc The Python Environment Starting Python Using the interpreter Running a Python script Python scripts on Unix/Windows Editors and IDEs Getting Started Using variables Builtin functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Array types About array types (AKA sequences) Lists and list methods Tuples Indexing and slicing Iterating through a sequence Nested sequences Sequence functions, keywords, and operators List comprehensions Generator Expressions Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Converting binary data with struct Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Parameters Global and local scope Nested functions Returning values Sorting The sorted() function Alternate keys Lambda functions Sorting collections Using operator.itemgetter() Reverse sorting Errors and Exception Handling Syntax errors Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages The import statement Module search path Creating Modules Using packages Function and Module aliases An Introduction to Python Classes About o-o programming Defining classes Constructors Methods Instance data Properties Class methods and data Regular Expressions RE syntax overview RE Objects Searching and matching Compilation flags Groups and special groups Replacing text Splitting strings Using the Standard Library The sys module Launching external programs Math functions Random numbers Reading CSV data Dates and Times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Working with the File System Paths, directories, and filenames Checking for existence Permissions and other file attributes Walking directory trees Creating filters with fileinput Using shutil for file operations Advanced Data Handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Network Programming Using requests Grabbing web content Sending email Using SSH for remote access Using FTP Writing real-life applications Reading input files a la Unix Parsing command-line options Detecting the current platform Implementing logging Additional course details: Nexus Humans Mastering Python Programming (TTPS4820) 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 Mastering Python Programming (TTPS4820) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently