2401 Courses delivered Online

Description Register on the Deep Learning & Neural Networks Python - Keras today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a certificate as proof of your course completion. The Deep Learning & Neural Networks Python - Keras course is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablets, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With This Course Receive a digital certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment You need to attend an assessment right after the completion of this course to evaluate your progression. For passing the assessment, you need to score at least 60%. After submitting your assessment, you will get feedback from our experts immediately. Who Is This Course For The course is ideal for those who already work in this sector or are aspiring professionals. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.   Course Content Course Introduction And Table Of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML Or DL For The Next AI Project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation And Sample Program To Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow Library Installation And Sample Program To Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation And Switching Theano And TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps And Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network With Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training And Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding The Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - K-Fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing The Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding The Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing The Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning For Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding The Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing The Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement By Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement By Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement By Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load The Trained Model As JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save And Load Model As YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load And Predict Using The Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load And Predict Using The Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load And Predict Using The Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load And Predict Using The Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction To Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading The Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule Using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Handwritten Digit Recognition Dataset MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model Using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN Using MNIST Large CNN using MNIST 00:09:00 Load And Predict Using The MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction To Image Augmentation Using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation Using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation Using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation Using Rotation And Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding And Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN Using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train And Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load And Predict Using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00

Develop the commercial awareness, financial knowledge and strategic thinking capabilities, to influence the direction of the business Course overview Duration: 2 days (13 hours) This course is aimed at managers who want to develop their commercial awareness, financial knowledge and strategic thinking capabilities, so that they can influence the direction of their business and deliver to their full potential. Day one of the course provides the skills and insights to make sense of your company’s financial position and performance. Day two helps delegates to consider the strategic thinking tools required to plot the forward course needed to maximise the potential of the business. As well as looking at how to make effective business decisions, this course gives a good grounding in finance and profitability. As a two day programme, day one provides the skills and insights to make sense of the company’s financial position and performance. Day two then considers the strategic thinking tools needed to plot the forward course needed to maximise the potential of the business. Objectives By the end of the course you will be able to: An understanding of the balance sheet, profit and loss account, cash flow and statutory and management accounts Learnt to correctly employment key financial ratios to analyse your business A practical definition of strategy analysis tools to examine the current environment and capabilities Steps to devise a mission and vision statement Recognition of the skills and resources needed to achieve the vision Generation of appropriate strategic and tactical commercial objectives Content What is Strategy Defining Strategy Strategic thinking Strategic models Commercial thinking – what is money? Where are we now STEEPLE analysis SWOT Analysis P&E forces at work Political distortions in capitalist markets Where are we trying to get to Setting the mission and vision Creating a BHAG Strategies for deflation and inflation The role of banks Commercial and investment banking Fractional reserving Securitisation How to get there Skill gap analysis Business Process Re engineering The role of creativity How to get there Getting the team on board Individual and team motivation The power of the brand Overcoming challenges Debt and deleveraging Change management Creating value Discounted Cash Flows Building the business case Asset Valuation techniques Making it happen Turning Strategic Thinking into Strategic Plans Scenario planning for an uncertain future Creating commitments and lock in Discussion and review Time will be set aside during the course for review sessions with time for questions, answers and action learning.

Duration 5 Days 30 CPD hours This course is intended for This section specifies the primary and secondary target audiences of this course by job roles and notes the relevance to each job role. Collaboration Engineers and Administration Primary audiences: Collaboration engineers involved in the design, implementation, and troubleshooting of Cisco collaboration core technologies. Secondary audiences: Administration involved in support and troubleshooting of Cisco collaboration technologies. Overview Upon completing this course, you will be able to meet these objectives: Describe the Cisco Expressway - C features and functionality within the collaboration architecture Configure and troubleshoot Cisco Unified Communications Manager and Cisco expressway Series integration Describe the Cisco Expressway - C additional features Configure and troubleshoot Cisco Collaboration solutions for B2B calls Describe how to secure B2B communication with Cisco Expressway Series Describe the MRA feature Describe the Cisco Expressway MRA security and integration options, including integration with Cisco Unity Connection and Cisco IM&P Configure Cisco Webex Hybrid Services This course provides students knowledge about Cisco Expressway Series solutions, such as B2B calls, Cisco Mobile and Remote Access for remote workers, authentication options, and additional Cisco Expressway Series features. Configuring and Troubleshooting the Cisco Expressway Series Cisco Expressway Series Architecture Discovery 1: Deploy virtualized Cisco Expressway Discovery 2: Perform the initial Cisco Expressway series configuration Describe SIP and H.323 in the Cisco Expressway series Describe interworking in the Cisco Expressway series Discovery 3: Register endpoints on Cisco Expressway series Zones Digital string manipulation Search rules Transforms Discovery 4: Call search history and registrations Troubleshoot call processing on Cisco Expressway series Discovery 5: Troubleshooting tools Backup and restore Rerference Configuring Cisco Expressway Additional Freatures Describe bandwidth management Hardening local endpoint registrations Discovery 6: Configure Cisco Expressway series bandwidth management and registration restrictions Discovery 7: Troubleshoot Cisco Expressway series endpoint registration and local dial plan Describe Cisco Expressway security and clustering features Discovery 8: Configure Cisco Expressway series security features Configuring and Troubleshooting Cisco Unified Communications Manager and Cisco Expressway Series Cisco unified communications manager and Cisco Expressway-C integration overview Dian plan overview Call policy Discovery 9: Configure Cisco unified communications manager to connect with Cisco Expressway-C Troubleshooting options for Cisco unified communications manager and Cisco Expressway-C intergration Discovery 10: Troubleshoot Cisco unified communications manager and Cisco Expressway series integration Discovery 11: Configure and troubleshoot Cisco unified communications manager and Cisco Expressway series integration (practice activity) References Configuring and Troubleshooting Cisco Collaboration Solutions for Bussiness-to-Bussiness Describe supported services for B2B collaboration Describe prerequisites for business to business collaboration Call flow including Cisco unified communications manager endpoints Network address translation in a collaboration environment Discovery 12: Implement a B2B Cisco collaboration solution Cisco Expressway series B2B call troubleshooting Discovery 13: Troubleshoot B2B calls on the Cisco Expressway series References Discovery 14: Troubleshoot B2B calls on the Cisco Expressway series (practice activity) Securing Business-Business Communication Firewall Traversal Secure media Secure media between Cisco unified communications manager and Cisco Expressway series Toll fraud prevention Discovery 15: Secure a B2B Cisco collaboration communication Refrences Configuring and Troubleshooting Mobile and Remote Access Describe prerequisites for mobile and remote access Describe service discovery Explore Expressway settings for MRA Certificates HTTP proxy Cisco jabber registration procedure Cisco jabber registration procedure in Hybrid deployment Cisco jabber configuration file Discovery 16: Configure MRA on the Cisco Expressway series MRA troubleshooting Discovery 17: Troubleshoot MRA on the Cisco Expressway series Integrating and Securing Mobile and Remote Access Secure Cisco unified communications integration Cisco unity connection integration Cisco MRA access control options Additional Cisco MRA features Discovery 18: Configure MRA with additional application integrations References Configuring Cisco Webex Hybrid Services Cisco Webex teams Describe Cisco Webex control hub Describe Cisco Webhex hybrid media services Describe Cisco Expressway requirements for using hybrid call service connect Explore Cisco Expressway requirements for using hybrid call service connect Describe Cisco Webex video mesh Discovery 19: Prepare for Cisco Webex teams integration Discovery 20: Configure Cisco Webex hybrid services Additional course details: Nexus Humans Cisco Implementing Cisco Collaboration Cloud and Edge Solutions v1.0 (CLCEI) 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 Collaboration Cloud and Edge Solutions v1.0 (CLCEI) 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 Typical candidates for this course are IT Professionals who will deploy and manage networks based on HPE's ArubaOS-CX switches. Overview After you successfully complete this course, expect to be able to: Use NetEdit to manage switch configurations Use the Network Analytics Engine (NAE) to implement scripting solutions to provide for proactive network management and monitoring Compare and contrast VSX, VSF, and backplane stacking Explain how VSX handles a split-brain scenario Implement and manage a VSX fabric Define ACLs and identify the criteria by which ACLs select traffic Configure ACLs on AOS-CX switches to select given traffic Apply static ACLs to interfaces to meet the needs of a particular scenario Examine an ACL configuration and determine the action taken on specific packets Deploy AOS-Switches in single-area and multi-area OSPF systems Use area definitions and summaries to create efficient and scalable multiple area designs Advertise routes to external networks in a variety of OSPF environments Promote fast, effective convergence during a variety of failover situations Use virtual links as required to establish non-direct connections to the backbone Implement OSFP authentication Establish and monitor BGP sessions between your routers and ISP routers Advertise an IP block to multiple ISP routers Configure a BGP router to advertise a default route in OSPF Use Internet Group Management Protocol (IGMP) to optimize forwarding of multicast traffic within VLANs Describe the differences between IGMP and IGMP snooping Distinguish between PIM-DM and PIM-SM Implement PIM-DM and PIM-SM to route multicast traffic Implement Virtual Routing Forwarding (VRF) policies to contain and segregate routing information Create route maps to control routing policies Understand the use of user roles to control user access on AOS-CX switches Implement local user roles on AOS-CX switches and downloadable user roles using a ClearPass solution Implement 802.1X on AOS-CX switch ports Integrate AOS-CX switches with an Aruba ClearPass solution, which might apply dynamic role settings Implement RADIUS-based MAC Authentication (MAC-Auth) on AOS-CX switch ports Configure captive portal authentication on AOS-CX switches to integrate them with an Aruba ClearPass solution Combine multiple forms of authentication on a switch port that supports one or more simultaneous users Configure dynamic segmentation on AOS-CX switches This course teaches you the advanced skills necessary to implement and operate enterprise level Aruba campus switching solutions. You will build on the skills you learned at the Associate level to configure and manage modern, open standards-based networking solutions using Aruba's OS-CX routing and switching technologies. In this course, participants learn about ArubaOS-CX switch technologies including: securing port access with Aruba's dynamic segmentation, redundancy technologies such as Multiple Spanning Tree Protocol (MSTP), link aggregation techniques including Link Aggregation Protocol (LACP) and switch virtualization with Aruba?s Virtual Switching Extension (VSX) and Aruba's Virtual Switching Framework (VSF). This course is approximately 50% lecture and 50% hands-on lab exercises. Introduction to Aruba Switching Switches overview Architectures NetEdit Overview Centralized configuration Switch groups/templates AOS-CX mobile App Network Analytics Engine (NAE) Overview Configuration Core NAE feature lab sflow, local mirror, remote mirror VSX VSF vs. VSX: access and Agg/core design Stacking review VSF and uni/multi packet forwarding Stack fragments / split brain VSX Overview: roles, control, data, management planes VSX components (ISL, Keepalive, VSX LAG, Active Gateway, Active-Forwarding, Link Delay) Split Brain scenario Upstream Connectively Options (ROP single VRF, SVIs with multiple VRF, VSX Lag SVIs with multiple VRFs) Upstream/Downstream unicast traffic flow (South-North and North-South) VSX Configuration: VSX and Active Gateway VSX firmware updates ACLs Overview: types, components MAC ACL, Standard ACL, Extended ACL, Classifier-based Policies Configuration: wildcard bits, logging, pacl, vacl, racl Advanced OSPF Review basic OSPF Multi area: setup and aggregation Area-Types Stub, Totally Stub, NSSA, Totally NSSA External routes OSPF tuning: costs, bfd, gr, auth, vrrp, virt link BGP Overview: i/e bgp, as numbers Best path selection Configuration: route announcement Route filtering to prevent transit as IGMP Overview Querier Snooping Unknown multicasts Multicast Routing: PIM Overview PIM DM 802.1X Authentication Overview: roles, requirements, coa, accounting Dynamic port configuration: avp, acl, qos, VLAN Port-based vs. user-based: examples Radius service tracking, critical VLAN MAC Authentication Overview: Use cases Radius-based MAC Auth Dynamic Segmentation Leverage dynamic segmentation features Configure tunneled-node on AOS-CX switches Describe when and how to configure PAPI enhanced security, high availability, and fallback switching for tunneled-node Quality of Service Overview VoQ (Virtual Output Queue) QOS: queueing, QOS marks, dot1p, dscp Trust levels QOS configuration: port, VLAN, policies Interaction with user roles Queue configuration Rate limiters LLDP-MED Additional Routing Technologies VRF - Management VRF PBR MDNS PIM SM Capitve Portal Authentication Overview of guest solutions Built-in web auth ClearPass redirect with CPPM

Duration 5 Days 30 CPD hours This course is intended for This course is intended for: Solutions Architects who are new to designing and building cloud architectures Data Center Architects who are migrating from on-premises environment to cloud architectures Other IT/cloud roles who want to understand how to design and build cloud architectures Overview In this course, you will learn how to: Make architectural decisions based on AWS architectural principles and best practices Use AWS services to make your infrastructure scalable, reliable, and highly available Use AWS Managed Services to enable greater flexibility and resiliency in an infrastructure Make an AWS-based infrastructure more efficient to increase performance and reduce costs Use the Well Architected Framework to improve architectures with AWS solutions This course covers all aspects of how to architect for the cloud over four-and-a-half-days. It covers topics from Architecting on AWS and Advanced Architecting on AWS to offer an immersive course in cloud architecture. You will learn how to design cloud architectures, starting small and working to large-scale enterprise level designs-and everything in between. Starting with the Well-Architected Framework, you will learn important architecting information for AWS services including: compute, storage, database, networking, security, monitoring, automation, optimization, benefits of de-coupling applications and serverless, building for resilience, and understanding costs Module 1: Introduction The real story of AWS Well-Architected Framework Six advantages of the cloud Global infrastructure Module 2: The Simplest Architectures S3 Glacier Choosing your regions Hands-on lab: Static Website Module 3: Adding a Compute Layer EC2 Storage solutions for instances Purchasing options such as dedicated host vs instances Module 4: Adding a Database Layer Relational vs non-relational Managed databases RDS Dynamo DB Neptune Hands-on lab: Deploying a web application on AWS Module 5: Networking in AWS Part 1 VPC CIDR and subnets Public vs private subnets NAT and internet gateway Security groups Module 6: Networking in AWS Part 2 Virtual Private Gateway VPN Direct Connect VPC peering Transit Gateway VPC Endpoints Elastic Load Balancer Route 53 Hands-on lab: Creating a VPC Module 7: AWS Identity and Access Management (IAM) IAM Identity federation Cognito Module 8: Organizations Organizations Multiple account management Tagging strategies Module 9: Elasticity, High Availability, and Monitoring Elasticity vs inelasticity Monitoring with CloudWatch, CloudTrail, and VPC Flow Logs Auto scaling Scaling databases Hands-on lab: Creating a highly available environment Module 10: Automation Why automate? CloudFormation AWS Quick Starts AWS Systems Manager AWS OpsWorks AWS Elastic Beanstalk Module 11: Deployment Methods Why use a deployment method? Blue green and canary deployment Tools to implement your deployment methods CI/CD Hands-on lab: Automating infrastructure deployment Module 12: Caching When and why you should cache your data Cloudfront Elasticache (Redis/Memcached) DynamoDB Accelerator Module 13: Security of Your Data Shared responsibility model Data classification Encryption Automatic data security Module 14: Building Decoupled Architecture Tight coupling vs loose coupling SQS SNS Module 15: Optimizations and Review Review questions Best practices Activity: Design and architecture - two trues and one lie Module 16: Microservices What is a microservice? Containers ECS Fargate EKS Module 17: Serverless Why use serverless? Lambda API Gateway AWS Step Functions Hands-on lab: Implementing a serverless architecture with AWS Managed Services Module 18: Building for Resilience Using managed services greatly increases resiliency Serverless for resiliency Issues with microservices to be aware of DDoS Hands-on lab: Amazon CloudFront content delivery and automating WAF rules Module 19: Networking in AWS Part 3 Elastic Network Adapter Maximum transmission units Global Accelerator Site to site VPN Transit Gateway Module 20: Understanding Costs Simple monthly calculator Right sizing your instances Price sensitive architecture examples Module 21: Migration Strategies Cloud migration strategies Planning Migrating Optimizing Hands-on lab: Application deployment using AWS Fargate Module 22: RTO/RPO and Backup Recovery Setup Disaster planning Recovery options Module 23: Final Review Architecting advice Service use case questions Example test questions Additional course details: Nexus Humans Architecting on AWS - Accelerator training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Architecting on AWS - Accelerator course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for This course is intended for anyone who is new to software development and wants, or needs, to gain an understanding of the fundamentals of coding and basics of C++ and object-oriented programming concepts. This course is for Non-Developers, or anyone who wants to have a basic understanding of and learn how to code C++ applications and syntax Overview Companies are constantly challenged to keep their applications, development projects, products, services (and programmers!) up to speed with the latest industry tools, skills, technologies and practices to stay ahead in the ever-shifting markets that make up today's fiercely competitive business landscape. The need for application, web and mobile developers and coders is seemingly endless as technologies regularly change and grow to meet the modern needs of demanding industries and clients. C++ and Programming Basics for Non-Programmers is a five-day, basic-level training course geared for IT candidates who have little or no prior experience in computer programming. Throughout this gentle introduction to programming and C++, students will learn to create applications and libraries using C++ using best practices and sound OO development techniques for writing object-oriented programs in C++. Special emphasis is placed on object-oriented concepts and best practices throughout the training. Fundamentals of the Program Development Cycle Computer Architecture The Notion of Algorithms Source Code vs. Machine Code Compile-Time vs. Run-Time Software Program Architecture Standalone Client/Server Distributed Web-Enabled IDE (Interactive Development Environment) Concepts Looping Constructs Counter-Controlled Repetition Sentinel-Controlled Repetition Nested Control Constructs break and continue Statements Structured Programming Best Practices Writing Methods (Functions) Static vs. Dynamic Allocation Declaring Methods Declaring Methods with Multiple Parameters Method-Call Stack Scope of Declarations Argument Promotion and Casting Designing Methods for Reusability Method Overloading Arrays Purpose of Arrays Declaring and Instantiating Arrays Passing Arrays to Methods Multidimensional Arrays Variable-Length Argument Lists Using Command-Line Arguments Using Environment Variables Deeper Into Classes and Objects Controlling Access to Class Members Referencing the Current Object Using this Overloading Constructors Default and No-Argument Constructors Composition of Classes Garbage Collection and Destructors The finalize Method Static Class Members Defining Classes Using Inheritance Application Development Fundamentals Structure of a C++ Program Memory Concepts Fundamental Data Type Declarations Fundamental I/O Concepts Fundamental Operators Arithmetic Operators Logical Operators Precedence and Associativity Building and Deploying a C++ Program Superclasses and Subclasses Advantages of Using Inheritance protected Class Members Constructors in Subclasses Increasing Convenience by Using Polymorphism Purpose of Polymorphic Behavior The Concept of a Signature Abstract Classes and Methods final Methods and Classes Purpose of Interfaces Using and Creating Interfaces Common Interfaces of the C++ API Files and Streams Concept of a Stream Class File Sequential Access Object Serialization to/from Sequential Access Files Fundamental Searching and Sorting Introduction to Searching Algorithms Linear Search Binary Search Introduction to Sorting Algorithms Selection Sort Insertion Sort Merge Sort Fundamental Data Structures Dynamic Memory Allocation Linked Lists Stacks Queues Trees Exception Handling Types of Exceptions Exception Handling Overview Introduction to Classes and Objects Classes, Objects and Methods Object Instances Declaring and Instantiating a C++ Object Declaring Methods set and get Methods Initiating Objects with Constructors Primitive Types vs. Reference Types Flow Control Conditional Constructs Exception Class Hierarchy Extending Exception Classes When to Throw or Assert Exceptions Formatted Output printf Syntax Conversion Characters Specifying Field Width and Precision Using Flags to Alter Appearance Printing Literals and Escape Sequences Formatting Output with Class Formatter Strings, Characters and Regular Expressions Fundamentals of Characters and Strings String Class String Operations StringBuilder Class Character Class StringTokenizer Class Regular Expressions Regular Expression Syntax Pattern Class Matcher Class Fundamental GUI Programming Concepts Overview of Swing Components Displaying Text and Graphics in a Window Event Handling with Nested Classes GUI Event Types and Listener Interfaces Mouse Event Handling Layout Managers Additional course details: Nexus Humans C Plus Plus and Programming Basics for Non-Programmers (TTCP2000) 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 C Plus Plus and Programming Basics for Non-Programmers (TTCP2000) 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.

Unlock your true potential with the Reclaiming Your Masculine and Feminine Toolkit! This comprehensive resource offers transformative exercises, including daily self-awareness prompts, boundary-building tools, emotional regulation techniques, and breathwork practices. Balance your energies, enhance self-awareness, and align with your purpose. Perfect for anyone looking to deepen their personal growth journey. Embrace your power today!

This course teaches you data analysis and visualisation using the versatile R language. From understanding data structures to performing advanced statistical analysis, this course equips you with the skills to extract meaningful insights from complex datasets. This Course At A Glance Accredited by CPD UK Endorsed by Quality Licence Scheme Get a deep understanding of data science, the process and the toolbox Learn about R and Rstudio Get an introduction to the basic data types in R Learn to perform arithmetic calculations on vectors Understand what is a matrix and how to analyse it Know what is factors and how to summarise it Recognise how to create a data frame Get an understanding of the relational and logical operators Learn what is a conditional statement and how to implement the same Learn about loops, functions and R packages Understand data manipulation with dplyr Data Science Course with R Programming Course Overview This comprehensive data science with R programming course is specially designed for those who are willing to get a better understanding of R programming and data science to gain proficiency in the same. This online course will help you strengthen your knowledge of data science, R and Rstudio, basics, vectors and much more. This online data science with R programming course will also help you acquire knowledge about the Matrices, factors, data frame, list, logical and relational operations and conditional statements. You will also gain an understanding of the advanced features like loops, functions R packages, regular expressions, etc., to master R language and data science. By the end of the course, you will be able to write R programmes efficiently and be able to analyse data. You will also develop the skills to become a successful data scientist or data analyst after completing this course. Who should take this course? This comprehensive data science with R programming course is suitable for anyone looking to improve their job prospects or aspiring to accelerate their career in this sector and want to gain in-depth knowledge of R programming. Entry Requirements There are no academic entry requirements for this data science with r programming course, and it is open to students of all academic backgrounds. However, you are required to have a laptop/desktop/tablet or smartphone and a good internet connection. Assessment Method This data science with r programming course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner can grasp from each section. In the assessment pass mark is 60%. Course Curriculum Data Science Overview Introduction to Data Science Data Science Career of the Future What is Data Science Data Science As a Process Data Science Toolbox Data Science Process Explained What's Next R and RStudio Engine and Coding Environment Installing R and RStudio RStudio a Quick Tour Introduction to Basics Arithmetic With R Variable Assignment Basic Data Types in R Vectors Creating a Vector Naming a Vector Arithmetic Calculations on Vectors Vector Selection Selection by Comparison Matrices What's a Matrix Analyzing Matrices Naming a Matrix Adding Columns and Rows to a Matrix Selection of Matrix Elements Arithmetic with Matrices Factors What's a Factor Categorical Variables and Factor Levels Summarizing a Factor Ordered Factors Data Frames What's a Data Frame Creating a Data Frame Selection of Data Frame Elements Conditional Selection Sorting a Data Frame Lists Why Would You Need Lists Creating a List Selecting Elements From a List Adding More Data to The List Relational Operators Equality Greater and Less Than Compare Vectors Compare Matrices Logical Operators AND, OR, NOT Operators Logical Operators with Vectors and Matrices Reverse The Result Relational and Logical Operators Together Conditional Statements The IF Statement IF…ELSE The ELSEIF Statement Loops Write a While Loop Looping with More Conditions Break Stop The While Loop What's a For Loop. Loop Over a Vector Loop Over a List Loop Over a Matrix For Loop with Conditionals Using Next and Break with For Loop Functions What Is a Function. Arguments Matching Required and Optional Arguments Nested Functions Writing Own Functions Functions with No Arguments Defining Default Arguments in Functions Function Scoping Control Flow in Functions R Packages Installing R Packages Loading R Packages Different Ways to Load a Package The Apply Family - Lapply What Is Lapply and When Is Used. Use Lapply with User-Defined Functions Lapply and Anonymous Functions Use Lapply with Additional Arguments The Apply Family - Sapply & Vapply What Is Sapply. How to Use Sapply. Sapply with Your Own Function Sapply with a Function Returning a Vector When Can't Sapply Simplify. What Is Vapply and Why Is It Used. Useful Functions Mathematical Functions Data Utilities Regular Expressions Grepl & Grep Metacharacters Sub & Gsub More Metacharacters Dates And Times Today and Now Create and Format Dates Create and Format Times Calculations with Dates Calculations with Times Getting and Cleaning Data Get and Set Current Directory Get Data From The Web Loading Flat Files Loading Excel Files Plotting Data in R Base Plotting System Base Plots Histograms Base Plots Scatterplots Base Plots Regression Line Base Plots Boxplot Data Manipulation With dplyr Introduction to dplyr Package Using The Pipe Operator (%>%) Columns Component Select() Columns Component Rename() and Rename_with() Columns Component Mutate() Columns Component Relocate() Rows Component Filter() Rows Component Slice() Rows Component Arrange() Rows Component Rowwise() Grouping of Rows Summarise() Grouping of Rows Across() Covid-19 Analysis Task Assessment Assessment - Data Science Course with R Programming Recognised Accreditation CPD Certification Service This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Many organisations look for employees with CPD requirements, which means, that by doing this course, you would be a potential candidate in your respective field. Quality Licence Scheme Endorsed The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. It will give you a competitive advantage in your career, making you stand out from all other applicants and employees.     Certificate of Achievement Endorsed Certificate from Quality Licence Scheme After successfully passing the MCQ exam you will be eligible to order the Endorsed Certificate by Quality Licence Scheme. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. It will give you a competitive advantage in your career, making you stand out from all other applicants and employees. There is a Quality Licence Scheme endorsement fee to obtain an endorsed certificate which is £65. Certificate of Achievement from Lead Academy After successfully passing the MCQ exam you will be eligible to order your certificate of achievement as proof of your new skill. The certificate of achievement is an official credential that confirms that you successfully finished a course with Lead Academy. Certificate can be obtained in PDF version at a cost of £12, and there is an additional fee to obtain a printed copy certificate which is £35. FAQs Is CPD a recognised qualification in the UK? CPD is globally recognised by employers, professional organisations and academic intuitions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD-certified certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Are QLS courses recognised? Although QLS courses are not subject to Ofqual regulation, they must adhere to an extremely high level that is set and regulated independently across the globe. A course that has been approved by the Quality Licence Scheme simply indicates that it has been examined and evaluated in terms of quality and fulfils the predetermined quality standards. When will I receive my certificate? For CPD accredited PDF certificate it will take 24 hours, however for the hardcopy CPD certificate takes 5-7 business days and for the Quality License Scheme certificate it will take 7-9 business days. Can I pay by invoice? Yes, you can pay via Invoice or Purchase Order, please contact us at info@lead-academy.org for invoice payment. Can I pay via instalment? Yes, you can pay via instalments at checkout. How to take online classes from home? Our platform provides easy and comfortable access for all learners; all you need is a stable internet connection and a device such as a laptop, desktop PC, tablet, or mobile phone. The learning site is accessible 24/7, allowing you to take the course at your own pace while relaxing in the privacy of your home or workplace. Does age matter in online learning? No, there is no age limit for online learning. Online learning is accessible to people of all ages and requires no age-specific criteria to pursue a course of interest. As opposed to degrees pursued at university, online courses are designed to break the barriers of age limitation that aim to limit the learner's ability to learn new things, diversify their skills, and expand their horizons. When I will get the login details for my course? After successfully purchasing the course, you will receive an email within 24 hours with the login details of your course. Kindly check your inbox, junk or spam folder, or you can contact our client success team via info@lead-academy.org

About this Virtual Instructor Led Training (VILT) This 2 half-day Virtual Instructor-Led Training (VILT) course will guide participants on the technoeconomic aspects of capture, utilization and geological storage of carbon dioxide. The VILT course will address the methods and techniques used in the technoeconomic assessment of Carbon Capture, Utilization & Storage (CCUS) projects. It will explore in detail the factors that affect the cost-effectiveness of current and emerging technologies for CO2 capture, transport and geological storage, including monitoring and verification. Given that the successful deployment of CCUS may require economic incentives, technical and economic drivers such as technological innovation, optimization, source sink matching and emerging opportunities will also be discussed. In addition, using several worked examples and case studies, this VILT course will explain the principles behind the analysis of the costs and opportunities of a CCS / CCUS project from source to sink and examines the possibilities of using carbon dioxide from an economic perspective. Training Objectives Upon completion of this VILT course, participants will be able to: Describe the economic considerations for CCS / CCUS projects Measure and calculate the cost-effectiveness of CCS / CCUS Identify the economic drivers for CCS / CCUS Understand the value of source to sink matching Outline the economic and environmental opportunities as well as challenges with using carbon dioxide injection in a range of applications Recognize niche opportunities for CO2 storage (coal seams, basalts, salt and others)   Target Audience This VILT course is ideally suited for a technical audience such as geoscientists, petroleum and chemical engineers as well as professionals such as economists, regulators, legal staff and managers wishing to learn more about the details of economic aspects and the basis for techno-economic analysis of Carbon Capture, Utilization and Storage projects. The VILT course is presented in an interactive workshop format, allowing for discussions. Participants should have: Basic background knowledge of CCUS technologies Experience with oil and gas, coal or other energy projects Basic understanding of the energy industry Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 2 half-day sessions comprising 4 hours per day, with 2 breaks of 15 minutes per day. The VILT course is presented in an interactive workshop format that allows discussion. Course Duration: 2 half-day sessions, 4 hours per session (8 hours in total). Trainer Your expert course leader received his B.Eng. in Chemical and Environmental Systems in 2002 from Tecnológico de Monterrey, Mexico, and his Ph.D. in Chemical Engineering in 2008 from the University of New South Wales (UNSW), in Sydney, Australia, at the UNESCO Centre for Membrane Science and Technology. His doctoral used computational fluid dynamics (CFD) to analyse the flows within membrane modules used for water treatment and desalination. He also worked on a desalination linkage project between the UNSW and the European Union, as part of Framework Programme 6. From 2009 to 2014, he worked for the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC), where he led the research into CO2 Transport Networks, co-led the development of a techno-economic model for the analysis of Carbon Capture and Storage (CCS) projects, and collaborated on several consultancy and feasibility studies conducted by CO2CRC for both Government and Industry. From 2014 to 2019, he held a CONACYT Research Fellowship at the Instituto Tecnológico de Sonora (ITSON) in Mexico, where he led collaborative research projects dealing with RO membrane biofouling (IHE-Delft), membrane modifications, solar energy use for desalination (CSIR-CSMCRI India) and CFD modelling of the hydrodynamics in membrane modules (UMP Malaysia). Since July 2019, he is a Research Fellow in the School of Chemical and Biomolecular Engineering at the University of Sydney, where his research focuses on finding ways to reduce the cost, energy use and environmental impact of technologies for providing clean energy and water. From 2015 to 2020, he was a Member of the Board of Directors of the Mexican Society of Membrane Science and Technology. He guest edited a special edition on CCS for the Journal 'Technologies' and is currently an Editorial Board member for the journal, 'Energies', a peer-reviewed open-access scientific journal. His research interests include improving the efficiency of osmotic membrane separation processes, modelling complex processes involving heat and mass transfer, and exploring the economic drivers of low emission technologies such as the Carbon Capture and Storage (CCS) chain. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Register on the R Programming for Data Science today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion. The R Programming for Data Science is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The R Programming for Data Science Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the R Programming for Data Science, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's Next? 00:01:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00