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This course aims to prepare individuals for the AWS Certified Solutions Architect Associate exam. It covers essential AWS services, cloud architecture design, deployment strategies, and best practices for managing various AWS components. Learning Outcomes: Understand the fundamental concepts of AWS Cloud Services and their application in real-world scenarios. Design and implement AWS Storage and Virtual Private Cloud (VPC) solutions. Learn how to design, implement, and manage Compute Services effectively. Master Identity and Access Management (IAM) and its best practices for secure access control. Explore Auto Scaling Solutions and Virtual Network Services to optimize AWS infrastructure. Gain proficiency in deploying applications and databases on AWS. Discover additional AWS services and their integration for comprehensive cloud solutions. Develop insights into achieving operational excellence with AWS services. Why buy this AWS Certified Solutions Architect Associate Preparation? 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This AWS Certified Solutions Architect Associate Preparation course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This AWS Certified Solutions Architect Associate Preparation does not require you to have any prior qualifications or experience. You can just enrol and start learning.This AWS Certified Solutions Architect Associate Preparation was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This AWS Certified Solutions Architect Associate Preparation is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Section 01: Introduction Introduction 00:03:00 Section 02: Exam Tips and Tricks What is AWS? 00:02:00 Why use AWS? 00:03:00 How to Get Started with AWS 00:04:00 AWS Certifications 00:04:00 Preparation Resources 00:02:00 Benefits of Certification 00:02:00 AWS CSA-A Overview 00:04:00 What's New on the 2020 Updated Exam? 00:03:00 AWS CSA-A Exam Objectives 00:06:00 The Four Key Areas (Compute, Networking, Storage, and Databases) 00:04:00 Master the Knowledge Areas 00:02:00 Use the System 00:05:00 Take Notes 00:03:00 Be Mentally and Physically Prepared 00:04:00 Take the Exam 00:04:00 Section 03: AWS Cloud Services Overview Cloud Computing Defined 00:08:00 Benefits of Cloud Computing 00:10:00 Cloud Computing Models 00:07:00 History 00:07:00 Platform 00:06:00 Services, Part 1 00:10:00 Services, Part 2 00:08:00 Security and Compliance 00:07:00 Regions and Availability 00:06:00 Section 04: AWS Storage Design Storage Services 00:07:00 S3 Storage Class 00:07:00 S3 Terminology 00:09:00 S3 Advanced Features 00:08:00 Creating S3 Buckets Lab 00:08:00 S3 Bucket Properties 00:08:00 S3 Managing Objects Lab 00:11:00 Glacier 00:07:00 Setting up a Glacier Vault Lab 00:08:00 S3 and Tape Gateway 00:06:00 S3 Enhanced Features 00:08:00 Elastic Block Store (EBS) 00:08:00 Creating EBS Volumes Lab 00:07:00 Elastic File System (EFS) 00:07:00 Creating an EFS File System Lab 00:07:00 EFS and PrivateLink 00:03:00 Intro to Amazon FSx 00:06:00 Hands-on with FSx 00:06:00 Integrating on-Premises Storage 00:07:00 Storage Access Security Lab 00:10:00 Storage Performance 00:08:00 Section 05: Virtual Private Cloud (VPC) Virtual Private Cloud (VPC) Overview 00:10:00 Creating a VPC Lab 00:11:00 Configuring DHCP Options Lab 00:04:00 Elastic IP Addresses 00:07:00 Elastic Network Interfaces (ENIs) 00:05:00 Endpoints 00:07:00 VPC Peering 00:08:00 Creating a VPC Peering Connection Lab 00:10:00 Security Groups Overview 00:07:00 Network Address Translation (NAT) 00:11:00 Gateways (VPGs and CGWs) 00:08:00 VPN Configuration Option 00:04:00 Section 06: Compute Services Design EC2 Overview 00:11:00 EC2 Instance Types 00:11:00 EC2 Pricing 00:13:00 EBS and EC2 00:05:00 Section 07: Compute Services Implementation Launching an EC2 Linux Instance Lab 00:13:00 Configuring an EC2 Linux Instance Lab 00:08:00 Setting up an EC2 Windows Instance Lab 00:12:00 Shared Tenancy 00:05:00 Dedicated Hosts 00:08:00 Dedicated Instances 00:06:00 AMI Virtualization 00:12:00 Section 08: Compute Services Management Instance Management 00:09:00 Connecting to Instances Lab 00:09:00 Working with Security Groups 00:10:00 Working with Security Groups Lab 00:10:00 Advanced EC2 Management 00:06:00 AWS Batch 00:06:00 Elastic Container Service (ECS) 00:08:00 Elastic Beanstalk Environment 00:11:00 Section 09: Identity and Access Management (IAM) Identity and Access Management (IAM) Overview 00:07:00 Principals 00:10:00 Root User 00:06:00 Authentication 00:06:00 Authorization Policies 00:13:00 Multi-Factor Authentication 00:08:00 Key Rotation 00:10:00 Multiple Permissions 00:06:00 AWS Compliance Program 00:07:00 AWS Security Hub 00:06:00 Shared Responsibility Models 00:06:00 Section 10: IAM Best Practices User Accounts 00:11:00 Password Policies 00:09:00 Credential Rotation 00:06:00 Principle of Least Privilege 00:05:00 IAM Roles 00:08:00 Policy Conditions 00:08:00 CloudTrail 00:12:00 Section 11: Auto Scaling Solutions Auto Scaling Overview 00:06:00 Auto Scaling Groups 00:04:00 Termination Policies 00:07:00 Auto Scaling Configuration Lab 00:13:00 Launch Methods 00:04:00 Load Balancer Concepts 00:08:00 Elastic Load Balancing (ELB) 00:10:00 Section 12: Virtual Network Services DNS 00:14:00 Configuring DNS Lab 00:07:00 Configuring Route 53 Lab 00:13:00 Configuring ACLs and NACLs Lab 00:09:00 Flow Logs 00:07:00 Section 13: AWS Application Deployment Application and Deployment Services 00:04:00 Lambda 00:06:00 API Gateway 00:09:00 Kinesis 00:06:00 Kinesis Data Streams and Firehose 00:06:00 Kinesis Data Analytics 00:04:00 Reference Architectures 00:06:00 CloudFront 00:10:00 Web Application Firewall (WAF) 00:09:00 Simple Queue Service (SQS) 00:10:00 Simple Notification Service (SNS) 00:08:00 Simple Workflow (SWF) 00:07:00 Step Functions 00:05:00 OpsWorks 00:08:00 Cognito 00:04:00 Elastic MapReduce (EMR) 00:05:00 CloudFormation 00:10:00 CloudFormation Properties 00:03:00 CloudWatch 00:06:00 Trusted Advisor 00:07:00 Organizations 00:09:00 Section 14: AWS Database Design Database Types 00:08:00 Relational Databases 00:08:00 Database Hosting Methods 00:05:00 High Availability Solutions 00:06:00 Scalability Solutions 00:06:00 Database Security 00:08:00 Aurora 00:06:00 Redshift 00:11:00 DynamoDB 00:10:00 Section 15: Database Deployment DynamoDB Tables Lab 00:08:00 MySQL Lab 00:13:00 Configuration Lab 00:13:00 Backups Lab 00:04:00 Restore Lab 00:04:00 Snapshot Lab 00:08:00 Monitoring Lab 00:06:00 Section 16: Additional AWS Services Media Content Delivery 00:13:00 Desktop and Appstreaming 00:06:00 ElastiCache 00:05:00 Security Services Lab 00:12:00 Analytics Engines 00:11:00 Development Operations (DevOps) 00:12:00 AWS Solutions 00:05:00 AWS Transit Gateway 00:03:00 AWS Backup 00:04:00 AWS Cost Explorer 00:04:00 Section 17: Operational Excellence with AWS The Operational Excellence Process 00:08:00 Widget Makers Scenario 00:06:00 Resilient Design 00:08:00 Resilient Design Scenario 00:05:00 Performant Design 00:09:00 Performant Design Scenario 00:06:00 Secure Design 00:08:00 Secure Design Scenario 00:05:00 Cost Optimization 00:07:00 Cost Optimization Scenario 00:05:00 General Best Practices 00:07:00
Customers are astute and well-practised in researching and seeking information, solutions and added value in the minimum number of clicks online. There's only so much time they're willing to spend carrying on clicking. This mentality isn't just restricted to the world of B2C. In our increasingly hectic world, where information is expected to be available instantly, it applies just as much to B2B. In this workshop, we look at how putting yourself in the shoes of your customer and mapping their decision-making and buying journey is critical to ensuring that you provide what they perceive as fast solutions and added value. You will learn all about the three pillars for creating competitive brand experiences: Customer engagement planning puts you firmly in the shoes of your customer, helping you to build meaningful marketing communications delivered through the right resources at the right time to inspire your customers to engage with you. This programme will help participants to: Understand the evolution of the customer buying journey Map a customer buying journey for your brand or solutions Understand the customer micro-moments and signals indicating interest and buying intent, both online and offline Apply the psychology of branding to build marketing communications with impact Develop sales and marketing content that differentiates your brand(s) from the competition by demonstrating unique value and how you can meet your customer's needs 1 The evolution of the customer journey Understand how the use of mobile has had an impact on the customer buying journey where today's customers can research and compare products and solutions whenever and wherever they like, making the purchase journey even less linear Explore how marketers are adapting to this new customer behaviour and drawing upon various strategies to win the hearts and minds of their audiences 2 The See-Think-Do-Care framework Explore the many different frameworks used to track the customer journey Understand and apply the modern marketing model, where the internet has enabled the customer to hop between multiple touchpoints before making a purchase decision 3 Customer micro-moments and signals in their buying journey Understand the online and offline moments when customers seek information to research and make buying decisions Apply this understanding to build a marketing communication plan to reach customers at all stages of their buying journey 4 The role of branding in the customer journey Explore the psychology of branding Learn how to ensure your branding is relevant to your target customer needs Bring together your brand value and story to achieve brand loyalty 5 The Why-How-What framework Apply a systematic approach to build a successful and compelling brand Understand how starting with 'why' will help build your brand purpose Apply the content marketing matrix to communicate your brand's value Apply the hero-help-hub model to build engaging content marketing Actionable outcomes We will use your brand examples to provide opportunities for practice: You will learn and reflect on best practice examples of customer engagement You will discover your brand value, purpose and the 'sweet spot' to drive engagement with your customers You will create a customer engagement plan that can be implemented immediately within your business You will receive immediate feedback on your customer engagement plan You will have the opportunity to share common issues and solutions with your colleagues in the group
Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum 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? 00:02:00 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 Assignment Assignment - R Programming for Data Science 00:00:00
Teaching Assistants Level 1,2 & 3 Is there any opportunity to be a certified teaching assistant to get a reputed job in the UK? The teaching assistant course provides comprehensive training for individuals aspiring to support educators and facilitate student learning in educational settings. This teaching assistant participant explores the fundamental principles of teaching and learning. As a teaching assistant, you will know how to manage classroom strategies and effective communication techniques. The Teaching Assistants Level 1,2 & 3 curriculum covers topics such as child development, differentiated instruction, and special educational needs support. Through practical experiences and theoretical insights, students in the Teaching Assistants Level 1,2 & 3 course learn to assist in lesson planning and implement instructional activities. As a teaching assistant, you can provide individualised support to students. Enrol in our teaching assistant programme to work collaboratively with teachers, contribute to student success, and create inclusive learning environments. Why choose this Teaching Assistant: Teaching Assistant Course from the School of Health Care? Self-paced Teaching Assistant: Teaching Assistant course, access available from anywhere in the world. High-quality study materials that are easy to understand. Teaching Assistant: Teaching Assistant Course developed by industry experts. After each module, there will be an MCQ quiz to assess your learning. Assessment results are generated automatically and instantly. 24/7 support is available via live chat, phone call, or email. Free PDF certificate after completing the Teaching Assistant: Teaching Assistant Course. Main Course: Teaching Assistant Level 1 Free Courses included with Teaching Assistant Course Course 01: Teaching Assistant Level 2 Course 02: Teaching Assistant Level 3 [ Note: Free PDF certificate as soon as completing the Teaching Assistant: Teaching Assistant Course] Teaching Assistants Level 1,2 & 3 In this Teaching Assistants Level 1,2 & 3 course, you will also learn about a range of concepts and techniques that have influenced modern primary teaching support practices. Enroll in our Teaching Assistants Level 1, 2, and 3 course right now to begin your path to a rewarding career in teaching! Who is this course for? Teaching Assistants Level 1,2 & 3 For those who desire to work as teaching assistants and obtain a recognised qualification in this profession, this Teaching Assistants Level 1,2 & 3 course has been created. This Teaching Assistants Level 1,2 & 3 course will help you to go advance level in the field of Teaching Assistant. You can enrol on higher level Teaching Assistant courses, such as: Level 2 Award in Teaching Assistant Practice Level 2 Certificate in Teaching Assistant Practice Level 3 Certificate in Teaching Assistant Studies Level 3 Diploma in Teaching Assistant Studies Level 4 Certificate in Teaching Assistant Leadership Level 4 Diploma in Teaching Assistant Leadership Level 5 Diploma in Teaching Assistant Management Level 6 Diploma in Teaching Assistant Research Level 4 Certificate in Higher Level Teaching Assistant (HLTA) Level 5 Higher Level Teaching Assistant (HLTA) Requirements Teaching Assistants Level 1,2 & 3 Online To enrol in this Teaching Assistants: Teaching Assistants, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Teaching Assistants: Teaching Assistants course. Be energetic and self-motivated to complete our Teaching Assistants: Teaching Assistants course. Basic computer Skill is required to complete our Teaching Assistants: Teaching Assistants course. If you want to enrol in our Teaching Assistants: Teaching Assistants course, you must be at least 15 years old. Career path Teaching Assistants Level 1,2 & 3 This credential in Teaching Assistants Level 1,2 & 3 courses will open up several paths including: Higher Level Teaching Assistant Primary Teaching Assistant Montessori Educator
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