178 Courses in Cardiff delivered Live Online

Duration 5 Days 30 CPD hours This course is intended for This course is designed for students who want to learn the R programming language, particularly students who want to leverage R for data analysis and data science tasks in their organization. The course is also designed for students with an interest in applying statistics to real-world problems. A typical student in this course should have several years of experience with computing technology, along with a proficiency in at least one other programming language. Overview In this course, you will use R to perform common data science tasks.You will: Set up an R development environment and execute simple code. Perform operations on atomic data types in R, including characters, numbers, and logicals. Perform operations on data structures in R, including vectors, lists, and data frames. Write conditional statements and loops. Structure code for reuse with functions and packages. Manage data by loading and saving datasets, manipulating data frames, and more. Analyze data through exploratory analysis, statistical analysis, and more. Create and format data visualizations using base R and ggplot2. Create simple statistical models from data. In our data-driven world, organizations need the right tools to extract valuable insights from that data. The R programming language is one of the tools at the forefront of data science. Its robust set of packages and statistical functions makes it a powerful choice for analyzing data, manipulating data, performing statistical tests on data, and creating predictive models from data. Likewise, R is notable for its strong data visualization tools, enabling you to create high-quality graphs and plots that are incredibly customizable. This course will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business. Lesson 1: Setting Up R and Executing Simple Code Topic A: Set Up the R Development Environment Topic B: Write R Statements Lesson 2: Processing Atomic Data Types Topic A: Process Characters Topic B: Process Numbers Topic C: Process Logicals Lesson 3: Processing Data Structures Topic A: Process Vectors Topic B: Process Factors Topic C: Process Data Frames Topic D: Subset Data Structures Lesson 4: Writing Conditional Statements and Loops Topic A: Write Conditional Statements Topic B: Write Loops Lesson 5: Structuring Code for Reuse Topic A: Define and Call Functions Topic B: Apply Loop Functions Topic C: Manage R Packages Lesson 6: Managing Data in R Topic A: Load Data Topic B: Save Data Topic C: Manipulate Data Frames Using Base R Topic D: Manipulate Data Frames Using dplyr Topic E: Handle Dates and Times Lesson 7: Analyzing Data in R Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Identify Missing Values Lesson 8: Visualizing Data in R Topic A: Plot Data Using Base R Functions Topic B: Plot Data Using ggplot2 Topic C: Format Plots in ggplot2 Topic D: Create Combination Plots Lesson 9: Modeling Data in R Topic A: Create Statistical Models in R Topic B: Create Machine Learning Models in R

Duration 3 Days 18 CPD hours This course is intended for Developers, Functional Testers, Test Automation Specialists, Performance Specialists, Environment and Data Specialists, Security Specialists Prerequisites for taking part in the workshop: It is recommended that participants should have completed the ISTQB© Certified Tester Foundation Level certification, or have attended the workshop. Overview Defined tasks need to be structured according to the technical requirements and the internal structure of the system needs to be analysed in detail in order to achieve the expected level of quality and detect errors during development. The ISTQB© Advanced Level Technical Test Analyst certification will teach you on the basis of the current ISTQB© Advanced Level syllabus. The various procedures, techniques and tools for non-functional system testing will be explained, and you will then be in a position to apply these in your future work as a Technical Test Analyst. The three-day certification will be followed by a two-hour examination. During the workshop, our experienced trainers will fully prepare you for the ISTQB© Advanced Level Technical Test Analyst examination. Following on from the ISTQB© Certified Tester Foundation Level training, this workshop covers the increasing technical challenges faced by system testing in particular. Topic 1 Tasks of a Technical Test Analyst in risk-based testing Topic 2 Structure-based testing: Simple condition test, condition/decision test, modified condition/decision test, multiple condition test, path test, API test, selection of structure-based procedures Topic 3 Analytical testing methods: static analysis (control flow analysis, data flow analysis, improved maintainability/adaptability with static analysis, call graphs), dynamic analysis (detection of memory leaks/?rogue? pointers, analysis of system performance) Topic 4 Quality features in technical tests (ISO 25000 standard): Planning aspects of technical testing, security testing, reliability testing, performance testing, resource usage, maintainability testing, portability testing Topic 5 Review checklists (architecture and code reviews) Topic 6 Testing tools and automation, tool integration, test automation projects, specific testing tools Topic 7 Practical exercises on all core topics Notes In order to take the examination, you must show at least 18 months? practical experience as a tester and be certified at ISTQB© Foundation Level. Confirmation from your employer or from your reference customers are accepted as proof of practical experience. Additional course details: Nexus Humans ISTQB Certified Tester, Advanced Level - Technical Test Analyst 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 ISTQB Certified Tester, Advanced Level - Technical Test Analyst course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This course is intended for The content is appropriate for test automation engineering roles, test manager roles, test lead roles, test architect roles, as well as developer roles. This course assumes you have a foundational understanding of testing and the purpose of automation. This course will be beneficial to anyone who is accountable for assessing, planning, designing, and implementing an integrated set of technology (testing infrastructure) that supports development, testing, and deployment. Overview Working in an interactive learning environment, led by our expert facilitator, attendees will learn to: Document the current state of test automation in your organization Define a custom test automation plan and architecture to fit their situation Create an initial implementation plan Identify initial key measures Develop a metrics dashboard for tracking the value of test automation Lay out a future strategy and roadmap to get there Introduction to Test Automation is a one-day, hands-on event designed to provide participants with the skills required to develop a custom test automation plan and architecture for their organization. Throughout the course, students will examine and work through various practical examples, learning how to create an integrated test automation plan and develop a test automation architecture. Participants will also learn about the possible real-world challenges they may face while trying to accomplish their goals, exploring the practical positive aspects of engaging their technical team, along with the possible frustrations of experiencing too much isolation between test automators and test designers. Getting Started Automation beginnings Software as a series of imperfect translations The Compelling Business Needs for Automation Automation the next opportunity Islands of Automation Getting products to market more quickly, at the right costs and quality Automation Challenges and Requirements Automation Challenges Test Automation Key Requirements Foundational material for your automation plan Templates Questions Examples Virtual Consulting included with this course Automation plan vision and strategy Vision, Strategy, Approach Example Defining your end in mind Deciding where to start Engaging Others Conducting a current state tools inventory Assessing your current state - tools and processes Tools inventory example and template Radar Chart as a means of presenting current state information Consider the best automation approach Waterfall vs. agile cycles of work Aligning tools with your methodologies Strategies for Automating The Test Automation Pyramid Developing your test automation architecture Blocks of automation capabilities Islands of Automation Integrated Tools Architecture Template Integrated Tools Architecture Examples Test automation architecture examples Examples of different test automation architectures and frameworks Selenium Key Test Automation Architecture Characteristics Acceptance test-driven and behavior-driven testing overview Test automation approaches FitNesse Cucumber Gherkin script overview Tool workflow Considerations for what to automate and when Categories of tests that might be automated We have many tool choices Key points in Test Tool Architecture Planning Piloting and Implementing automation Selecting and evaluating tools and rolling them out Selling Automation - qualitative questions Selling Automation - quantitative questions Measuring automation benefits Measures in technical terms Measures in business terms Measures of testing vs. measures of test automation Next Steps A few keys to success

3 Months Subscription Up to 45 mock tests Detailed feedback and scoring on all skills Progress report Model Answer Library on Writing Four free one-to-one sessions with an IELTS Expert

We offer the most advanced “Certified Six Sigma Green Belt Course” as per the curriculum outline of The ASQ Body of Knowledge and accredited by top international Lean & Six Sigma accreditation bodies. Six Sigma Green Belt Deliverables: 22+ hours of Instructor-led interactive virtual classroom session on the weekend Access to 45+ hours of Module based Six Sigma lectures via LMS 100+ Toolkits and Project Templates for Analysis and Implementation Soft copy of Lean Six Sigma Green Belt Body of Knowledge Live Data-oriented project, with Scenario and Analysis Methodology 20+ Dummy Projects and Case studies for Lean Six Sigma Application Support via subject expert through telephonic discussion on the weekend Sample Questions and Examination Guide for Certification Preparation Pre and Post assignments for process groups and knowledge areas Project implementation support and Data visualization using MINITAB PRO CLSSGB certification examination anytime within the 90 days course duration Certification Validation Tool for third-party credentials validation PARTICULARS Duration (Hours) 1. Define Phase 22 2. Measure Phase 14 3. Analyse Phase 20 4. Improve Phase 7 5. Control Phase 7 Total Duration 70 (Hours) Introduction Become an expert in six sigma methodology by getting hands-on knowledge on DMAIC, Project Charter, Process Capability, FMEA, Sigma calculation, Test of Hypothesis, Control Charts, VSM, JIT using real case scenarios and real-life examples. Lean and DMAIC methodologies using live projects. The Six Sigma Certification is accredited by The Council for Six Sigma Certification. The certification also acknowledges the BOK outline of The American Society for Quality, USA. The course features world-class content with live projects and MINITAB PRO driven data analysis training with end to end support in project implementation by Master Black Belt Experts and Trainers. What is Six Sigma Certification? A person with Six Sigma certification has problem-solving abilities. Someone may gain Green Belt, Black Belt or Master Black Belt certification. The higher certification one attains, the more is the ability to solve complex organizational problems. Six Sigma certification is a process of individual’s knowledge validation using a classification system, generally referred to as "Belts" (Green Belt, Black Belt, Master Black Belt) This verification test individual commands over six sigma methodology and tools. The belt classification shows the position these certified individuals would occupy in an organizational structure and job roles. Six Sigma Green Belt training is especially for the future project leaders of Lean Six Sigma projects. We deliberately mix non-profit with profit participants. There will then be fun, useful discussions and knowledge exchanges during the training sessions. In addition, there are also many self-employed people who follow the LSS Green Belt training to increase their expertise as in a trimmer. What do you do to get the Six Sigma Green Belt certificate? Our Six Sigma Green Belt training consists of a number of components: Training: in an intensive training program you learn the background of Lean and Six Sigma and we put what we have learned into practice with different simulations. Extra: With our Body of Knowledge and whitepapers you place what you have learned in a theoretical framework. The program also contains various homework assignments, in which we focus, among other things, on the use of MINITAB PRO. Follow-up: During the training, you will receive an access code to an e-learning module. You can pass the substance again in an interactive way. Exam: On the last training day you will make the CLSSGB Green Belt exam. If you succeed, you will immediately receive the official Certified Lean Six Sigma Green Belt certification. Global Recognition of Your Certification: Agenda Overview of Six Sigma and the organizationSix Sigma and organizational goalsValue of six sigmaOrganizational goals and six sigma projectsOrganizational drivers and metricsLean principles in the organizationLean conceptsValue-streaming mappingDesign for six sigma (DFSS) methodologiesRoadmaps for DFSSBasic failure mode and effects analysis (FMEA)Design FMEA and process FMEA Define PhaseProject identificationProject SelectionProcess elementsBenchmarkingProcess inputs and outputsOwners and stakeholders Voice of the customer (VOC) Customer identificationCustomer dataCustomer requirements Project Management Basics Project charterProject scopeProject metricsProject planning toolsProject documentationProject risk analysisProject closureManagement and planning toolsBusiness results for projectsProcess performance CommunicationTeam dynamics and performanceTeam stages and dynamicsTeam roles and responsibilitiesTeam toolsTeam Communication Measure PhaseProcess analysis and documentationProbability and statisticsBasic probability conceptsCentral limit theorem, Statistical distributions, Collecting and summarizing dataTypes of data and measurement scalesSampling and data collection methodsDescriptive statisticsGraphical methodsMeasure Phase (contd E. Measurement system analysis (MSA) F. Process and performance capabilityProcess performance vs. process specificationsProcess capability studiesProcess capability (Cp, Cpk) and process performance (Pp, Ppk) indicesShort-term vs. long-term capability and sigma shift Analyze PhaseExploratory data analysisMulti-vari studiesCorrelation and linear regression B, Hypothesis testingBasics Tests for means, variances, and proportionsIntroduction to MINITAB Data analysis Improve Phase of Six SigmaDesign of experiments (DOE)Basic terms, DOE graphs, and plotsThe root cause analysisLean Tools 1. Waste elimination 2. Cycle-time reduction 3. Kaizen and kaizen blitz V1. Control PhaseStatistical process control (SPC)SPC BasicsRational subgroupingControl chartsControl planLean tools for process controlTotal productive maintenance (TPM)Visual factory Project Implementation & SupportMINITAB Practice and guidance for projectProject implementation supportTemplates and Toolkits application for Project workSupport on Data Project, Implementation and project completion BenefitsFrom the course Learn the principles and philosophy behind the Six Sigma technique Learn to apply statistical methods to improve business processes Design and implement Six Sigma projects in a practical scenario Learn the DMAIC process and various tools used in Six Sigma methodology Knowledge of Six Sigma Green Belt Professional enables you to understand real-world business problems, increase an organization's revenue by streamlining the process, and become an asset to an organization According to Villanova University, employers such as United Health Group, Honeywell, GE and Volkswagen have been actively seeking professionals with Six Sigma to fill a variety of positions The Training enhances your skills and enables you to perform roles like Quality Manager, Quality Analyst, Finance Manager, Supervisor, Quality Control, etc. According to Indeed.com, the national average salary for a Six Sigma Green Belt is $72,000 per year in the United States.   From the workshop Instructor LED training by Six Sigma Black Belt and Master Belt experts to make candidate learn the real scenario of six sigma tools and methodology Learn the principles and philosophy behind the Six Sigma method Dummy project by instructors to make candidate get a hands-on six sigma projects Downloadable Six Sigma PPT & Six Sigma PDF Industry Based case studies High-Quality training from an experienced trainer The Program extensively uses Minitab, specialized statistical software. It provides you with a thorough knowledge of Six Sigma philosophies and principles (including supporting systems and tools). Know about six sigma certification cost and six sigma green belt certification cost. Who should attend? The Six Sigma program is designed for professionals and students who want to develop the ability to lead process improvement initiatives. Six Sigma tools and process is widely used in all business processes. Six Sigma is applicable in all industry and in all functional areas. An indicative list of participants in our Green Belt program could include: Financial/business analyst Commodity manager Project manager Quality manager Production manager Production Engineer Business development manager Manufacturing process engineer Continuous improvement director Business managers or consultants Project manager/Program Manager Director or VP of operations CEO, CFO, CTO Certification On successful completion of the course and course requisites, the candidate will receive Internationally recognized Six Sigma Green Belt Certification. This course offers Six Sigma Certification Validation Tool for Employers Your Six Sigma Certification Validation Tool can be used by employers, clients and other stakeholders to validate the authenticity of your Six Sigma Certifications you have received. Using the programming code located on your certified LSSGB certification, one can see all your training and certification details online.

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

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Duration 5 Days 30 CPD hours This course is intended for This course is designed for application developers. Overview Describe the benefits of implementing a decision management solution with Operational Decision Manager.Identify the key user roles that are involved in designing and developing a decision management solution, and the tasks that are associated with each role.Describe the development process of building a business rule application and the collaboration between business and development teams.Set up and customize the Business Object Model (BOM) and vocabulary for rule authoring. Implement the Execution Object Model (XOM) that enables rule execution.Orchestrate rule execution through ruleflows. Author rule artifacts to implement business policies.Debug business rule applications to ensure that the implemented business logic is error-free.Set up and customize testing and simulation for business users.Package and deploy decision services to test and production environments.Integrate decision services for managed execution within an enterprise environment.Monitor and audit execution of decision services.Work with Operational Decision Manager features that support decision governance. This course introduces developers to IBM Operational Decision Manager V8.9.2. It teaches participants the concepts and skills required to design, develop, and integrate a business rule solution with Operational Decision Manager. This course begins with an overview of Operational Decision Manager, which is composed of two main environments: Decision Server for technical users and Decision Center for business users. The course outlines the collaboration between development and business teams during project development. Through instructor-led presentations and hands-on lab exercises, participants learn about the core features of Decision Server, which is the primary working environment for developers. Participants design decision services and work with the object models that are required to author and execute rule artifacts. Participants gain experience with deployment and execution, and work extensively with Rule Execution Server. In addition, students become familiar with rule authoring so that you can support business users to set up and customize the rule authoring and validation environments. Participants also learn how to use Operational Decision Manager features to support decision governance. Introducing IBM Operational Decision Manager Exercise: Operational Decision Manager in action Developing decision services Exercise: Setting up decision services Programming with business rules and developing object models Exercise: Working with the BOM Exercise: Refactoring Orchestrating ruleset execution Exercise: Working with ruleflows Authoring rules Exercise: Exploring action rules Exercise: Authoring action rules Exercise: Authoring decision tables Customizing rule vocabulary with categories and domains Exercise: Working with static domains Exercise: Working with dynamic domains Working with queries Exercise: Working with queries Debugging rules Exercise: Executing rules locally Exercise: Debugging a ruleset Enabling tests and simulations Exercise: Enabling rule validation Managing deployment Exercise: Managing deployment Exercise: Using Build Command to build RuleApps Executing rules with Rule Execution Server Exercise: Exploring the Rule Execution Server console Auditing and monitoring ruleset execution Exercise: Auditing ruleset execution through Decision Warehouse Working with the REST API Exercise: Executing rules as a hosted transparent decision service (HTDS) Additional course details: Nexus Humans WB402 IBM Developing Rule Solutions in IBM Operational Decision Manager V8.9.2 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 WB402 IBM Developing Rule Solutions in IBM Operational Decision Manager V8.9.2 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: DevOps engineers DevOps architects Operations engineers System administrators Developers Overview In this course, you will learn to: Use DevOps best practices to develop, deliver, and maintain applications and services at high velocity on AWS List the advantages, roles and responsibilities of small autonomous DevOps teams Design and implement an infrastructure on AWS that supports DevOps development projects Leverage AWS Cloud9 to write, run and debug your code Deploy various environments with AWS CloudFormation Host secure, highly scalable, and private Git repositories with AWS CodeCommit Integrate Git repositories into CI/CD pipelines Automate build, test, and packaging code with AWS CodeBuild Securely store and leverage Docker images and integrate them into your CI/CD pipelines Build CI/CD pipelines to deploy applications on Amazon EC2, serverless applications, and container-based applications Implement common deployment strategies such as 'all at once,' 'rolling,' and 'blue/green' Integrate testing and security into CI/CD pipelines Monitor applications and environments using AWS tools and technologies DevOps Engineering on AWS teaches you how to use the combination of DevOps cultural philosophies, practices, and tools to increase your organization?s ability to develop, deliver, and maintain applications and services at high velocity on AWS. This course covers Continuous Integration (CI), Continuous Delivery (CD), infrastructure as code, microservices, monitoring and logging, and communication and collaboration. Hands-on labs give you experience building and deploying AWS CloudFormation templates and CI/CD pipelines that build and deploy applications on Amazon Elastic Compute Cloud (Amazon EC2), serverless applications, and container-based applications. Labs for multi-pipeline workflows and pipelines that deploy to multiple environments are also included. Module 0: Course overview Course objective Suggested prerequisites Course overview breakdown Module 1: Introduction to DevOps What is DevOps? The Amazon journey to DevOps Foundations for DevOps Module 2: Infrastructure automation Introduction to Infrastructure Automation Diving into the AWS CloudFormation template Modifying an AWS CloudFormation template Demonstration: AWS CloudFormation template structure, parameters, stacks, updates, importing resources, and drift detection Module 3: AWS toolkits Configuring the AWS CLI AWS Software Development Kits (AWS SDKs) AWS SAM CLI AWS Cloud Development Kit (AWS CDK) AWS Cloud9 Demonstration: AWS CLI and AWS CDK Hands-on lab: Using AWS CloudFormation to provision and manage a basic infrastructure Module 4: Continuous integration and continuous delivery (CI/CD) with development tools CI/CD Pipeline and Dev Tools Demonstration: CI/CD pipeline displaying some actions from AWS CodeCommit, AWS CodeBuild, AWS CodeDeploy and AWS CodePipeline Hands-on lab: Deploying an application to an EC2 fleet using AWS CodeDeploy AWS CodePipeline Demonstration: AWS integration with Jenkins Hands-on lab: Automating code deployments using AWS CodePipeline Module 5: Introduction to Microservices Introduction to Microservices Module 6: DevOps and containers Deploying applications with Docker Amazon Elastic Container Service and AWS Fargate Amazon Elastic Container Registry and Amazon Elastic Kubernetes service Demonstration: CI/CD pipeline deployment in a containerized application Module 7: DevOps and serverless computing AWS Lambda and AWS Fargate AWS Serverless Application Repository and AWS SAM AWS Step Functions Demonstration: AWS Lambda and characteristics Demonstration: AWS SAM quick start in AWS Cloud9 Hands-on lab: Deploying a serverless application using AWS Serverless Application Model (AWS SAM) and a CI/CD Pipeline Module 8: Deployment strategies Continuous Deployment Deployments with AWS Services Module 9: Automated testing Introduction to testing Tests: Unit, integration, fault tolerance, load, and synthetic Product and service integrations Module 10: Security automation Introduction to DevSecOps Security of the Pipeline Security in the Pipeline Threat Detection Tools Demonstration: AWS Security Hub, Amazon GuardDuty, AWS Config, and Amazon Inspector Module 11: Configuration management Introduction to the configuration management process AWS services and tooling for configuration management Hands-on lab: Performing blue/green deployments with CI/CD pipelines and Amazon Elastic Container Service (Amazon ECS) Module 12: Observability Introduction to observability AWS tools to assist with observability Hands-on lab: Using AWS DevOps tools for CI/CD pipeline automations Module 13: Reference architecture (Optional module) Reference architectures Module 14: Course summary Components of DevOps practice CI/CD pipeline review AWS Certification

Medical Terminology Training Course Overview: This Medical Terminology Training course provides a comprehensive foundation in understanding the language used in healthcare settings. Learners will gain a solid understanding of medical terms related to human anatomy, various body systems, lab tests, and diagnostic equipment. The course is designed to offer practical value by enhancing communication within healthcare teams and improving accuracy in documentation. By the end of the course, learners will be able to recognise and correctly use medical terminology in professional settings, leading to better collaboration and patient care. Course Description: This course covers key areas of medical terminology, from human anatomy and physiological systems to diagnostic equipment and laboratory tests. Learners will explore the meanings behind commonly used medical terms, including acronyms and abbreviations, making it easier to communicate complex medical information effectively. Each module is structured to help learners familiarise themselves with different systems of the body, such as the cardiovascular, respiratory, and musculoskeletal systems, and the language used to describe them. By the end of the course, learners will have acquired the skills to confidently engage in medical environments, improving both their professional competency and their ability to interpret medical documents. Medical Terminology Training Curriculum: Module 01: Human Body Vocabulary with Pictures Module 02: Equipment, Instruments and Lab Tests Module 03: Acronyms and Abbreviation Module 04: Digestive System Module 05: Cardiovascular System Module 06: Blood and Immunity System Module 07: Respiratory System Module 08: Musculoskeletal System Module 09: Central Nervous System (See full curriculum) Who is this course for? Individuals seeking to understand medical terminology. Professionals aiming to enhance communication within healthcare teams. Beginners with an interest in medical terminology or healthcare. Those working in administrative or support roles in healthcare settings. Career Path Medical Receptionist Health Administrator Medical Secretary Clinical Support Worker Laboratory Assistant Medical Records Coordinator