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***24 Hour Limited Time Flash Sale*** Google Analytics Course - Taking Your Business to the Next Level Course Admission Gifts FREE PDF & Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter Are you a professional feeling stuck in your career, struggling to keep up with the ever-changing demands of the industry? Or perhaps you're a beginner, unsure of where to start or how to break into your desired field. Whichever stage you're in, our exclusive Google Analytics for Beginners - Master Google Analytics Bundle provides unique insights and tools that can help you achieve your goals. Designed to cater to the needs of both seasoned professionals and aspiring newcomers, our Google Analytics for Beginners - Master Google Analytics Course bundle is a comprehensive program that will equip you with the essential skills and knowledge you need to succeed. 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24 Hours Left! Don't Let the Winter Deals Slip Away - Enrol Now in this Data Analyst Course! Unlock the power of Data Analysis and become a master of insights with our Data Analyst (Data Analytics) course. Gain the Data Analyst skills to decipher complex datasets, extract valuable information, and make data-driven decisions that drive success as a Data Analyst. Join us on this Data Analyst (Data Analytics) course and embark on a journey to transform raw data into actionable intelligence, empowering businesses to thrive in the digital age with Data Analyst (Data Analytics) Courses Included in This Data Analyst (Data Analytics) Training: Course 01: Diploma in Data Analysis at QLS Level 5 Course 02: Diploma in Business Data Analysis at QLS Level 5 Course 03: SQL Masterclass: SQL For Data Analytics Learning outcome of this Data Analyst (Data Analytics) course: Master retail Data analytics for data-driven decisions. Uncover consumer behavior with retail psychology. 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Learn Data Analyst (Data Analytics) from anywhere in the world Data Analyst (Data Analytics) is affordable and simple to understand Data Analyst (Data Analytics) is entirely online, interactive lesson with voiceover audio Lifetime Access to the Data Analyst (Data Analytics) course materials Data Analyst (Data Analytics) comes with Data Analysis Assessment Process of Data Analyst(Data Analytics) QLS Course: Assignment & MCQ Based 60% Marks to pass Instant Assessment Certificate of Data Analyst QLS Endorsed Certificate (additional cost) CPD Approved Certificate CPD 150 CPD hours / points Accredited by CPD Quality Standards Course 01- Data Analysis: Modifying a Worksheet 25:59 1: Insert, Delete, and Adjust Cells, Columns, and Rows Preview 10:08 2: Search for and Replace Data 08:38 3: Use Proofing and Research Tools 07:13 Working with Lists 37:47 4: Sort Data 10:03 5: Filter Data 09:49 6: Query Data with Database Functions 09:02 7: Outline and Subtotal Data 08:53 Analyzing Data 12:33 8: Apply Intermediate Conditional Formatting 06:50 9: Apply Advanced Conditional Formatting 05:43 Visualizing Data with Charts 38:03 10: Create Charts 13:18 11: Modify and Format Charts 12:16 12: Use Advanced Chart Features 12:29 Using PivotTables and PivotCharts 44:25 13: Create a PivotTable 13:28 14: Analyze PivotTable Data 12:00 15: Present Data with PivotCharts 07:35 16: Filter Data by Using Timelines and Slicers 11:22 Working with Multiple Worksheets and Workbooks 24:00 17: Use Links and External References 12:24 18: Use 3-D References 05:51 19: Consolidate Data 05:45 Using Lookup Functions and Formula Auditing 30:28 20: Use Lookup Functions 12:45 21: Trace Cells 09:05 22: Watch and Evaluate Formulas 08:38 Automating Workbook Functionality 35:27 23: Apply Data Validation 13:28 24: Search for Invalid Data and Formulas with Errors 04:06 25: Work with Macros 17:53 Creating Sparklines and Mapping Data 07:19 26: MapData 07:19 Forecasting Data 27:54 27: Determine Potential Outcomes Using Data Tables 08:47 28: Determine Potential Outcomes Using Scenarios 09:16 29: Use the Goal Seek Feature 04:16 30: Forecasting Data Trends 05:35 Course 02- Module 1: Introduction to Retail Analytics 32:03 31: Introduction to Retail Analytics Preview 32:03 Module 2: Retail Psychology 07:06 32: Retail Psychology 07:06 Module 3: Retail and Data Analytics 12:00 33: Retail and Data Analytics 12:00 Module 4: Benefits of Retail Analytics 16:26 34: Benefits of Retail Analytics 16:26 Module 5: Retail Strategy 09:44 35: Retail Strategy 09:44 Module 6: Retail Buying and Merchandising 11:27 36: Retail Buying and Merchandising 11:27 Module 7: Forecasting 23:27 37: Forecasting 23:27 Module 8: Retail Pricing 16:30 38: Retail Pricing 16:30 Module 9: Analytics Software 19:37 39: Analytics Software 19:37 Module 10: Supply Chain Management in Retailing 07:37 40: Supply Chain Management in Retailing 07:37 Module 11: The Sales Process and Dealing with Customers at the Checkout 04:57 41: The Sales Process and Dealing with Customers at the Checkout 04:57 Module 12: Selling in Multiple Channels 12:40 42: Selling in Multiple Channels 12:40 Module 13: Taking Trends and Targeting Customers Effectively 05:38 43: Taking Trends and Targeting Customers Effectively 05:38 Assessment (Optional) 12:00 44: MCQ Question 12:00 Order Your Certificate 02:00 45: Order Your CPD Certificate 01:00 46: Order Your QLS Endorsed Certificate 01:00 Who is this course for? Data Analyst (Data Analytics) Training This course is for people who want to quickly and easily learn about Data Analyst (Data Analytics). Requirements Data Analyst (Data Analytics) Training You will not need any prior background or expertise to enrol in this Data Analyst (Data Analytics) course. Career path Data Analyst: £25,000 - £50,000 Junior Data Scientist: £30,000 - £60,000 Senior Data Analyst/Scientist: £50,000 - £100,000 Data Analytics Manager: £60,000 - £120,000 Certificates Cademy certificate of completion Digital certificate - Included Will be downloadable when all lectures have been completed Certificate of completion Digital certificate - £10 Diploma in Retail And Data Analytics at QLS Level 5 Hard copy certificate - £119 Show off Your New Skills with a Certificate of Completion After successfully completing the Diploma in Retail And Data Analytics at QLS Level 5, you can order an original hardcopy certificate of achievement endorsed by the Quality Licence Scheme. The certificate will be home-delivered, with a pricing scheme of - 119 GBP inside the UK 129 GBP (including postal fees) for International Delivery Certificate Accredited by CPDQS 29 GBP for Printed Hardcopy Certificate inside the UK 39 GBP for Printed Hardcopy Certificate outside the UK (International Delivery)

Duration 4 Days 24 CPD hours This course is intended for This is an intermediate course for experienced DBAs and technical individuals, with experience on other relational database platforms, who plan, implement, and maintain Db2 11.1 for Linux, UNIX, and Windows databases. These skills can also be utilize to support cloud based databases using Db2 on Cloud or Db2 Hosted environments. Overview Please refer to course overview This course teaches you to perform, basic and advanced, database administrative tasks using Db2 11.1. These tasks include creating and populating databases and implementing a logical design to support recovery requirements. The access strategies selected by the Db2 Optimizer will be examined using the Db2 Explain tools. Various diagnostic methods will be presented, including using various db2pd command options. Students will learn how to implement automatic archival for database logs and how to plan a redirected database restore to relocate either selected table spaces or an entire database. The REBUILD option of RESTORE, which can build a database copy with a subset of the tablespaces, will be discussed. We will also cover using the TRANSPORT option of RESTORE to copy schemas of objects between two Db2 databases. The selection of indexes to improve application performance and the use of SQL statements to track database performance and health will be covered. This course provides a quick start to Db2 database administration skills for experienced relational Database Administrators (DBA). Overview of Db2 11Command Line Processor (CLP) and GUI UsageThe Db2 EnvironmentCreating Databases and Data PlacementCreating Database ObjectsMoving DataBackup and RecoveryLocks and ConcurrencyDatabase Maintenance, Monitoring and Problem DeterminationSecurityDatabase Rebuild SupportDb2 Database and Table Space RelocationUsing Explain ToolsUsing Indexes for PerformanceAdvanced Monitoring

***24 Hour Limited Time Flash Sale*** Statistics for Data Science & Machine Learning Level 7 Advanced Diploma Admission Gifts FREE PDF & Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter Are you a professional feeling stuck in your career, struggling to keep up with the ever-changing demands of the industry? Or perhaps you're a beginner, unsure of where to start or how to break into your desired field. Whichever stage you're in, our exclusive Statistics for Data Science & Machine Learning Level 7 Advanced Diploma Bundle provides unique insights and tools that can help you achieve your goals. Designed to cater to the needs of both seasoned professionals and aspiring newcomers, our Statistics for Data Science & Machine Learning Level 7 Advanced Diploma bundle is a comprehensive program that will equip you with the essential skills and knowledge you need to succeed. Whether you're looking to advance in your current role or embark on a new career journey, this bundle has everything you need to take your professional life to the next level. But that's not all. When you enrol in Statistics for Data Science & Machine Learning Level 7 Advanced Diploma Online Training, you'll receive 20 CPD-Accredited PDF Certificates, Hard Copy Certificates, and our exclusive student ID card, all absolutely free. Courses Are Included In this Statistics for Data Science & Machine Learning Level 7 Advanced Diploma Career Bundle: Course 01: Statistics for Data Science & Machine Learning Course 02: Data Science & Machine Learning with R Training Course 03: R Programming for Data Science Course 04: Statistical Concepts in R Course 05: Learn Python, JavaScript, and Microsoft SQL for Data Science Course 06: Data Science & Machine Learning with Python Course 07: Spatial Data Visualization and Machine Learning in Python Course 08: Azure Machine Learning Course 09: Python Data Science Course 10: Python Data Science with Numpy, Pandas, and Matplotlib Course 11: Quick Data Science Approach from Scratch Course 12: Learn MySQL from Scratch for Data Science and Analytics Course 13: Hands-on Machine Learning Project - Auto Image Captioning for Social Media Course 14: Statistical Analysis Course 15: Statistics Essentials Course 16: Data Analysis In Excel Course 17: Microsoft Excel Course for Everyone - Complete the Excel Course Course 18: Introduction to Discrete Maths Course 19: Advanced Mathematics Training Course 20: Computer Simulation of Realistic Mathematical Models With Statistics for Data Science & Machine Learning Level 7 Advanced Diploma, you'll embark on an immersive learning experience that combines interactive lessons with voice-over audio, ensuring that you can learn from anywhere in the world, at your own pace. With 24/7 tutor support, you'll never feel alone in your journey, whether you're a seasoned professional or a beginner. Don't let this opportunity pass you by. Enrol in Statistics for Data Science & Machine Learning Level 7 Advanced Diploma today and take the first step towards achieving your goals and dreams. Why buy this Advanced Diploma? Free CPD Accredited Certificate upon completion of Statistics for Data Science & Machine Learning Level 7 Advanced Diploma Get a free student ID card with Statistics for this Course. Lifetime access to the course materials Get instant access to this course Learn Statistics for Data Science & Machine Learning Level 7 Advanced Diploma from anywhere in the world 24/7 tutor support with the Statistics for Data Science & Machine Learning Level 7 Advanced Diploma course. Start your learning journey straightaway with our Statistics for Data Science & Machine Learning Level 7 Advanced Diploma Training! Statistics for Data Science & Machine Learning Level 7 Advanced Diploma premium bundle consists of 20 precisely chosen courses on a wide range of topics essential for anyone looking to excel in this field. Each segment of Statistics for Data Science & Machine Learning Level 7 Advanced Diploma is meticulously designed to maximise learning and engagement, blending interactive content and audio-visual modules for a truly immersive experience. Certification You have to complete the assignment given at the end of the Statistics for Data Science & Machine Learning Level 7 Advanced Diploma course. After passing the Statistics for Data Science & Machine Learning Level 7 Advanced Diploma exam You will be entitled to claim a PDF & Hardcopy certificate accredited by CPD Quality standards completely free. CPD 200 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This course is ideal for: Students seeking mastery in this field Professionals seeking to enhance their skills Anyone who is passionate about this topic Requirements This Statistics for Data Science & Machine Learning Level 7 Advanced Diploma doesn't require prior experience and is suitable for diverse learners. Career path This Statistics for Data Science & Machine Learning Level 7 Advanced Diploma bundle will allow you to kickstart or take your career in the related sector to the next stage. Certificates CPD Accredited Digital certificate Digital certificate - Included CPD Accredited Hard copy certificate Hard copy certificate - Included If you are an international student, then you have to pay an additional 10 GBP for each certificate as an international delivery charge.

Duration 4 Days 24 CPD hours This course is intended for Students in this course are interested in designing and implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam. This course provides the knowledge and skills to design and implement DevOps processes and practices. Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms Prerequisites Successful learners will have prior knowledge and understanding of: Cloud computing concepts, including an understanding of PaaS, SaaS, and IaaS implementations. Both Azure administration and Azure development with proven expertise in at least one of these areas. Version control, Agile software development, and core software development principles. It would be helpful to have experience in an organization that delivers software. AZ-104T00 - Microsoft Azure Administrator AZ-204T00: Developing Solutions for Microsoft Azure 1 - Introduction to DevOps What is DevOps? Explore the DevOps journey Identify transformation teams Explore shared goals and define timelines 2 - Choose the right project Explore greenfield and brownfield projects Decide when to use greenfield and brownfield projects Decide when to use systems of record versus systems of engagement Identify groups to minimize initial resistance Identify project metrics and key performance indicators (KPIs) 3 - Describe team structures Explore agile development practices Explore principles of agile development Define organization structure for agile practices Explore ideal DevOps team members Enable in-team and cross-team collaboration Select tools and processes for agile practices 4 - Choose the DevOps tools What is Azure DevOps? What is GitHub? Explore an authorization and access strategy Migrate or integrate existing work management tools Migrate or integrate existing test management tools Design a license management strategy 5 - Plan Agile with GitHub Projects and Azure Boards Link GitHub to Azure Boards Configure GitHub Projects Manage work with GitHub Project boards Customize Project views Collaborate using team discussions Agile Plan and Portfolio Management with Azure Boards 6 - Introduction to source control Explore DevOps foundational practices What is source control? Explore benefits of source control Explore best practices for source control 7 - Describe types of source control systems Understand centralized source control Understand distributed source control Explore Git and Team Foundation Version Control Examine and choose Git Understand objections to using Git Describe working with Git locally 8 - Work with Azure Repos and GitHub Migrate from TFVC to Git Use GIT-TFS Develop online with GitHub Codespaces 9 - Structure your Git Repo Explore monorepo versus multiple repos Implement a change log 10 - Manage Git branches and workflows Explore branch workflow types Explore feature branch workflow Explore Git branch model for continuous delivery Explore GitHub flow Explore fork workflow Version Control with Git in Azure Repos 11 - Collaborate with pull requests in Azure Repos Collaborate with pull requests Examine GitHub mobile for pull request approvals 12 - Identify technical debt Examine code quality Examine complexity and quality metrics Measure and manage technical debt Integrate other code quality tools Plan effective code reviews 13 - Explore Git hooks Implement Git hooks 14 - Plan foster inner source Explore foster inner source Implement the fork workflow Describe inner source with forks 15 - Manage Git repositories Work with large repositories Purge repository data Manage releases with GitHub Repos Automate release notes with GitHub 16 - Explore Azure Pipelines Explore the concept of pipelines in DevOps Describe Azure Pipelines Understand Azure Pipelines key terms 17 - Manage Azure Pipeline agents and pools Choose between Microsoft-hosted versus self-hosted agents Explore job types Explore predefined agent pool Understand typical situations for agent pools Communicate with Azure Pipelines Communicate to deploy to target servers Examine other considerations Describe security of agent pools Configure agent pools and understanding pipeline styles 18 - Describe pipelines and concurrency Understand parallel jobs Estimate parallel jobs Describe Azure Pipelines and open-source projects Explore Azure Pipelines and Visual Designer Describe Azure Pipelines and YAML 19 - Explore continuous integration Learn the four pillars of continuous integration Explore benefits of continuous integration Describe build properties Enable Continuous Integration with Azure Pipelines 20 - Implement a pipeline strategy Configure agent demands Implement multi-agent builds Explore source control types supported by Azure Pipelines 21 - Integrate with Azure Pipelines Describe the anatomy of a pipeline Understand the pipeline structure Detail templates Explore YAML resources Use multiple repositories in your pipeline 22 - Introduction to GitHub Actions What are Actions? Explore Actions flow Understand workflows Describe standard workflow syntax elements Explore events Explore jobs Explore runners Examine release and test an action 23 - Learn continuous integration with GitHub Actions Describe continuous integration with actions Examine environment variables Share artifacts between jobs Examine Workflow badges Describe best practices for creating actions Mark releases with Git tags Create encrypted secrets Use secrets in a workflow Implement GitHub Actions for CI/CD 24 - Design a container build strategy Examine structure of containers Work with Docker containers Understand Dockerfile core concepts Examine multi-stage dockerfiles Examine considerations for multiple stage builds Explore Azure container-related services Deploy Docker containers to Azure App Service web apps 25 - Introduction to continuous delivery Explore traditional IT development cycle What is continuous delivery? Move to continuous delivery Understand releases and deployments Understand release process versus release 26 - Create a release pipeline Describe Azure DevOps release pipeline capabilities Explore release pipelines Explore artifact sources Choose the appropriate artifact source Examine considerations for deployment to stages Explore build and release tasks Explore custom build and release tasks Explore release jobs Configure Pipelines as Code with YAML 27 - Explore release recommendations Understand the delivery cadence and three types of triggers Explore release approvals Explore release gates Use release gates to protect quality Control Deployments using Release Gates 28 - Provision and test environments Provision and configure target environments Configure automated integration and functional test automation Understand Shift-left Set up and run availability tests Explore Azure Load Testing Set up and run functional tests 29 - Manage and modularize tasks and templates Examine task groups Explore variables in release pipelines Understand variable groups 30 - Automate inspection of health Automate inspection of health Explore events and notifications Explore service hooks Configure Azure DevOps notifications Configure GitHub notifications Explore how to measure quality of your release process Examine release notes and documentation Examine considerations for choosing release management tools Explore common release management tools 31 - Introduction to deployment patterns Explore microservices architecture Examine classical deployment patterns Understand modern deployment patterns 32 - Implement blue-green deployment and feature toggles What is blue-green deployment? Explore deployment slots Describe feature toggle maintenance 33 - Implement canary releases and dark launching Explore canary releases Examine Traffic Manager Understand dark launching 34 - Implement A/B testing and progressive exposure deployment What is A/B testing? Explore CI-CD with deployment rings 35 - Integrate with identity management systems Integrate GitHub with single sign-on (SSO) Explore service principals Explore Managed Identity 36 - Manage application configuration data Rethink application configuration data Explore separation of concerns Understand external configuration store patterns Examine Key-value pairs Examine App configuration feature management Integrate Azure Key Vault with Azure Pipelines Manage secrets, tokens and certificates Examine DevOps inner and outer loop Integrate Azure Key Vault with Azure DevOps Enable Dynamic Configuration and Feature Flags 37 - Explore infrastructure as code and configuration management Explore environment deployment Examine environment configuration Understand imperative versus declarative configuration Understand idempotent configuration 38 - Create Azure resources using Azure Resource Manager templates Why use Azure Resource Manager templates? Explore template components Manage dependencies Modularize templates Manage secrets in templates Deployments using Azure Bicep templates 39 - Create Azure resources by using Azure CLI What is Azure CLI? Work with Azure CLI 40 - Explore Azure Automation with DevOps Create automation accounts What is a runbook? Understand automation shared resources Explore runbook gallery Examine webhooks Explore source control integration Explore PowerShell workflows Create a workflow Examine checkpoint and parallel processing 41 - Implement Desired State Configuration (DSC) Understand configuration drift Explore Desired State Configuration (DSC) Explore Azure Automation State configuration (DSC) Examine DSC configuration file Explore hybrid management Implement DSC and Linux Automation on Azure 42 - Implement Bicep What is Bicep? Install Bicep Understand Bicep file structure and syntax 43 - Introduction to Secure DevOps Describe SQL injection attack Understand DevSecOps Explore Secure DevOps Pipeline Explore key validation points Explore continuous security validation Understand threat modeling 44 - Implement open-source software Explore how software is built What is open-source software Explore corporate concerns with open-source software components Explore common open-source licenses Examine license implications and ratings 45 - Software Composition Analysis Inspect and validate code bases for compliance Explore software composition analysis (SCA) Integrate Mend with Azure Pipelines Implement GitHub Dependabot alerts and security updates Integrate software composition analysis checks into pipelines Examine tools for assess package security and license rate Interpret alerts from scanner tools Implement security and compliance in an Azure Pipeline 46 - Static analyzers Explore SonarCloud Explore CodeQL in GitHub Manage technical debt with SonarCloud and Azure DevOps 47 - OWASP and Dynamic Analyzers Plan Implement OWASP Secure Coding Practices Explore OWASP ZAP penetration test Explore OWASP ZAP results and bugs 48 - Security Monitoring and Governance Implement pipeline security Explore Microsoft Defender for Cloud Examine Microsoft Defender for Cloud usage scenarios Explore Azure Policy Understand policies Explore initiatives Explore resource locks Explore Azure Blueprints Understand Microsoft Defender for Identity 49 - Explore package dependencies What is dependency management? Describe elements of a dependency management strategy Identify dependencies Understand source and package componentization Decompose your system Scan your codebase for dependencies 50 - Understand package management Explore packages Understand package feeds Explore package feed managers Explore common public package sources Explore self-hosted and SaaS based package sources Consume packages Publish packages Package management with Azure Artifacts 51 - Migrate consolidating and secure artifacts Identify existing artifact repositories Migrate and integrating artifact repositories Secure access to package feeds Examine roles Examine permissions Examine authentication 52 - Implement a versioning strategy Understand versioning of artifacts Explore semantic versioning Examine release views Promote packages Explore best practices for versioning 53 - Introduction to GitHub Packages Publish packages Install a package Delete and restore a package Explore package access control and visibility 54 - Implement tools to track usage and flow Understand the inner loop Explore Azure Monitor and Log Analytics Examine Kusto Query Language (KQL) Explore Application Insights Implement Application Insights Monitor application performance with Application Insights 55 - Develop monitor and status dashboards Explore Azure Dashboards Examine view designer in Azure Monitor Explore Azure Monitor workbooks Explore Power BI Build your own custom application 56 - Share knowledge within teams Share acquired knowledge within development teams Integrate with Azure Boards Share team knowledge using Azure Project Wiki 57 - Design processes to automate application analytics Explore rapid responses and augmented search Integrate telemetry Examine monitoring tools and technologies 58 - Manage alerts, blameless retrospectives and a just culture Examine when get a notification Explore how to fix it Explore smart detection notifications Improve performance Understand server response time degradation Reduce meaningless and non-actionable alerts Examine blameless retrospective Develop a just culture

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