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Course Overview Do you want to familiarize with various programming structure and build your career as a software engineer? Then this course is perfect for you. Learn how you can use HTML CSS my SQL GitHub XAMPP and Heroku from this Modern PHP/MYSQL/ GitHub & Heroku Tutorial course and boost your programming skill in no time. This Modern PHP/MYSQL/ GitHub & Heroku Tutorial course will teach you the function of different platforms of web development. You will learn about PHP, bootstrap, MySQL, GitHub and Heroku. The lessons will help you understand programming structures from scratch and explore different areas of web development. The activities of the course will help you to practice the knowledge you learn and enhance your skill. You'll be able to work and create sample websites with the lectures.  You'll receive certifications after completing the course. This course can be a stepping stone for you to enhance your skill and be a professional web developer. Learning Outcomes Understand how XAMPP works Familiarize with the role of PHP in web-based programs Setup Apache server and PHP environment using XAMPP server Learn how to use GitHub Be able to build data-driven and dynamic web applications Learn how to deploy web applications using Heroku Learn the basics of bootstrap 4 Who is this course for? This course is a complete package of the database, PHP, Bootstrap and GitHub. This is ideal for anyone who wants to learn software designing and its steps. The course will teach you the necessary skills and knowledge you need for software development from scratch. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path Modern PHP/MYSQL/ GitHub & Heroku Tutorial Course is a useful qualification to possess and would be beneficial for any related profession or industry such as: Web Developers Web Designers Software Developers PHP Developers App Designers Unit 01: Introduction Introduction 00:06:00 Unit 02: Environment Configuration Module 01: Setup a PHP Environment using XAMPP 00:16:00 Module 02: Install Composer Package Manager 00:03:00 Module 03: Visual Studio Code - Web Development Add ons 00:12:00 Module 04: Create a GitHub Account 00:13:00 Module 05: Create a Heroku Account 00:08:00 Unit 03: PHP Basics and Syntax Module 01: How PHP Works 00:29:00 Module 02: IFELSE Statements 00:19:00 Module 03: Switch Statements 00:09:00 Module 04: FOR Loop 00:10:00 Module 05: WHILE AND DOWHILE Loops 00:14:00 Module 06: PHP Arrays and Manipulation 00:13:00 Module 07: String Manipulation Functions 00:28:00 Module 08: Date and Time Manipulation Functions 00:15:00 Module 09: User Defined Functions 00:22:00 Module 10: PHP Include and Require 00:22:00 Module 11: PHP Website Layout - With Bootstra 00:23:00 Module 12: Add Project to Github 00:08:00 Module 13: Publish Website to Heroku 00:20:00 Unit 04: PHP Forms and MySQL and User Authentication Module 01: Project and Website Setup 00:21:00 Module 02: Create a Bootstrap 4 Form 00:28:00 Module 03: PHP Form - $_GET Action 00:23:00 Module 04: PHP Form - $_POST Action 00:11:00 Module 05: Design Database with phpMyAdmin 00:19:00 Module 06: Connect to Database using PHP PDO 00:18:00 Module 07: Save Records to Database 00:38:00 Module 08: View Database Records 00:36:00 Module 09: View One Record's Details 00:28:00 Module 10: Update Database Records 00:34:00 Module 11: Delete Database Records 00:11:00 Module 12: Final Touches: Form Validation, Error Messages, Success Messages 00:17:00 Module 13: Create Heroku App and Remote Database 00:21:00 Module 14: Setup Authentication Tables in Database 00:20:00 Module 15: Setup Login and Authentication 00:29:00 Module 16: Control User Access 00:08:00 Module 17: Sending Confirmation Emails 00:31:00 Module 18: Upload Profile Pictures 00:31:00 Module 19: Final Touches 00:14:00 Resources Resources - Modern PHP/MYSQL/ GitHub & Heroku Tutorial 00:00:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Description: The 70-246 - Monitoring and Operating a Private Cloud with System Center 2012 R2 (MCSE) course teaches you how to monitor and operate a private cloud with System Center 2012 R2. Throughout the course, you will learn the basics of the cloud, the ways of working with the business cloud, cloud services, monitoring and automating responses. The course will teach you how to handle problems in the Private Cloud, and the procedures of Service Management in the Private Cloud. You will also be introduced to cloud protection, recovery, compliance, the use of SLAs, Dashboards and Widgets. The course shows you the real-time state using Visio, system centre analytics, service level tracking, viewing SSRS and Excel to view data, PerformancePoint and configuring and deploying widgets and dashboards. Finally, you will learn cleaning up system centre databases systems. After completing the course, you will understand how Operations Manager handles monitoring, Service Manager and App Controller facilitate self-service, and Orchestrator glues everything together. Assessment: At the end of the course, you will be required to sit for an online MCQ test. Your test will be assessed automatically and immediately. You will instantly know whether you have been successful or not. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? 70-246 - Monitoring and Operating a Private Cloud with System Center 2012 R2 (MCSE) training is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our 70-246 - Monitoring and Operating a Private Cloud with System Center 2012 R2 (MCSE) course is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. System Center 2012 What is System Center 2012 FREE 00:30:00 Introducing the Cloud Discussion of Cloud Computing 00:19:00 Important Requirements 00:07:00 Working with System Center and the Infrastructure 00:05:00 Maintaining the Cloud Health 00:05:00 How Components are Integrated 00:06:00 Are You in Compliance 00:05:00 Working with the Business Cloud Examining SC 2012 VMM 00:17:00 Working with VMs with the VMM 00:11:00 Creating Clouds for Business 00:16:00 Cloud Services Looking at Service Templates and VMM Profiles 00:22:00 Web Deploy Packages 00:08:00 Server App V Introduction 00:05:00 The Data of the N Tier Application 00:05:00 What's New with VMM R2 00:07:00 Importing and Deploying the Stock trader Application 00:10:00 Installing SQL Server 00:10:00 Monitoring Overview of Operations Manager 00:20:00 Customize the Monitoring Operations 00:09:00 Monitoring Application Performance 00:14:00 Advanced Monitoring 00:04:00 Using Operations Manager for Applications 00:04:00 Using Operations Manager for the Network 00:11:00 Using Operations Manager for Distributed Applications 00:07:00 What's New in Operations Manager 2012 R2 00:09:00 Deploying an Agent 00:09:00 Configuration for Custom Monitoring 00:11:00 Configuring Basic Monitoring and Application Perfomance 00:12:00 Installing Operations Manager 00:05:00 Automating Responses Looking at Orchestrator 2012 00:08:00 Putting Orchestrator, Operations Manager, and Service Manager Together 00:15:00 What's New with Orchestrator 2012 R2 00:04:00 Managing Problems in the Private Cloud What is Problem Management 00:07:00 Using Custom Rules 00:08:00 Service Management in the Private Cloud Service Manager Introduction 00:10:00 Security Settings 00:09:00 Work Items 00:08:00 Incident Queues and Service Offerings 00:03:00 What's New with Service Manager 2012 R2 00:01:00 Configuring the Incident Template 00:10:00 Cloud Protection, Recovery, and Compliance Protecting and Recovering Data for the Private Cloud 00:29:00 Data Recovery 00:15:00 Overview of the Process Pack for IT GRC 00:14:00 Installing the Process Pack for IT GRC 00:06:00 Implementing an IT GRC Control Management Program 00:06:00 How to Maintain Compliance Through VMM Security Baselines with System Center 00:06:00 What's New with DPM 2012 R2 Advisor 00:03:00 Configuring Manual Protection 00:06:00 SLAs, Dashboards and Widgets Configuring and Deploying Widgets and Dashboards 00:12:00 Real-Time State Using Visio 00:10:00 System Center Analytics 00:12:00 Service Level Tracking 00:05:00 Viewing SSRS and Excel to View Data 00:04:00 PerformancePoint 00:04:00 Cleaning Up System Center Databases Service Manager Groom Settings 00:08:00 View and Purge Orchestrator Runbook Logs 00:08:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

There is a lot to learn in Power BI, this course takes a comprehensive look at the fundamentals of analysing data and includes a balanced look at the four main components that make up Power BI Desktop: Report view, Data view, Model view, and the Power Query Editor. It also demonstrates how to utilise the online Power BI service. It looks at authoring tools that enable you to connect to and transform data from a variety of sources, allowing you to produce detailed reports through a range of visualisations, in an interactive and dynamic way. It also includes a detailed look at formulas by writing both M functions in Power Query, and DAX functions in Desktop view. This knowledge will allow you to take your reports to the next level. The aim of this course is to provide a complete introduction to understanding the Power BI analysis process, by working hands-on with examples that will equip you with the necessary skills to start applying your learning straight away. 1 Getting Started The Power BI ecosystem Opening Power BI Desktop Power BI's four views Introduction to Dashboards 2 Importing Files Importing data sources Importing an Excel file Importing a CSV file Importing a database Connect to an SQL Server Database Import vs. Direct Query Importing from the web Importing a folder of files Managing file connections 3 Shape Data in the Query Editor The process of shaping data Managing data types Keeping and removing rows Add a custom column Appending tables together Hiding queries in reports Fixing error issues Basic maths operations 4 The Data Model Table relationships Relationship properties 5 Merge Queries Table join kinds Merging tables 6 Inserting Dashboard Visuals Things to keep in mind Inserting maps Formatting Maps Inserting charts Formatting Charts Inserting a tree map Inserting a table, matrix, and card Controlling number formats About report themes Highlighting key points Filter reports with slicers Sync slicers across dashboards Custom web visuals 7 Publish and share Reports Publishing to Power BI service Editing online reports Pinning visuals to a dashboard What is Q&A? Sharing dashboards Exporting reports to PowerPoint Exporting reports as PDF files 8 The Power Query Editor Fill data up and down Split column by delimiter Add a conditional column More custom columns Merging columns 9 The M Functions Inserting text functions Insert an IF function Create a query group 10 Pivoting Tables Pivot a table Pivot and append tables Pivot but don't aggregate Unpivot tables Append mismatched headers 11 Data Modelling Expanded Understanding relationships Mark a date table 12 DAX New Columns New columns and measures New column calculations Insert a SWITCH function 13 Introduction to DAX Measures Common measure functions Insert a SUM function Insert a COUNTROWS function Insert a DISTINCTCOUNT function Insert a DIVIDE function DAX rules 14 The CALCULATE Measure The syntax of CALCULATE Insert a CALCULATE function Control field summarisation Things of note 15 The SUMX measure X iterator functions Anatomy of SUMX Insert a SUMX function When to use X functions 16 Time Intelligence Measures Importance of a calendar table Insert a TOTALYTD function Change financial year end date Comparing historical data Insert a DATEADD function 17 Hierarchies and Groups Mine data using hierarchies Compare data in groups

This ultimate course to kickstart your Python journey from scratch. This comprehensive course covers all the essential concepts of Python, providing explanations, examples, and practical implementations. Designed with beginners in mind, our goal is to help you learn and master Python by building a variety of projects.

Duration 5 Days 30 CPD hours This course is intended for Deployment engineer Network engineer Sales engineer Overview After taking this course, you should be able to: Describe the Cisco conferencing architecture including cloud, hybrid, and on-premises conferencing Describe the physical deployment options and deployment models for Cisco Meeting Server, including Cisco Meeting Server 1000, 2000, and virtual machine Configure a Cisco Meeting Server single combined deployment for Web-Real Time Communications (WebRTC) endpoints within the enterprise Use APIs and the Cisco Meeting Server API Guide to configure profiles using Postman and the Webadmin API tool Configure a scalable and resilient deployment of Cisco Meeting Server with three servers for WebRTC endpoints within the enterprise Configure a scalable and resilient deployment of Cisco Meeting Server to support standard Session Initiation Protocol (SIP) and WebRTC connectivity outside the enterprise Configure a scalable and resilient deployment of Cisco Meeting Server to support recording and streaming of conferences Configure Cisco Unified Communications Manager and Cisco Meeting Server to support Rendezvous, Scheduled, and Ad-hoc conferencing for Cisco Unified CM registered endpoints Configure Cisco Meeting Server to integrate with a preconfigured on-premise Microsoft Skype for Business installation Install Cisco TelePresence Management Suite (Cisco TMS) and Cisco TelePresence Management Suite for Microsoft Exchange (Cisco TMSXE) on a single Microsoft Windows 2012 server and connect to an existing SQL environment Install and integrate Cisco Meeting Management with Cisco TMS and Cisco Meeting Server Set up and manage a scheduled conference with Cisco TMS and Cisco Meeting Management Capture and analyze logs from Cisco Meeting Server and Cisco Meeting Manager to diagnose faults, including a SIP connection error The Implementing Cisco Collaboration Conferencing (CLCNF) v1.0 course focuses on Cisco© on-premises conferencing architecture and solutions. You will gain knowledge and skills to design and implement common conferencing deployment scenarios of Cisco Meeting Server, its integration with call control features such as Cisco Unified Communications Manager and Cisco Expressway, and other Cisco collaboration conferencing devices.This course offers lessons and hands-on labs to prepare you for the 300-825 Implementing Cisco Collaboration Conferencing (CLCNF) exam. Course outline Describing Cisco Conferencing Architecture Configuring a Single Combined Deployment Installing Cisco Meeting Server Using APIs with Cisco Meeting Server Configuring a Cisco Meeting Server Scalable and Resilient Deployment Configuring Business to Business (B2B) and WebRTC Firewall Traversal Connectivity for Cisco Meeting Server Configuring Recording and Streaming with Cisco Meeting Server Troubleshooting Cisco Meeting Server Integrating Cisco Meeting Server with Cisco Unified CM Integrating Cisco Meeting Server with Microsoft Skype for Business Installing and Operating Cisco TMS and Cisco TMSXE Installing and Integrating Cisco Meeting Management Additional course details: Nexus Humans Cisco Implementing Cisco Collaboration Conferencing v2.0 (CLCNF) 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 Conferencing v2.0 (CLCNF) 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 4 Days 24 CPD hours This course is intended for The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview Overview of data science and machine learning at scale Overview of the Hadoop ecosystem Working with HDFS data and Hive tables using Hue Introduction to Cloudera Data Science Workbench Overview of Apache Spark 2 Reading and writing data Inspecting data quality Cleansing and transforming data Summarizing and grouping data Combining, splitting, and reshaping data Exploring data Configuring, monitoring, and troubleshooting Spark applications Overview of machine learning in Spark MLlib Extracting, transforming, and selecting features Building and evaluating regression models Building and evaluating classification models Building and evaluating clustering models Cross-validating models and tuning hyperparameters Building machine learning pipelines Deploying machine learning models Spark, Spark SQL, and Spark MLlib PySpark and sparklyr Cloudera Data Science Workbench (CDSW) Hue This workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges. Using scenarios and datasets from a fictional technology company, students discover insights to support critical business decisions and develop data products to transform the business. The material is presented through a sequence of brief lectures, interactive demonstrations, extensive hands-on exercises, and discussions. The Apache Spark demonstrations and exercises are conducted in Python (with PySpark) and R (with sparklyr) using the Cloudera Data Science Workbench (CDSW) environment. The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview of data science and machine learning at scaleOverview of the Hadoop ecosystemWorking with HDFS data and Hive tables using HueIntroduction to Cloudera Data Science WorkbenchOverview of Apache Spark 2Reading and writing dataInspecting data qualityCleansing and transforming dataSummarizing and grouping dataCombining, splitting, and reshaping dataExploring dataConfiguring, monitoring, and troubleshooting Spark applicationsOverview of machine learning in Spark MLlibExtracting, transforming, and selecting featuresBuilding and evauating regression modelsBuilding and evaluating classification modelsBuilding and evaluating clustering modelsCross-validating models and tuning hyperparametersBuilding machine learning pipelinesDeploying machine learning models Additional course details: Nexus Humans Cloudera Data Scientist Training 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 Cloudera Data Scientist Training 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 class is intended for the following participants: Cloud architects, administrators, and SysOps/DevOps personnel Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform. Overview This course teaches participants the following skills: Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Platform Understand how pod networking works in Kubernetes Engine Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/ kubectl commands Launch, roll back and expose jobs in Kubernetes Manage access control using Kubernetes RBAC and Google Cloud IAM Managing pod security policies and network policies Using Secrets and ConfigMaps to isolate security credentials and configuration artifacts Understand GCP choices for managed storage services Monitor applications running in Kubernetes Engine This class introduces participants to deploying and managing containerized applications on Google Kubernetes Engine (GKE) and the other services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as pods, containers, deployments, and services; as well as networks and application services. This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring. Introduction to Google Cloud Platform Use the Google Cloud Platform Console Use Cloud Shell Define cloud computing Identify GCPs compute services Understand regions and zones Understand the cloud resource hierarchy Administer your GCP resources Containers and Kubernetes in GCP Create a container using Cloud Build Store a container in Container Registry Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE) Understand how to choose among GCP compute platforms Kubernetes Architecture Understand the architecture of Kubernetes: pods, namespaces Understand the control-plane components of Kubernetes Create container images using Google Cloud Build Store container images in Google Container Registry Create a Kubernetes Engine cluster Kubernetes Operations Work with the kubectl command Inspect the cluster and Pods View a Pods console output Sign in to a Pod interactively Deployments, Jobs, and Scaling Create and use Deployments Create and run Jobs and CronJobs Scale clusters manually and automatically Configure Node and Pod affinity Get software into your cluster with Helm charts and Kubernetes Marketplace GKE Networking Create Services to expose applications that are running within Pods Use load balancers to expose Services to external clients Create Ingress resources for HTTP(S) load balancing Leverage container-native load balancing to improve Pod load balancing Define Kubernetes network policies to allow and block traffic to pods Persistent Data and Storage Use Secrets to isolate security credentials Use ConfigMaps to isolate configuration artifacts Push out and roll back updates to Secrets and ConfigMaps Configure Persistent Storage Volumes for Kubernetes Pods Use StatefulSets to ensure that claims on persistent storage volumes persist across restarts Access Control and Security in Kubernetes and Kubernetes Engine Understand Kubernetes authentication and authorization Define Kubernetes RBAC roles and role bindings for accessing resources in namespaces Define Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources Define Kubernetes pod security policies Understand the structure of GCP IAM Define IAM roles and policies for Kubernetes Engine cluster administration Logging and Monitoring Use Stackdriver to monitor and manage availability and performance Locate and inspect Kubernetes logs Create probes for wellness checks on live applications Using GCP Managed Storage Services from Kubernetes Applications Understand pros and cons for using a managed storage service versus self-managed containerized storage Enable applications running in GKE to access GCP storage services Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and Bigquery from within a Kubernetes application

A course that focuses on using Kotlin for server-side development using the Spring Boot framework. This hands-on course will help you get familiar with the basics of the Kotlin programming language as well as the entire process of building RESTful APIs using Kotlin Spring Boot.

Basic Python syntax and principles of Object Orientated Programming. Most attendees are in-work IT Professional. Private individuals are also very welcome. Evening courses also running. Our Style: Hands-on, Practical Location: Online, Instructor-led Download: anaconda.com Duration: 6 weeks, 1 evening per week, 6pm - 8pm Times: arrange a time for your time zone

Duration 3 Days 18 CPD hours This course is intended for Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Overview This course teaches participants the following skills: Use best practices for application development. Choose the appropriate data storage option for application data. Implement federated identity management. Develop loosely coupled application components or microservices. Integrate application components and data sources. Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment. Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Best Practices for Application Development Code and environment management. Design and development of secure, scalable, reliable, loosely coupled application components and microservices. Continuous integration and delivery. Re-architecting applications for the cloud. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK. Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials. Overview of Data Storage Options Overview of options to store application data. Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner. Best Practices for Using Cloud Firestore Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling. Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow. Lab: Store application data in Cloud Datastore. Performing Operations on Cloud Storage Operations that can be performed on buckets and objects. Consistency model. Error handling. Best Practices for Using Cloud Storage Naming buckets for static websites and other uses. Naming objects (from an access distribution perspective). Performance considerations. Setting up and debugging a CORS configuration on a bucket. Lab: Store files in Cloud Storage. Handling Authentication and Authorization Cloud Identity and Access Management (IAM) roles and service accounts. User authentication by using Firebase Authentication. User authentication and authorization by using Cloud Identity-Aware Proxy. Lab: Authenticate users by using Firebase Authentication. Using Pub/Sub to Integrate Components of Your Application Topics, publishers, and subscribers. Pull and push subscriptions. Use cases for Cloud Pub/Sub. Lab: Develop a backend service to process messages in a message queue. Adding Intelligence to Your Application Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API. Using Cloud Functions for Event-Driven Processing Key concepts such as triggers, background functions, HTTP functions. Use cases. Developing and deploying functions. Logging, error reporting, and monitoring. Managing APIs with Cloud Endpoints Open API deployment configuration. Lab: Deploy an API for your application. Deploying Applications Creating and storing container images. Repeatable deployments with deployment configuration and templates. Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments. Execution Environments for Your Application Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run. Lab: Deploying your application on App Engine flexible environment. Debugging, Monitoring, and Tuning Performance Application Performance Management Tools. Stackdriver Debugger. Stackdriver Error Reporting. Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting. Stackdriver Logging. Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.