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Learn everything you need to know to be fully competent with Window OS. This syllabus takes you around the basics and then on another deep dive into all the elements. Discover things you never knew and speed up your experience using Windows OS. Module 1: Introduction to Windows OS • Understanding the Windows operating system • Navigating the Windows interface • Customizing system settings and preferences Module 2: File Management • Managing files and folders in Windows Explorer • Copying, moving, and renaming files • Using the Recycle Bin and data recovery Module 3: Windows Built-in Apps • Using Microsoft Edge for web browsing • Effective web searching using search engines • Email management with Windows Mail • Calendar and task management with Windows Calendar Module 4: Software Installation and Updates • Installing and updating software applications • Managing and uninstalling programs • Windows Store and app installations Module 5: Microsoft Office Basics • Introduction to Microsoft Office suite • Using Microsoft Word for document creation • Basic spreadsheet management with Microsoft Excel Module 6: Microsoft Office Intermediate Skills • Advanced features in Microsoft Word • Creating and formatting spreadsheets in Microsoft Excel • Creating dynamic presentations with PowerPoint Module 7: Multimedia and Graphics • Basic image editing with Paint • Using Windows Photo app for photo management • Creating graphics with Paint 3D Module 8: Productivity and Collaboration • Using OneDrive for cloud-based storage and collaboration • Working with Windows Sticky Notes and To-Do • Collaborative editing with Microsoft Office Online Module 9: Troubleshooting and Maintenance • Identifying and resolving common Windows issues • Using Task Manager for performance monitoring • Maintenance tasks for Windows OS Module 10: Windows Security and Privacy • Overview of Windows security features • Online safety and privacy best practices • Protecting personal data and devices Module 11: Advanced Windows Features • Customizing the Windows Start Menu and Taskbar • Using Cortana for voice commands and search • Virtual desktops and advanced multitasking Module 12: Using AI and Chat GPT • Introduction to AI and Chat GPT technology • Exploring AI-powered features in Windows • Using Chat GPT for productivity and assistance Module 13: Browsing and Search Engines • Effective use of web browsers • Utilizing search engines for research • Online safety and privacy while browsing Module 14: Cybersecurity • Understanding cybersecurity threats • Protecting against malware and phishing attacks • Secure online practices and password management Module 15: Software Installation and Factory Reset • Installing and updating software applications • Factory resetting a Windows device • Data backup and recovery during resets Module 16: Final Projects and Assessment • Culminating projects showcasing Windows OS skills • Practical exams assessing Windows software knowledge and skills • Preparing for industry-recognized certifications (optional) Please note that the duration and depth of each module can vary depending on the level of expertise required and the specific needs of the learners. Additionally, it's important to adapt the curriculum to the learners' proficiency levels, whether they are A Level/GCSE students or adult learners with different experience levels.

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

Duration 5 Days 30 CPD hours This course is intended for This intermediate course is designed for experienced Integration Specialists and Senior-Level Developers with experience in application development, messaging middleware applications, and transport protocols such as HTTP and FTP. Overview Describe the features and uses of the IBM Integration BusDevelop, deploy, and test message flow applicationsGenerate message flow applications from predefined patternsUse IBM Integration Bus problem determination aids to diagnose and solve development and runtime errorsDescribe the function and appropriate use of IBM Integration Bus processing nodesWrite basic Extended Structured Query Language and Java programs to transform dataUse the IBM Graphical Data Mapping editor to transform dataDefine, use, and test simple XML and Data Format Description Language (DFDL) data modelsDescribe supported transport protocols and how to call them in message flows This course teaches you how to use IBM Integration Bus to develop, deploy, and support message flow applications. Students will learn how to construct applications to transport and transform data. Course Outline Course introduction Introduction to IBM Integration Bus Application development fundamentals Exercise: Importing and testing a message flow Creating message flow applications Exercise: Creating a message flow application Connecting to IBM MQ Exercise: Connecting to IBM MQ Controlling the flow of messages Exercise: Adding flow control to a message flow application Modeling the data Exercise: Creating a DFDL model Processing file data Exercise: Processing file data Using problem determination tools and help resources Exercise: Using problem determination tools Exercise: Implementing explicit error handling Mapping messages with the Graphical Data Mapping editor Referencing a database in a message flow application Exercise: Referencing a database in a map Using Compute nodes to transform messages Exercise: Transforming data by using the Compute and JavaCompute nodes Processing JMS, HTTP, and web service messages Preparing for production Exercise: Creating a runtime-aware message flow Course summary Additional course details: Nexus Humans WM666 IBM Integration Bus V10 Application Development I 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 WM666 IBM Integration Bus V10 Application Development I 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.

Ready to stop sending your resume into the void? It’s time to master a fundamental life skill for every ambitious administrative professional: crafting a resume that doesn’t just list your entire work history, but actually it gets you interviews. Join us for an intensive workshop where we reveal the industry secrets behind the art and science of standout resumes.

Duration 48.125 Days 288.75 CPD hours Cisco Learning Library: Collaboration provides on-demand training to help your IT staff design, implement, manage, and troubleshoot your organization?s collaboration and video infrastructure based on Cisco collaboration and unified communications solutions.This comprehensive technical training library includes full-length interactive certification courses, product and technology courses with labs, and thousands of reference materials. Collaboration Library Certification Courses CCNP Collaboration Implementing Cisco Collaboration Core Technologies (CLCOR) v1.0 Implementing Cisco Collaboration Applications (CLICA) v1.0 Implementing Cisco Advanced Call Control and Mobility Services (CLACCM) v1.0 Implementing Cisco Collaboration Cloud and Edge Solutions (CLCEI) v1.0 Implementing Automation for Cisco Collaboration Solutions (CLAUI) v1.0 CCIE Collaboration Implementing Cisco Collaboration Core Technologies (CLCOR) v1.0 Product and technology training Cisco Video Infrastructure Design (VID) v1.0 Developing Applications for Cisco Webex and Webex Devices (DEVWBX) v1.0 Implementing Automation for Cisco Collaboration Solutions (CLAUI) v1.0 Implementing Cisco Advanced Call Control and Mobility Services (CLACCM) v1.0 Implementing Cisco Collaboration Applications (CLICA) v1.0 Implementing Cisco Collaboration Cloud and Edge Solutions (CLCEI) v1.0 Implementing Cisco Collaboration Core Technologies (CLCOR) v1.0 Understanding Cisco Collaboration Foundations (CLFNDU) v1.0

Duration 2 Days 12 CPD hours This course is intended for This in an introductory-level class for intermediate skilled team members. Students should have prior software development experience or exposure, have some basic familiarity with containers, and should also be able to navigate the command line. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment led by our expert facilitator, students will explore: What a Kubernetes cluster is, and how to deploy and manage them on-premises and in the cloud. How Kubernetes fits into the cloud-native ecosystem, and how it interfaces with other important technologies such as Docker. The major Kubernetes components that let us deploy and manage applications in a modern cloud-native fashion. How to define and manage applications with declarative manifest files that should be version-controlled and treated like code. Containerization has taken the IT world by storm in the last few years. Large software houses, starting from Google and Amazon, are running significant portions of their production load in containers. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. This is a hands-on workshop style course that teaches core features and functionality of Kubernetes. You will leave this course knowing how to build a Kubernetes cluster, and how to deploy and manage applications on that cluster. Getting Started Our sample application Kubernetes concepts Declarative vs imperative Kubernetes network model First contact with kubectl Setting up Kubernetes Working with Containers Running our first containers on Kubernetes Exposing containers Shipping images with a registry Running our application on Kubernetes Exploring the Kubernetes Dashboard The Kubernetes dashboard Security implications of kubectl apply Scaling a deployment Daemon sets Labels and selectors Rolling updates Next Steps Accessing logs from the CLI Managing stacks with Helm Namespaces Next steps

Training duration: 10 hrs. Click here for more info Method: 1-2-1, Personalized attention, Tailored content, Flexible pace, Individual support. Schedule: Personalized training experience with our flexible 1-2-1 sessions. Tailor your own schedule by pre-booking a convenient hour of your choice, available from Monday to Saturday between 9 am and 7 pm. Discover the world of 3D computer graphics and animation with our Autodesk Maya Basic to Fundamentals Training Course. Whether you're a beginner or aspiring artist, this comprehensive program equips you with essential skills in modeling, animation, and rendering. Benefit from interactive learning, experienced instructors, and the option to choose in-person or live online sessions. Enroll now to gain industry-standard knowledge and unleash your creativity in the field of animation and visual effects. Maya Basic to Intermediate Course Course Duration: 10 hours Course Outline: I. Introduction to Maya (1 hour) - Gain an insightful overview of Maya and its diverse applications - Familiarize yourself with the Maya interface and essential tools - Master navigation and viewport controls with ease - Learn the art of creating and managing projects proficiently II. Creating 3D Models (2 hours) - Lay a strong foundation in polygon modeling basics - Craft and shape basic objects and shapes adeptly - Refine and modify objects with precision and creativity - Unlock the art of constructing complex objects using extrusions and bevels III. Texturing and Materials (1 hour) - Venture into the realm of texturing and its significance - Create and skillfully apply materials to enhance visual appeal - Master the art of texture mapping and UV unwrapping techniques - Seamlessly import and incorporate textures and images into your projects IV. Lighting and Rendering (1.5 hours) - Illuminate your creations with fundamental lighting techniques - Set up cameras and compose visually captivating scenes - Master the art of rendering still images and dynamic animations - Explore diverse output options and file formats for professional results V. Animation (2.5 hours) - Embark on an enthralling journey into the world of animation - Effectively utilize keyframe animation and animation curves - Create and edit animation clips for seamless and captivating motion - Dive into the intricacies of rigging and animating a simple character VI. Special Effects (1 hour) - Unleash the potential of particle systems and dynamics - Create and manipulate mesmerizing fluid and fire effects - Craft and refine awe-inspiring special effects such as explosions and smoke VII. Intermediate Modeling Techniques (1 hour) - Elevate your skills with NURBS modeling essentials - Create and modify curves and surfaces with finesse - Dive into the world of crafting organic shapes using NURBS techniques - Employ sculpting tools to create high-resolution and detailed models VIII. Conclusion and Next Steps (0.5 hours) - Recap the wealth of knowledge from the course content - Discover valuable tips and resources for further learning and growth - Engage in a dynamic Q&A session and provide valuable feedback

Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.

Duration 4 Days 24 CPD hours This course is intended for This course is for IT Professionals with expertise in designing and implementing solutions running on Microsoft Azure. They should have broad knowledge of IT operations, including networking, virtualization, identity, security, business continuity, disaster recovery, data platform, budgeting, and governance. Azure Solution Architects use the Azure Portal and as they become more adept they use the Command Line Interface. Candidates must have expert-level skills in Azure administration and have experience with Azure development processes and DevOps processes. Overview Recommend solutions to minimize costs Recommend a solution for Conditional Access, including multi-factor authentication Recommend a solution for a hybrid identity including Azure AD Connect and Azure AD Connect Recommend a solution for using Azure Policy Recommend a solution that includes KeyVault Recommend a solution that includes Azure AD Managed Identities Recommend a storage access solution Design an Azure Site Recovery solution Recommend a solution for autoscaling Recommend a solution for containers Recommend a solution for network security Recommend a solution for migrating applications and VMs Recommend a solution for migration of databases This course teaches Solutions Architects how to translate business requirements into secure, scalable, and reliable solutions. Lessons include design considerations related to logging, cost analysis, authentication and authorization, governance, security, storage, high availability, and migration. This role requires decisions in multiple areas that affect an overall design solution. Design a Compute Solution Recommend a Solution for Compute Provisioning Determine Appropriate Compute Technologies Recommend a Solution for Containers Recommend a Solution for Automating Compute Management Design a Network Solution Recommend a Solution for Network Addressing and Name Resolution Recommend a Solution for Network Provisioning Recommend a Solution for Network Security Recommend a Solution for iInternete Connectivity and On-Premises Networks Recommend a Solution for Automating Network Management Recommend a Solution for Load Balancing and Rraffic Routing Design for Migration Assess and On-Premises Servers and Applications for Migration Recommend a Solution for Migrating Applications and VMs Recommend a Solution for Migration of Databases Design Authentication and Authorization Tips for Identity and Access Management Recommend a Solution for Multi-Factor Authentication Five Steps for Securing Identity Infrastructure Recommend a Solution for Single-Sign On (SSO) Recommend a Solution for a Hybrid Identity Recommend a Solution for B2B Integration Recommend a Hierarchical Structure for Management Groups Design Governance Recommend a Solution for using Azure Policy Recommend a Solution for using Azure Blueprint Design a Solution for Databases Select an Appropriate Data Platform Based on Requirements Overview of Azure Data Storage Recommend Database Service Tier Sizing Dynamically Scale Azure SQL Database and Azure SQL Managed Instances Recommend a Solution for Encrypting Data at Rest, Transmission, and In Use Select an Appropriate Storage Account Understanding Storage Tiers Recommend a Storage Access Solution Recommend Storage Management Tools Design Data Integration Recommend a Data Flow Recommend a Solution for Data Integration Design a Solution for Logging and Monitoring Azure Monitoring Services Azure Monitor Design a Solution for Backup and Recovery Recommend a Recovery Solution for Hybrid and On-Premises Workloads Design and Azure Site Recovery Solution Recommend a Solution for Recovery in Different Regions Recommend a Solution for Azure Backup Management Design a Solution for Data Archiving and Retention Design for High Availability Recommend a Solution for Application and Workload Redundancy Recommend a Solution for Autoscaling Identify Resources that Require High Availability Identify Storage Tpes for High Availability Recommend a Solution for Geo-Redundancy of Workloads Design for Cost Optimization Recommend Solutions for Cost Management Recommended Viewpoints for Minimizing Costs Design an Application Architecture Recommend a Microservices Architecture Recommend an Orchestration Solution for Deployment of Applications Recommend a Solution for API Integration Design Security for Applications Security for Applications and Services Recommend a Solution using Key Vault Recommend Solutions using Azure AD Managed Identities

Duration 1 Days 6 CPD hours This course is intended for Individuals planning to deploy applications and create application environments on Google Cloud. Developers, systems operations professionals, and solution architects getting started with Google Cloud. Executives and business decision makers evaluating the potential of Google Cloud to address their business needs. Overview Identify the purpose and value of Google Cloud products and services. Interact with Google Cloud services. Describe ways in which customers have used Google Cloud. Choose among and use application deployment environments on Google Cloud: App Engine, Google Kubernetes Engine, and Compute Engine. Choose among and use Google Cloud storage options: Cloud Storage, Cloud SQL, Cloud Bigtable, and Firestore. Make basic use of BigQuery, Google's managed data warehouse for analytics. This course uses lectures, demos, and hands-on labs to give you an overview of Google Cloud products and services so that you can learn the value of Google Cloud and how to incorporate cloud-based solutions into your business strategies. Introducing Google Cloud Platform Explain the advantages of Google Cloud Platform. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Platform Identify the purpose of projects on Google Cloud Platform. Understand the purpose of and use cases for Identity and Access Management. List the methods of interacting with Google Cloud Platform. Lab: Getting Started with Google Cloud Platform. Google Compute Engine and Networking Identify the purpose of and use cases for Google Compute Engine. Understand the basics of networking in Google Cloud Platform. Lab: Deploying Applications Using Google Compute Engine. Google Cloud Platform Storage Options Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, and Google Cloud Bigtable. Learn how to choose between the various storage options on Google Cloud Platform. Lab: Integrating Applications with Google Cloud Storage. Google Container Engine Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Introduction to Hybrid and Multi-Cloud computing (Anthos). Lab: Deploying Applications Using Google Container Engine. Google App Engine and Google Cloud Datastore Understand the purpose of and use cases for Google App Engine and Google Cloud Datastore. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand the purpose of and use cases for Google Cloud Endpoints. Lab: Deploying Applications Using App Engine and Cloud Datastore. Deployment and Monitoring Understand the purpose of template-based creation and management of resources. Understand the purpose of integrated monitoring, alerting, and debugging. Lab: Getting Started with Stackdriver and Deployment Manager. Big Data and Machine Learning Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Lab: Getting Started with BigQuery. Summary and Review Summary and Review. What's Next?.