18729 Courses

Duration 4 Days 24 CPD hours This course is intended for Students in this course are interested in implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam. Overview After completing this course, students will be able to: Plan for the transformation with shared goals and timelines Select a project and identify project metrics and Key Performance Indicators (KPI's) Create a team and agile organizational structure Design a tool integration strategy Design a license management strategy (e.g., Azure DevOps and GitHub users) Design a strategy for end-to-end traceability from work items to working software Design an authentication and access strategy Design a strategy for integrating on-premises and cloud resources Describe the benefits of using Source Control Describe Azure Repos and GitHub Migrate from TFVC to Git Manage code quality including technical debt SonarCloud, and other tooling solutions Build organizational knowledge on code quality Explain how to structure Git repos Describe Git branching workflows Leverage pull requests for collaboration and code reviews Leverage Git hooks for automation Use Git to foster inner source across the organization Explain the role of Azure Pipelines and its components Configure Agents for use in Azure Pipelines Explain why continuous integration matters Implement continuous integration using Azure Pipelines Define Site Reliability Engineering Design processes to measure end-user satisfaction and analyze user feedback Design processes to automate application analytics Manage alerts and reduce meaningless and non-actionable alerts Carry out blameless retrospectives and create a just culture Define an infrastructure and configuration strategy and appropriate toolset for a release pipeline and application infrastructure Implement compliance and security in your application infrastructure Describe the potential challenges with integrating open-source software Inspect open-source software packages for security and license compliance Manage organizational security and compliance policies Integrate license and vulnerability scans into build and deployment pipelines Configure build pipelines to access package security and license ratings 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. Module 1: Get started on a DevOps transformation journey Introduction to DevOps Choose the right project Describe team structures Choose the DevOps tools Plan Agile with GitHub Projects and Azure Boards Introduction to source control Describe types of source control systems Work with Azure Repos and GitHub Module 2: Development for enterprise DevOps Structure your Git Repo Manage Git branches and workflows Collaborate with pull requests in Azure Repos Explore Git hooks Plan foster inner source Manage Git repositories Identify technical debt Module 3: Implement CI with Azure Pipelines and GitHub Actions Explore Azure Pipelines Manage Azure Pipeline agents and pools Describe pipelines and concurrency Explore Continuous integration Implement a pipeline strategy Integrate with Azure Pipelines Introduction to GitHub Actions Learn continuous integration with GitHub Actions Design a container build strategy Module 4: Design and implement a release strategy Introduction to continuous delivery Explore release strategy recommendations Build a high-quality release pipeline Introduction to deployment patterns Implement blue-green deployment and feature toggles Implement canary releases and dark launching Implement A/B testing and progressive exposure deployment Module 5: Implement a secure continuous deployment using Azure Pipelines Create a release pipeline Provision and test environments Manage and modularize tasks and templates Automate inspection of health Manage application configuration data Integrate with identity management systems Implement application configuration Module 6: Manage infrastructure as code using Azure and DSC Explore infrastructure as code and configuration management Create Azure resources using Azure Resource Manager templates Create Azure resources by using Azure CLI Explore Azure Automation with DevOps Implement Desired State Configuration (DSC) Implement Bicep Module 7: Implement security and validate code bases for compliance Introduction to Secure DevOps Implement open-source software Software Composition Analysis Static analyzers OWASP and Dynamic Analyzers Security Monitoring and Governance Module 8: Design and implement a dependency management strategy Explore package dependencies Understand package management Migrate, consolidate, and secure artifacts Implement a versioning strategy Introduction to GitHub Packages Module 9: Implement continuous feedback Implement tools to track usage and flow Develop monitor and status dashboards Share knowledge within teams Design processes to automate application analytics Manage alerts, Blameless retrospectives and a just culture Additional course details: Nexus Humans AZ-400 Designing and Implementing Microsoft DevOps Solutions 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 AZ-400 Designing and Implementing Microsoft DevOps Solutions 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 2 Days 12 CPD hours This course is intended for This course is intended for Sales Representatives (SR), Sales Managers and End-users who have an interest in the Sales components of Dynamics 365. Students should have an existing working knowledge of either Microsoft Dynamics 365 or Microsoft Dynamics CRM. As a minimum, students should attend the prerequisite course Introduction to Microsoft Dynamics 365 Overview Understand the features and tools that exist in Microsoft Dynamics 365 for SR?s and Sales Managers. Be familiar with the stages of the Sales Order. Process in Microsoft Dynamics 365. Understand the fundamentals of Lead and Opportunity Management. Be able to track, manage, qualify Leads and convert to Opportunities and related customer records in Microsoft Dynamics 365. Know how to disqualify and cancel Leads, and convert Activity records to Leads and Opportunities. Understand how to collaborate on Opportunities with other SR?s and close Opportunity records as Won and Lost. Be able to track Competitors and Stakeholders. Understand how to view Resolution Activities. Add Products and Write-In Products to Opportunities. Build and maintain a repository of Products, Product Bundles and Product Families in the Product Catalog. Configure Unit Groups, Price Lists and Discount Lists. Work with Product Properties and view a Product Hierarchy. Create Quotes and add Products. Work with the Sales Order Process to convert Quotes to Orders and Invoices. Fulfill Orders and manage Invoice payments. Explore the Sales Reports and create a custom Sales Report using the Reporting Wizard in Microsoft Dynamics 365. Understand the significance of Sales Goal Management and Metrics in Microsoft Dynamics 365. Explore the Sales Charts and Dashboards and create a custom Sales Dashboard in Microsoft Dynamics 365. This course provides students with a detailed hands-on experience of the Salesfeatures and components of Microsoft Dynamics 365. Introduction Sales Order Process Scenarios An Introduction to Sales in Dynamics 365 The Dynamics 365 Platform Dynamics 365 Sales Fundamentals Security Considerations Where to get Help Further Reading and Resources Lead Management The Lead Management Process Working with Lead Records Working with the Lead Form Lead Assignment Leads and Activities Qualifying a Lead Disqualifying a Lead Opportunities Management Introduction to Opportunities The Opportunity Views The Opportunity Form Opportunity Sales Process Closing an Opportunity Resolution Activities Products Introduction to the Product Catalog Adding Products Configuring Unit Groups Price Lists and Price List Items Quotes, Orders and Invoices Introduction to Order Processing Adding Products to an Opportunity Working with Quotes Working with Orders Working with Invoices Sales Analysis Introduction to Sales Analysis in Dynamics 365 The Sales Reports The Reporting Wizard Working with Sales Charts Working with Sales Dashboards Working with Sales Goals and Metrics

Duration 2 Days 12 CPD hours This course is intended for This course is intended for software testers, architects, engineers, or other related roles, who wish to apply AI to software testing practices within their enterprise. While there are no specific pre-requisites for this course, it would be helpful is the attendee has familiarity with basic scripting (Python preferred) and be comfortable with working from the command line (for courses that add the optional hands-on labs). Attendees without basic scripting skills can follow along with the hands-on labs or demos. Overview This course introduces AI and related technologies from a practical applied software testing perspective. Through engaging lecture and demonstrations presented by our expert facilitator, students will explore: Exploring AI Introduction to Machine Learning Introduction to Deep Learning Introduction to Data Science Artificial Intelligence (AI) in Software Testing Implementing AI in Test Automation Innovative AI Test Automation Tools for the Future Implementing AI in Software Testing / AI in Test Automation is an introductory-level course for attendees new to AI, Machine Learning or Deep Learning who wish to automate software testing tasks leveraging AI. The course explores the essentials of AI, ML and DL and how the integrate into IT business operations and initiatives. Then the course moves to specifics about the skills, techniques and tools used to apply AI to common software testing requirements. Exploring AI AI-Initiatives The Priority: Excellence AI- Intelligence Types The Machine Learning Types The Quality Learning Initiative The Inception in Academics AI - Importance & Applications The Re-visit Learning Re-visited via AI Teaching in the world of AI Exploring AI for Self-Development AI In Academics Beyond Academics Introduction to Machine Learning What is Machine Learning? Why Machine Learning? Examples - Algorithms behind Machine Learning Introduction to Deep Learning What is Deep Learning? Why Deep Learning? Example - Deep Learning Vs Machine Learning Introduction to Data Science What is Data Science? Why Data Science? Examples - Use Cases of Data Science Artificial Intelligence (AI) in Software Testing What is AI in Software Testing? The Role of AI Testing Why do we Need AI in Software Testing? Pros and Cons of AI in Software Testing Applications of AI in Software Testing Is it time for Testers or QA Teams to worry about AI? Automated Testing with Artificial Intelligence Implementing AI in Test Automation Training the AI Bots Challenges with AI-powered Applications Examples - Real World use cases using Artificial Intelligence Demo - Facial Emotion Detection Using Artificial Intelligence Demo - Text Analysis API Using Artificial Intelligence Demo - EYE SPY Mobile App Using Artificial Intelligence Innovative AI Test Automation Tools for the Future Tools used for Implementing AI in Automation Testing What is NEXT? AI Test Automation Demo using Testim

Duration 1 Days 6 CPD hours This course is intended for This course is intended for both novice and experienced IT professionals, Network Administrators new to Active Directory, Help Desk Personnel, Network Support Personal, Desktop Support Personal, Managers that oversee IT personnel, Developers that create products that interact with Active Directory and Exchange Administrators. Overview At Course Completion you will Understand the industry standards used in Active Directory and their importance. Recognize the functionality of Domain Controllers and Active Directory Replication mechanisms. Understand Forest, Domain and OU structure. Recognize and understand the role of Active Directory Sites. Skills needed to determine Domain Controller Server versions, Forest and Domain Functional levels. Describe authentication Mechanisms in Active Directory NTLM and Kerberos. Optimize and maintain Group Policy Objects (GPO) used in Active Directory. Understand the functioning of Active Directory Partitions and the Global Catalog. Fundamental understanding of using Active Directory with Cloud Services like Federation Services and Azure. This one-day instructor-led class is intended for IT professionals and IT managers who work with Active Directory or supervise IT professionals that work with Active Directory. Additionally, IT professionals that work with products that integrate with Active Directory such as Exchange can also benefit. In this course, students learn how and why Active Directory was developed by Microsoft, the fundamental architecture, basic design, management, as well as security and fundamentals for cloud integration with services like Azure. Module 1: Principles of Active Directory Development of Active Directory What is X.500 LDAP Active Directory Architecture NTLM and Kerberos Managing operating systems with GPOs, Workplace Join and InTune Active Directory Groups: Domain Local, Global and Universal Using and Managing Active Directory Domain Controllers Forest and Domain Functional Levels Introduction to Active Directory Partitions and the Global Catalog Basic Forest Structure and Design Basic Domain Structure and Design Basic OU Structure and Design Module 2: Fundamentals of WAN management with Active Directory Understanding AD Sites and WAN Traffic Management Basic AD Sites and Logon Traffic Introduction to AD Sites and Replication Traffic Bridgehead Servers and Site Link Objects Site Aware Applications Module 3: Introduction to Active Directory Group Policy Objects Introduction to Group Policy Administrative Templates Fundamental Concepts of GPO Scripts Introduction to Creating and Using GPOs Principles of Managing Multiple GPOs Block, Enforce and Inheritance GPOs and Active Directory Versions Introduction to Controlling and Installing Software with GPOs, SRP and App Locker Module 4: Principles of Active Directory Integration Active Directory and ?The Cloud? User Principle Names, Authentication and Active Directory Federated Services Conclusion, Additional Resources, Labs and Exercises Additional course details: Nexus Humans 55152AC Fundamentals of Active Directory 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 55152AC Fundamentals of Active Directory 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.

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Duration 3 Days 18 CPD hours This course is intended for Developers Administrators Overview Understand why Blockchain is needed and where Explore the major components of Blockchain Learn about Hyperledger Fabric v1.1 and the structure of the Hyperledger Architecture Lean the features of the Fabric model including chaincode, SDKs, Ledger, Security and Membership Services Perform comprehensive labs on writing chaincode Explore the architecture of Hyperledger Fabric v1.1 Understand and perform in depth labs on Bootstrapping the Network Gain a detailed understanding of the benefits, components and architecture of Hyperledger Composer Learn Hyperledger Explorer and Hyperledger Composer Playground Perform comprehensive labs to integrate/develop an application with Hyperledger Fabric running a smart contract Build applications on Hyperledger Fabric v1.1 This instructor-led Hyperledger training course is designed for developers and administrators who want to take a comprehensive deep dive on Hyperledger Fabric and Hyperledger Composer. This Hyperledger training course has several comprehensive labs, giving you real world experience.In 3 days, you will learn the need for blockchain applications, where blockchain is used, and about Hyperledger Fabric, the open source framework for developing blockchain applications and solutions with a modular architecture. Introduction to Blockchain Introduction to Blockchain What is Blockchain Types of network Public network Permissioned network Private network Need for Blockchain Components of Blockchain Consensus Provenance Immutability Finality Where can Blockchain be used Example on Blockchain How Blockchain Works How Blockchain Works Structure of Blockchain Block Hash Blockchain Distributed Lifecycle of Blockchain Smart Contract Consensus Algorithm Proof of Work Proof of Stake Practical Byzantine Fault Tolerance Actors of Blockchain Blockchain developer Blockchain operator Blockchain regulator Blockchain user Membership service provider Building A Small Blockchain Application Introduction to Hyperledger Fabric v1.1 Introduction to Hyperledger What is Hyperledger Why Hyperledger Where can Hyperledger be used Hyperledger Architecture Membership Blockchain Transaction Chaincode Hyperledger Fabric Features of Hyperledger Fabric Installation of prerequisite Getting Started With Fabric Model The Fabric Model Features of Fabric Model Chaincode SDKs Ledger Privacy through channels Security and Membership services Assets Consensus Components of Fabric Model Peer Orderer Certificate Authority Building your network Chaincode Chaincode Chaincode API How to write a Chaincode Lab Work Architecture of Hyperledger Fabric v1.1 Architecture of Hyperledger Fabric Transaction Ledger Nodes Peer Endorser Ordering Nodes Channels Certificate Authority Transaction Flow Lab Work Bootstrapping Bootstrapping the Network Introduction Lab Work Task 1 - Generate the crypto material for the various participants. Task 2 - Generate the genesis block for the Orderer node and start ordering service (solo node). Task 3 - Generated the configuration transaction block to create a new channel. Task 4 - Sign the configuration block and create the new channel. Task 5 - Make peers of all the organizations join the channel that we created in Task 4 Introdcution to Hyperledger Explorer Introduction To Hyperledger Explorer Block Details Peer List Chaincode List Transaction Details Installation of Hyperledger Explorer Starting the Explorer App Introduction to Hyperledger Composer Introduction Components of Hyperledger Composer Benefits of Hyperledger Composer Key Concepts Hyperledger Composer Solution Installation Hyperledger Composer Playground Hyperledger Composer Playground Introduction Playground Overview Lab Work Additional course details: Nexus Humans Hyperledger Training - Developing on Hyperledger Fabric 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 Hyperledger Training - Developing on Hyperledger Fabric 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 5 Days 30 CPD hours This course is intended for This course is intended for Developers and architects who will be developing applications for iOS devices. In this course you'll be shown a complete introduction to iPhone and iPad development, emphasizing the newest technologies and best practices for iOS. Introduction & Setup Start Here Joining the Apple iOS Developer Program Installing Xcode and the iOS SDK A Guided Tour of Xcode An Introduction to Xcode Playgrounds Swift Programming Language Swift Data Types, Constants, and Variables Swift Operators and Expressions Swift Flow Control The Swift Switch Statement An Overview of Swift Functions The Basics of Object Oriented Programming in Swift An Introduction to Swift Subclassing and Extensions Working with Array and Dictionary Collections in Swift Understanding Error Handling in Swift Views, Layouts, & Storyboards iOS Application and Development Architecture Creating an Interactive iOS App Understanding Views, Windows and the View Hierarchy An Introduction to Auto Layout in iOS Working with iOS Auto Layout Constraints in Interface Builder Implementing iOS Auto Layout Constraints in Code Implementing Cross-Hierarchy Auto Layout Constraints in iOS Understanding the iOS Auto Layout Visual Format Language Using Trait Variations to Design Adaptive User Interfaces Using Storyboards in Xcode An Overview of iOS Table Views Using Xcode Storyboards to Build Dynamic TableViews Implementing TableView Navigation Working with the iOS Stack View Class A Guide to Multitasking in iOS Implementing a Page based iOS Application using UIPageViewController Data Storage with Files, iCloud, & Databases Working with Directories in Swift on iOS Working with Files in Swift on iOS Preparing an iOS App to use iCloud Storage Managing Files using the iOS UIDocument Class Using iCloud Storage in an iOS Application Synchronizing iOS Key-Value Data using iCloud iOS Database Implementation using SQLite Working with iOS Databases using Core Data CloudKit Data Storage on iOS Touch, Taps, & Gestures An Overview of iOS Multitouch, Taps and Gestures An Example iOS Touch, Multitouch and Tap Application Detecting iOS Touch Screen Gesture Motions Identifying Gestures using iOS Gesture Recognizers iOS 3D Touch Implementing TouchID Authentication in iOS Apps Advanced View Options Drawing iOS 2D Graphics with Core Graphics Interface Builder Live Views and iOS Embedded Frameworks Using Core Graphics and Core Image iOS Animation using UIViewPropertyAnimator iOS UIKit Dynamics iOS Sprite Kit Programming iOS Multitasking, Background Transfer Service and Fetching iOS Application State Preservation and Restoration Integrating Maps into iOS Applications Getting Location Information using the iOS Core Location Framework Extensions An Introduction to Extensions in iOS An iOS Today Extension Widget Tutorial Creating an iOS Photo Editing Extension Creating an iOS Action Extension Receiving Data from an iOS Action Extension Building iOS Message Apps Using Event Kit to Create Date and Location Based Reminders Multimedia and Social Media Accessing the iOS Camera and Photo Library iOS Video Playback using AVPlayer and AVPlayerViewController An iOS Multitasking Picture in Picture Tutorial Playing Audio on iOS using AVAudioPlayer Recording Audio on iOS with AVAudioRecorder iOS Speech Recognition Introduction to SiriKit Integrating Twitter and Facebook into iOS Applications The App Store Making Store Purchases with SKStoreProductViewController Class Building In-App Purchasing into iOS Applications Configuring and Creating App Store Hosted Content for iOS In-App Purchases Preparing and Submitting an iOS Application to the App Store Additional course details: Nexus Humans iOS App Development Essentials 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 iOS App Development Essentials 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 This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

Duration 2 Days 12 CPD hours This course is intended for IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS StatisticsBase. Anyone who wants to refresh their knowledge and statistical experience. Overview Introduction to statistical analysis Describing individual variables Testing hypotheses Testing hypotheses on individual variables Testing on the relationship between categorical variables Testing on the difference between two group means Testing on differences between more than two group means Testing on the relationship between scale variables Predicting a scale variable: Regression Introduction to Bayesian statistics Overview of multivariate procedures This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results. Introduction to statistical analysis Identify the steps in the research process Identify measurement levels Describing individual variables Chart individual variables Summarize individual variables Identify the normal distributionIdentify standardized scores Testing hypotheses Principles of statistical testing One-sided versus two-sided testingType I, type II errors and power Testing hypotheses on individual variables Identify population parameters and sample statistics Examine the distribution of the sample mean Test a hypothesis on the population mean Construct confidence intervals Tests on a single variable Testing on the relationship between categorical variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Identify differences between the groups Measure the strength of the association Testing on the difference between two group meansChart the relationship Describe the relationship Test the hypothesis of two equal group means Assumptions Testing on differences between more than two group means Chart the relationship Describe the relationship Test the hypothesis of all group means being equal Assumptions Identify differences between the group means Testing on the relationship between scale variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Treatment of missing values Predicting a scale variable: Regression Explain linear regression Identify unstandardized and standardized coefficients Assess the fit Examine residuals Include 0-1 independent variables Include categorical independent variables Introduction to Bayesian statistics Bayesian statistics and classical test theory The Bayesian approach Evaluate a null hypothesis Overview of Bayesian procedures in IBM SPSS Statistics Overview of multivariate procedures Overview of supervised models Overview of models to create natural groupings

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning on AWS 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 Deep Learning on AWS 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.