18760 Courses

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.

Duration 2 Days 12 CPD hours This course is intended for Application developers who want to increase their understanding of Spring and Spring Boot and a focus on fundamentals. Overview By the end of the course, you should be able to meet the following objectives: Describe the benefits provided by Spring Boot Initialize a project using Spring Boot Starters Leverage Spring Boot's auto configuration features Create simplified backing-store solutions using Spring Data JPA Build a simple MVC application using Spring Boot, embedded Web Server and fat JARs or classic WARs Build a RESTful Web application Use Spring Security to secure Web and REST endpoints Enable and extend metrics and monitoring capabilities using Spring Boot actuator Leverage advance configuration capabilities Utilize Spring Boot enhancements to testing This course offers experience with Spring Boot and its major features, including auto-configuration, Actuator, Spring Boot testing framework and more. On completion, participants will have a foundation for creating enterprise and cloudready applications. Please note that this course is a subset of the material in our 4-day Spring: Core Training course - there is no need to take both courses. This course is recommended if you have a good working knowledge of Spring Basics (see Prerequisites) but are new to Spring Boot. Introduction to Spring Essentials Why Spring Configuration using Spring Bean creation Data Management Spring Boot Introduction Introduction to Spring Boot Features Value Proposition of Spring Boot Creating a simple Boot application using Spring Initializer website Spring Boot Dependencies, Auto-configuration, and Runtime Dependency management using Spring Boot starters How auto-configuration works Configuration properties Overriding auto-configuration Using CommandLineRunner JPA with Spring and Spring Data Quick introduction to ORM with JPA Benefits of using Spring with JPA JPA configuration in Spring Configuring Spring JPA using Spring Boot Spring Data JPA dynamic repositories Spring MVC Architecture and Overview Introduction to Spring MVC and request processing Controller method signatures Using @Controller, @RestController and @GetMapping annotations Configuring Spring MVC with Spring Boot Spring Boot packaging options, JAR or WAR Rest with Spring MVC An introduction to the REST architectural style Controlling HTTP response codes with @ResponseStatus Implementing REST with Spring MVC, @RequestMapping, @RequestBody and @ResponseBody Spring MVC?s HttpMessageConverters and automatic content negotiation Spring Security What problems does Spring Security solve? Configuring authentication Implementing authorization by intercepting URLs Authorization at the Java method level Understanding the Spring Security filter chain Spring security testing Actuators, Metrics and Health Indicators Exposing Spring Boot Actuator endpoints Custom Metrics Health Indicators Creating custom Health Indicators External monitoring systems Spring Boot Testing Enhancements Spring Boot testing overview Integration testing using @SpringBootTest Web slice testing with MockMvc framework Slices to test different layers of the application

Duration 3.5 Days 21 CPD hours This course is intended for This course is for AWS Cloud Architects with expertise in designing and implementing solutions running on AWS who now want to design for Microsoft Azure. Overview After completing this course, students will be able to: Secure identities with Azure Active Directory and users and groups. Implement identity solutions spanning on-premises and cloud-based capabilities Apply monitoring solutions for collecting, combining, and analyzing data from different sources. Manage subscriptions, accounts, Azure policies, and Role-Based Access Control. Administer Azure using the Resource Manager, Azure portal, Cloud Shell, and CLI. Configure intersite connectivity solutions like VNet Peering, and virtual network gateways. Administer Azure App Service, Azure Container Instances, and Kubernetes. This course teaches Solutions Architects who have previously designed for Amazon Web Services how to translate business requirements into secure, scalable, and reliable solutions for Azure. Introduction to Azure Subscriptions and accounts Resource groups and templates in Azure Resource Manager Azure global infrastructure Azure regions Azure Availability Zones Comparison with AWS Implement Azure Active Directory Introduction to Azure Active Directory Domains and custom domains Safety features Guest users in Azure Active Directory Manage multiple directories Comparison with AWS Implement and manage hybrid identities Introduction to Azure AD Connect Comparison with AWS Implement virtual networking Azure Virtual Network and VNet peering VPN and ExpressRoute connections Comparison with AWS Implement VMs for Windows and Linux Configure high availability Comparison with AWS Implement load balancing and network security Implement Azure Load Balancer Implement an Azure Application Gateway Implement Azure Firewall Implement network security groups and application security groups Comparison with AWS Implement container-based applications Configure Azure Kubernetes Service Publish a solution on an Azure Container Instance Comparison with AWS Implement an application infrastructure Create an App Service plan Create and configure Azure App Service Configure networking for an App Service Introduction to Logic Apps and Azure Functions Comparison with AWS Implement storage accounts Azure Storage core concepts Managing the Azure Blob storage lifecycle Working with Azure Blob storage Comparison with AWS Implement NoSQL databases Introduction to Azure Cosmos DB Consistency Select appropriate CosmosDB APIs Set up replicas in CosmosDB Comparison with AWS DynamoDB Implement Azure SQL databases Configure Azure SQL database settings Implement Azure SQL Database managed instances Configure high availability for an Azure SQL database Comparison with AWS Implement cloud infrastructure monitoring Monitor security Monitor cost Configure a Log Analytics workspace Comparison with AWS Implement and manage Azure governance solutions Assign RBAC roles Configure management access to Azure Implement and configure an Azure Policy Comparison with AWS Manage security for applications Implement Azure Key Vault Implement and configure Azure AD Managed Identities Register and manage applications in Azure AD Comparison with AWS Migration, backup, and disaster recovery management Migrate workloads Implement Azure Backup for VMs Implement disaster recovery Comparison with AWS

Duration 2 Days 12 CPD hours This course is intended for Report Authors Overview Create query models Create reports based on query relationships Introduction to dimensional data Introduction to dimensional data in reports Dimensional report context Focus your dimensional data Calculations and dimensional functions Create advanced dynamic reports This offering teaches Professional Report Authors about advanced report building techniques using relational data models, dimensional data, and ways of enhancing, customizing, managing, and distributing professional reports. The course builds on topics presented in the Fundamentals course. Activities will illustrate and reinforce key concepts during this learning activity. Create query models Build a query and connect it to a report Answer a business question by referencing data in a separate query Create reports based on query relationships Create join relationships between queries Combine data containers based on relationships from different queries Create a report comparing the percentage of change Introduction to dimensional reporting concepts Examine data sources and model types Describe the dimensional approach to queries Apply report authoring styles Introduction to dimensional data in reports Use members to create reports Identify sets and tuples in reports Use query calculations and set definitions Dimensional report context Examine dimensional report members Examine dimensional report measures Use the default measure to create a summarized column in a report Focus your dimensional data Focus your report by excluding members of a defined set Compare the use of the filter() function to a detail filter Filter dimensional data using slicers Calculations and dimensional functions Examine dimensional functions Show totals and exclude members Create a percent of base calculation Create advanced dynamic reports Use query macros Control report output using a query macro Create a dynamic growth report Create a report that displays summary data before detailed data and uses singletons to summarize information Design effective prompts Create a prompt that allows users to select conditional formatting values Create a prompt that provides users a choice between different filters Create a prompt to let users choose a column sort order Create a prompt to let users select a display type Examine the report specification Examine report specification flow Identify considerations when modifying report specifications Customize reporting objects Distribute reports Burst a report to email recipients by using a data item Burst a list report to the IBM Cognos Analytics portal by using a burst table Burst a crosstab report to the IBM Cognos Analytics portal by using a burst table and a master detail relationship Enhance user interaction with HTML Create interactive reports using HTML Include additional information with tooltips Send emails using links in a report Introduction to IBM Cognos Active Reports Examine Active Report controls and variables Create a simple Active Report using Static and Data-driven controls Change filtering and selection behavior in a report Create interaction between multiple controls and variables Active Report charts and decks Create an Active Report with a Data deck Use Master detail relationships with Decks Optimize Active Reports Create an Active Report with new visualizations

Duration 5 Days 30 CPD hours This course is intended for Developed for experienced IT Professionals working with Citrix Virtual Apps and Desktops 7.1x. Potential students include administrators, engineers, and architects responsible for the end user workspace, provisioning services environment, and overall health and performance of the solution. Overview How to configure Workspace Environment Management to improve the end user environment and virtual resource consumption Understand Zones in Citrix Virtual Apps and Desktops 7.1x and how to account for user and desktop locations and optimal connection and registration How to build and manage App Layers to minimize image sprawl with Citrix Virtual Apps and Desktops 7.1x Understand and configure HDX channels and protocols for improved performance delivering multimedia and data over network connections Get more value out of your Citrix Virtual Apps and Desktops 7.1x investment through the use of Workspace Environment Management, Provisioning Services, Application Layering, and advanced features. Students leave this course with a good understanding of how to manage more complex solutions such as multizone environments spanning multiple locations with configurations around StoreFront, the Delivery Controllers, and HDX. Students will gain the skills to improve logon times, user personalization, and resource performance through Workspace Environment Management. Also, learn to optimize management of your app and desktop images by building and combining App Layers. End the course by learning to install, configure, and manage Provisioning Services in accordance with leading practices.This course includes a voucher to take the related exam (1Y0-311 Citrix XenApp and XenDesktop 7.15 Advanced Administration) and earn your Citrix Certified Professional - Virtualization (CCP-V) certification. Implementing Redundancy and Scalability StoreFront and Citrix Gateway Site Infrastructure Machines Running the Virtual Delivery Agent Managing a Virtual Apps and Desktops Environment with Multiple Locations Zones VDA Registration in a Multi-Zone Environment Zone Preference Optimal Gateway Routing and Zones Managing StoreFront Store Subscriptions in a Multi- Location Environment StoreFront and Citrix ADC Branding Implementing Backups and Disaster Recovery Backups Disaster Recovery Considerations Disaster Recovery Process Implementing Advanced Authentication Methods Multi-factor Authentication - RADIUS & OTP Multi-factor Authentication - Smart Card Authentication Federated Authentication - ADFS, SAML, and FAS Improving App and Data Security Introduction to Application Security Preventing Jailbreak Attacks Minimizing the Impact of Attacks Securing Machines Running the Virtual Delivery Agent TLS to VDA Encryption GPOs and Citrix Policies Image Management Introduction to Troubleshooting Troubleshooting Methodology Process (Standard Slide) Resource Tools and Utilities Introduction to PowerShell Troubleshooting Access Issues Troubleshooting StoreFront Troubleshooting Citrix Gateway Troubleshooting Delivery Controller Issues Validating FMA Services Troubleshooting VDA Registration Issues Troubleshooting VDA Registration Troubleshooting HDX Connection Issues Troubleshooting HDX Connections Introduction to App Layering App Layering Introduction Architecture and How it Works Creating an OS Layer The OS Layer Creating a Platform Layer The Platform Layer Creating App Layers The App Layers Creating Elastic App and User Layers Elastic App Layering User Layers Deploying a Layered Image using Citrix Virtual Apps and Desktops Using Templates in App Layering Using Layered Images in a Citrix Virtual Apps and Desktops Site Exploring Layer Priority Layer Priority Maintaining an App Layering Environment Updating Layers Maintaining and Updating the App Layering Environment Common App Layering Considerations and Additional Resources Introduction to Workspace Environment Management (WEM) Workspace Environment Management (WEM) Introduction WEM Administration Using WEM to Centralize Managing User Resources with WEM Managing Profiles with WEM Managing Endpoints with the WEM Transformer Feature Using WEM for Performance Optimization Optimizing Machine Performance with WEM Optimizing User Experience with WEM Using WEM to Secure Environments WEM Environments Migrating and Upgrading WEM Migrating to WEM Upgrading a WEM Deployment WEM Multi-Location Considerations

Duration 4 Days 24 CPD hours This course is intended for System installersSystem integratorsSystem administratorsNetwork administratorsSolutions designers Overview After completing this course, you should be able to:Explain transactional service activation and how it relates to business requirementsExplain the benefits and uses of Cisco NSOExplain how Cisco NSO communicates with network devicesUnderstand the NETCONF protocol and be able to read and write simple YANG modelsInstall NSO and describe how NSO uses NETCONF and the Device Manager componentUnderstand the difference between devices that are fully NETCONF capable and those that are less or not NETCONF capableExplain the YANG service model structureDescribe how YANG is used with NSO, create and deploy a service, and explain NSO FASTMAPDesign and manage services with YANG modelsPerform NSO configuration and basic troubleshooting, and describe the following NSO features: integration options, alarms and reporting, scalability and performance options, and available function packsUse logs to troubleshoot the Cisco NSO deployment and check NSO communication with network devicesExplain the mapping logic of service parameters to device models and consequently to device configurationsDescribe the use of different integration options and APIsExplain the use of Reactive FASTMAP for manipulating and implementing advanced Network Functions Virtualization (NFV) componentsDescribe the use of feature components and function packsDefine and explain the European Telecommunications Standards Institute (ETSI) Open Source NFV Management and Orchestration (MANO) principles and solutionWork with the alarm console, and understand the NSO alarm structure and how it conforms to modern network operations procedures The Cisco NSO Essentials for Programmers and Network Architects (NSO201) course introduces you to Cisco© Network Services Orchestrator (NSO). You will learn to install Cisco NSO and use it to manage devices and create services based on YANG templates with XPath. This course provides a brief overview of NSO as a network automation solution, as well as an introduction to NETCONF, YANG, and XPath. You will learn about service packages, network element drivers, and Application Programming Interfaces (APIs). The course also covers service creation, device and configuration management, NSO maintenance, NSO options and integrations, and basic NSO troubleshooting. Introduction to Cisco NSO Meeting Challenges with Orchestration Challenges of Network Management Challenges of Network Orchestration NSO Features and Benefits That Meet Challenges Standardized Approach What Is NSO? Logical Architecture Components What Does NSO Do? Orchestration Use Cases How Does NSO Work? Introduction to NETCONF and YANG Packages Mapping Logic Network Element Drivers (NEDs) Resources and Training Resources Training Get Started with Cisco NSO Installing Cisco NSO Setup Overview Cisco NSO Local Installation Installing NEDs Using NetSim NETCONF Overview Challenges of Network Management Introduction to NETCONF NETCONF Operation Device Manager Device Manager Overview Device Configuration Management Device Connection Management Templates and Groups Other Device Management Tools Service Manager Essentials YANG Overview Introduction to YANG Other Representations of YANG Data Types XPath Overview Basic YANG Statements Can You Spot the Error? Using Services Package Architecture Creating a Service Package Sample Service Configuration Service Template YANG Service Model Deploying a Service Model-to-Model Mapping Mapping Introduction Mapping Logic FASTMAP Template Processing Service Design and Cisco NSO Programmability Service Design Service Design Overview Top-Down Approach Bottom-Up Approach Device Configuration Service Model Service Management Service Management Tasks Service Lifecycle Management Guidelines NSO Programmability Introduction NSO Programmability Overview Python Service Skeleton Creating a Service YANG Model Creating a Service Template Template Processing with Python Cisco NSO Flexibility System Configuration and Troubleshooting System Configuration System Troubleshooting Integration Integration Options NETCONF Server Web Integration SNMP Agent Alarm Management and Reporting Alarm Management Reporting Scalability and Performance High Availability High-Availability Cluster Communications Clustering Layered Service Architecture Addressing Performance Limitations Components and Function Packs Function Packs NFV Orchestration Reactive FASTMAP

Duration 4 Days 24 CPD hours This course is intended for This course is geared for experienced skilled Java developers, software developers, data scientists, machine learning experts or others who wish to transtion their coding skills to Scala, learning how to code in Scala and apply it in a practical way. This is not a basic class. Overview Working in a hands-on learning environment led by our expert instructor you'll: Get comfortable with Scala's core principles and unique features, helping you navigate the language confidently and boosting your programming skills. Discover the power of functional programming and learn techniques that will make your code more efficient,maintainable, and enjoyable to write. Become proficient in creating dynamic web applications using the Play Framework, and easily connect to databases with the user-friendly Slick library. Master concurrency programming with Akka, empowering you to build scalable and fault-tolerant applications that excel in performance. Enhance your testing skills using ScalaTest and ScalaCheck, ensuring the reliability and quality of your Scala applications, while having fun in the process. Explore the fascinating world of generative AI and GPT technologies, and learn how to integrate them into your projects,adding a touch of innovation and intelligence to your Scala solutions. If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals. Discover the power of Scala programming in our comprehensive, hands-on technical training course designed specifically for experienced object-oriented (OO) developers. Scala is a versatile programming language that combines the best of both OO and functional programming paradigms, making it ideal for a wide range of projects, from web applications to big data processing and machine learning. By mastering Scala, you'll be able to develop more efficient, scalable, and maintainable applications. Fast Track to Scala Programming for OO / Java Developers is a four day hands-on course covers the core principles of Scala, functional programming, web application development, database connectivity, concurrency programming, testing, and interoperability between Scala and Java. Additionally, you'll explore cutting-edge generative AI and GPT technologies, learning how to integrate them into your Scala applications for intelligent suggestions or automation. Throughout the course you?ll explore the latest tools and best practices in the Scala ecosystem, gaining valuable knowledge and experience that can be directly applied to your day-to-day work. With 50% of the course content dedicated to hands-on labs, you'll gain practical experience applying the concepts you've learned across various projects, such as building functional web applications, connecting to databases, designing modular components, and implementing concurrency. Upon completing the course, you'll have a solid understanding of the language and its features, empowering you to confidently apply your new skills in data science and machine learning projects. You'll exit well-prepared to create efficient, scalable, and maintainable Scala applications, regardless of the complexity of your projects. Introduction to Scala Scala features and benefits Comparing Scala with Java and other OO languages Installing Scala and setting up the development environment Object-Oriented Programming in Scala Classes and objects Traits, mixins, and inheritance Companion objects and factories Encapsulation and polymorphism Functional Programming Basics Pure functions and referential transparency Higher-order functions and currying Immutability and persistent data structures Pattern matching and recursion Having Fun with Functional Data Structures Lists, sets, and maps in Scala Folding and reducing operations Stream processing and lazy evaluation For-comprehensions Building Web Applications in Functional Style Introduction to Play Framework Functional web routing and request handling JSON handling with Play-JSON Middleware and functional composition Connecting to a Database Introduction to Slick library Database configuration and setup Querying and updating with Slick Transactions and error handling Building Scalable and Extensible Components Modular architecture and design patterns Dependency injection with MacWire Type classes and type-level programming Implicit parameters and conversions Concurrency Programming & Akka Introduction to Akka framework and Actor model Actor systems and message passing Futures and Promises Supervision and fault tolerance Building Confidence with Testing Introduction to ScalaTest and ScalaCheck Unit testing and property-based testing Test-driven development in Scala Mocking and integration testing Interoperability between Scala and Java Calling Java code from Scala Using Java libraries in Scala projects Converting Java collections to Scala collections Writing Scala code that can be called from Java Using Generative AI and GPT Technologies in Scala Programming Overview of GPT and generative AI Integrating GPT with Scala applications Use cases and practical examples

Duration 70 Days 420 CPD hours Cisco Learning Library: Networking offers a subscription to all Cisco core online networking training, including product training, technology training, and certifications such as Cisco Routing and Switching, Wireless, Design, and Network Programmability.This comprehensive technical training library includes full-length, interactive certification courses, additional product and technology training with labs, and thousands of reference materials. Networking Library Certification Courses CCNA Implementing and Administering Cisco Solutions (CCNA) v1.0 CCNP Enterprise Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 Implementing Cisco Enterprise Advanced Routing and Services (ENARSI) v1.0 Implementing Cisco SD-WAN Solutions (SDWAN300) v1.0 Designing Cisco Enterprise Networks (ENSLD) v1.0 Designing Cisco Enterprise Wireless Networks (ENWLSD) v1.0 Implementing Cisco Enterprise Wireless Networks (ENWLSI) v1.1 Implementing Automation for Cisco Enterprise Solutions (ENAUI) v1.0 CCIE Enterprise Infrastructure Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 CCIE Enterprise Wireless Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 Product and Technology Training Implementing and Administering Cisco Solutions (CCNA) v1.0 Developing Applications and Automating Workflows Using Cisco Core Platforms (DEVASC) v1.0 Developing Applications Using Cisco Core Platforms and APIs (DEVCOR) v1.0 Developing Solutions Using Cisco IoT and Edge Platforms (DEVIOT) v1.0 Implementing DevOps Solutions and Practices Using Cisco Platforms (DEVOPS) v1.0 Developing Applications for Cisco Webex and Webex Devices (DEVWBX) v1.0 Implementing Automation for Cisco Enterprise Solutions (ENAUI) v1.0 Implementing Automation for Cisco Collaboration Solutions (CLAUI) v1.0 Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.0 Implementing Automation for Cisco Security Solutions (SAUI) v1.0 Implementing Automation for Cisco Service Provider Solutions (SPAUI) v1.0 Introducing Automation for Cisco Solutions (CSAU) v1.0 Cisco Certified Technician Supporting Cisco Routing and Switching Network Devices (RSTECH) v3.0 Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.0 Implementing Cisco Enterprise Advanced Routing and Services (ENARSI) v1.0 Implementing Cisco SD-WAN Solutions (SDWAN300) v1.0 Designing Cisco Enterprise Networks (ENSLD) v1.0 Implementing Cisco Enterprise Wireless Networks (ENWLSI) v1.1 Cisco NCS 2000 Deploying 96-Channel Flex Spectrum (OPT201) v3.0 Cisco Digital Network Architecture Implementation Essentials (DNAIE) v2.0 Understanding Cisco Industrial IoT Networking Foundation (INFND) v1.0 Programming Use Cases for Cisco Digital Network Architecture v1.0 (DNAPUC) v1.0 Engineering Cisco Meraki Solutions Part 1 (ECMS1) v1.0 Deploying Cisco SD-Access (ENSDA) v1.1 Cisco SD-WAN Operation and Deployment (ENSDW) v1.0 Introduction to Cisco IOS XR (IOSXR100) v2.0 Cisco IOS XR System Administration (IOSXR200) v1.1 Cisco IOS XR Basic Troubleshooting (IOSXR201) v1.1 Cisco ASR 9000 Series IOS XR 64-Bit Software Migration and Operational Enhancements (IOSXR211) v1.0 Cisco IOS XR Layer 3 VPN Implementation and Verification (IOSXR301) v1.1 Cisco IOS XRMulticast Routing Implementation and Verification (IOSXR302) v1.1 Cisco IOS XR Broadband Network Gateway Implementation and Verification (IOSXR304) v1.0 NSO Essentials for Programmers and Network Architects (NSO201) v3.0 Cisco NSO Administration and DevOps (NSO303) v3.0 Cisco Optical Technology Advanced (OPT300) v2.0 Implementing Segment Routing on Cisco IOS XR (SEGRTE201) v2.0 Operating and Implementing Cisco WAN Automation Engine (WAE200) v3.0 Implementing Cisco Virtual Wide Area Application Services (VWAAS) v1.0 Configuring and Operating Cisco EPN Manager (EPNM100) v3.0 Cisco Elastic Services Controller (ESC300) v2.0 Product and Technology Training Deploying Cloud Connect Solutions with Cisco Cloud Services Router 1000V (CLDCSR) v1.0 Implementing Cisco Multicast (MCAST) v2.0 Cisco Prime Central Intermediate ? Administration and Operations (CPCI-AO) v1.0 Cisco Prime Network Intermediate ? Administration and Operation (CPNI-AO) v1.1 Cisco Prime Provisioning (CPP) v6.5 Cisco Prime Performance Manager (CPPERF) v1.0 Implementing Cisco Catalyst 9000 Switches (ENC9K) v1.0 Cisco Aggregation Services Router 9000 Series Essentials (ASR9KE) v6.0 Network Convergence System 5500 Series Router (NCS5500HW) v1.0 Cisco DNA Center Fast-Start Use Cases (A-SDA-FASTSTART) Getting Started with DNA Center Assurance (A-DNAC-ASSUR) v1.0 Overview of Cisco DNA Center Fast Start Use Cases for System Engineers (P-SDA-SYSEF) Planning and Deploying SD-Access Fundamentals (For Customers) (CUST-SDA-FUND) v1.0 Preparing the Identity Services Engine (ISE) for SD-Access (For Customers) (CUST-SDA-ISE) v1.0 SD-Access 1.2 Update Supplement (A-SDA-12UPDT) The SD-WAN Mastery Collection - Getting Started (For Customers) v1.0 (A-SDW-START) The SD-WAN Mastery Collection - Deploying the Data Plane (For Customers) v1.0 (A-SDW-DATPLN) The SD-WAN Mastery Collection - Developing the Overlay Topology (For Customers) v1.0 (A-SDW-OVRLAY) The SD-WAN Mastery Collection - Managing the Application Experience (For Customers) v1.0 (A-SDW-APPEXP) The SD-WAN Mastery Collection - Bringing Up the Control Plane Devices (For Customers) v1.0 (A-SDW-CTRPLN) Securing Branch Internet and Cloud Access with Cisco SD-WAN (A-SDW-BRSEC) Programming for Network Engineers (PRNE) v1.0 Cisco Optical Technology Intermediate (OPT200) v2.0 Advanced Implementing and Troubleshooting MPLS VPN Networks (AMPLS) BGP Bootcamp (BGP) Building Core Networks with OSPF, IS-IS, BGP and MPLS Bootcamp (BCN) Configuring BGP on Cisco Routers (BGP) v4.0 Implementing Cisco MPLS v3.0 Internetworking Technology Overview (ITO) Introduction to IP Multicast Bootcamp Introduction to IPsec VPN Bootcamp (IPsec VPN) Introduction to IPv6 Bootcamp (IPv6) Introduction to MPLS-VPN Bootcamp (MPLS-VPN) LAN Switching Bootcamp (LAN-SW) RP Bootcamp Troubleshooting for Network Support Engineers