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Course Overview: This Investment course offers learners a comprehensive understanding of investment strategies and financial markets. The course covers a range of essential topics, including different investment types, portfolio management, and risk assessment. Learners will gain valuable insights into bond and stock markets, enabling them to make informed decisions in diverse investment environments. The course is designed for those looking to enhance their investment knowledge, regardless of their current financial expertise, providing a solid foundation in the principles of investing. Course Description: In this course, learners will explore various investment methods, from bonds to stocks, and gain an understanding of core financial concepts such as portfolio diversification and risk management. The course delves into investment theory, focusing on how markets function, the evaluation of potential returns, and the identification of risk factors. With an emphasis on building a structured investment strategy, learners will also gain an understanding of how to manage and optimise their portfolios. By the end, learners will have the tools and knowledge to evaluate different investment opportunities, supporting their financial growth and decision-making processes. Course Modules: Module 01: Introduction to Investment Overview of investment basics The role of investments in personal finance Understanding risk and return Module 02: Types and Techniques of Investment Stock market, bonds, and real estate investments Active vs passive investing Introduction to alternative investments Module 03: Key Concepts in Investment Compound interest and time value of money Diversification and asset allocation Financial instruments overview Module 04: Understanding the Finance Basics of financial statements Financial ratios and metrics Introduction to valuation techniques Module 05: Investing in Bond Market Types of bonds and their characteristics Bond pricing and yields Understanding interest rates and bond durations Module 06: Investing in Stock Market Stock market indices and trading Analysis of stock performance Fundamentals of stock picking Module 07: Risk and Portfolio Management Measuring and managing investment risk Portfolio construction and diversification strategies Evaluating portfolio performance (See full curriculum) Who is this course for? Individuals seeking to develop investment skills for personal financial growth. Professionals aiming to enhance their understanding of financial markets. Beginners with an interest in investing and financial markets. Anyone interested in building a solid foundation in investment strategies. Career Path: Investment Analyst Financial Planner Portfolio Manager Stock Broker Risk Manager Wealth Manager Financial Consultant

Course Overview This comprehensive course on "Complete After Effects for Graphic Design" is designed to equip learners with the skills necessary to use After Effects effectively in graphic design. Covering everything from creating visual effects and patterns to generating artwork from scratch, this course helps learners develop a deep understanding of After Effects tools and techniques. Learners will gain the confidence to create sophisticated animations and special effects that enhance their design projects. With practical lessons and a focus on industry-relevant skills, this course provides invaluable value to anyone looking to strengthen their graphic design capabilities using After Effects. Course Description In this course, learners will dive deep into the essential features of After Effects, including creating special effects, working with patterns and textures, and generating artwork from minimal input. The course takes a structured approach, starting with a solid introduction to After Effects, followed by advanced techniques for creating visually engaging content. By the end of the course, learners will be able to produce impressive animations and effects for use in graphic design projects. Throughout the course, learners will refine their understanding of animation principles and the software's advanced features, equipping them with the skills to implement creative ideas in a professional context. Course Modules Module 01: Introduction Introduction to After Effects interface Understanding key concepts in animation and motion design Navigating the timeline and workspace Module 02: Creating Special Effects Using effects and presets Creating cinematic effects for design Layering techniques and animation adjustments Module 03: Creating Patterns and Textures Working with textures and patterns Developing seamless loops and animated backgrounds Customising effects to suit design projects Module 04: Generating Artwork from (Almost) Nothing Techniques for generating artwork using basic shapes Exploring fractal animations and procedural design Using plugins to expand creative possibilities Module 05: Where to Go from Here Understanding next steps in advancing your After Effects skills Recommended resources for further learning Tips for building a professional portfolio (See full curriculum) Who is this course for? Individuals seeking to enhance their graphic design expertise. Professionals aiming to integrate animation and effects into their design projects. Beginners with an interest in digital design and animation. Designers wishing to improve their proficiency with After Effects. Career Path Graphic Designer Motion Graphics Designer Visual Effects Artist Animation Artist Digital Content Creator

Duration 2 Days 12 CPD hours This course is intended for Built for experienced IT Professionalsworking with Citrix Virtual Appsand Desktops who need to plan for,implement, or manage a ProvisioningServices environment. Potential studentsinclude administrators, engineers, andarchitects. Overview #NAME? In this course, students will learn to install and configure a highly available Citrix Provisioning farm according to leading practices. In this course, students will learn about the architecture, communication, and processes that make up Citrix Provisioning to be successful with deploying and managing a farm. Manage and integrate vDisks and target devices with Citrix Virtual Apps and Desktops for easy rollback, upgrades, and performance of Virtual Delivery Agent machines. At the end of this course students will be able to install, configure and manage the CitrixProvisioning 7 solution. Advanced Provisioning Learning Objectives Introduction to Citrix Provisioning (PVS) Getting Started with Citrix Provisioning Citrix Provisioning Architecture Citrix Provisioning Infrastructure Lab VM Power Management Learning Objectives The Citrix Provisioning Server The Farm Database The Store Streaming the vDisk Lab VM Power Management Learning Objectives vDisk Introduction Master Target Device Preparation Streaming Introduction Boot Methods Target Devices Lab VM Power Management Learning Objectives Target Devices Introduction Reads and Writes Machine and User Data Integrating Citrix Provisioning with Citrix Virtual Apps and Desktops Lab VM Power Management Learning Objectives The Complete Architecture Overview The Citrix Virtual Desktops Setup Wizard Manage the Target Devices through Creating Device Collections Using Provisioned Services with Citrix Virtual Apps and Desktops Managing Citrix Provisioning from Citrix Cloud Advanced Architecture Lab VM Power Management Learning Objectives Farm Component Scalability Store Redundancy Farm Database Redundancy Supporting Citrix Provisioning Lab VM Power Management Learning Objectives vDisk Updates Delegate Administration Audit and Support Alternative vDisk Update Methods

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 5 Days 30 CPD hours This course is intended for This is an introductory- level Java programming course, designed for experienced developers who wish to get up and running with JEE, or who need to reinforce sound Java for Web / JEE coding practices. Attendees should have a working knowledge of developing basic Java software applications. Overview Students who attend Mastering JEE Web Application Development will leave the course armed with the required skills to design and build scalable, secure, maintainable web applications - leveraging our extensive experience in the delivery of scalable enterprise applications with complex web interfaces based on JEE technologies. Throughout this training, you will be confronted with common web application design problems and given the tools you will need to solve them, such as JEE design patterns. You will also be exposed to a range of JEE and web technologies such as Servlets, JSPs, JSF, JNDI, CDI and advice on when and how to use them. Students will also learn about the capabilities of servlets, their advantages, servlet architecture, and session management. Developers will also learn about managing resources, deployment, and application models, how to use custom tags, and how to build robust and capable web applications using servlets and other components. The course begins with a discussion of web application architecture. A major part of the course is spent on the various web components that are used to implement dynamic web applications. Students will learn not only specific topics and APIs but also how to fit the pieces together into a complete application. Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will learn to: Design and build web applications from both business and technical requirements Build web interfaces with JSF, JSPs and Servlets, using the latest technologies in JEE. Write maintainable web applications that separate HTML and Java Understand the design and development of web applications using Servlets, JSPs, web fragments, and JSF Work JEE's version of dependency injection (CDI) Make Servlets cooperate and share data Store and process session information Deal with concurrency issues Access databases with JPA Work with annotations included in JEE Work with WebSockets as well as asynchronous servlets Use Java Bean validation in a web application Properly handle various types of exceptions This course is for experienced Java developers who are new to JEE and need to get up and running with essential dynamic web development skills. You will gain core JEE knowledge and skills that can be used as the foundation for developing production-quality web applications to a basic level. Developing Java EE applications Enterprise Development Java EE Core Components JEE Dynamic Web Applications Introduction to Servlets Form processing using Servlets Java Server Pages Implementing MVC in JEE Session Management JEE Servlet Filters and Listeners Servlet Filters Expression Language 3.0 (EL) Overview of EL The EL language Custom Tags Introduction to Custom Tags The Java Standard Tag Library Contexts and Dependency Injection (CDI) Introduction to CDI Using CDI CDI and Java EE Using Resources JEE DataSources Overview of JPA Java API for WebSocket Introduction to WebSocket Implementing WebSocket Endpoint Extending WebSockets Java Bean Validation (JSR 349) Introduction to Bean Validation Bean Validation Managing Web Applications Web Fragments Error Handling Asynchronous Servlets Web Security Introduction to Java Server Faces Introduction to JSF JSF Components Facelets Facelets Facelets Templating and Resources Additional course details: Nexus Humans Mastering JEE Web Development (TT5100) 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 Mastering JEE Web Development (TT5100) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for The course will likely be attended by SQL Server report creators who are interested in alternative methods of presenting data. Overview After completing this course, students will be able to: ? Perform Power BI desktop data transformation. ? Describe Power BI desktop modelling. ? Create a Power BI desktop visualization. ? Implement the Power BI service. ? Describe how to connect to Excel data. ? Describe how to collaborate with Power BI data. ? Connect directly to data stores. ? Describe the Power BI developer API. ? Describe the Power BI mobile app. The main purpose of the course is to give students a good understanding of data analysis with Power BI. The course includes creating visualizations, the Power BI Service, and the Power BI Mobile App. Introduction to Self-Service BI Solutions Introduction to business intelligence Introduction to data analysis Introduction to data visualization Overview of self-service BI Considerations for self-service BI Microsoft tools for self-service BI Lab : Exploring an Enterprise BI solution Introducing Power BI Power BI The Power BI service Lab : Creating a Power BI dashboard Power BI Using Excel as a data source for Power BI The Power BI data model Using databases as a data source for Power BI The Power BI service Lab : Importing data into Power BI Shaping and Combining Data Power BI desktop queries Shaping data Combining data Lab : Shaping and combining data Modelling data Relationships DAX queries Calculations and measures Lab : Modelling Data Interactive Data Visualizations Creating Power BI reports Managing a Power BI solution Lab : Creating a Power BI report Direct Connectivity Cloud data Connecting to analysis services Lab : Direct Connectivity Developer API The developer API Custom visuals Lab : Using the developer API Power BI mobile app The Power BI mobile app Using the Power BI mobile app Power BI embedded

Course Overview The German Language Course for Beginners is designed to provide a comprehensive introduction to one of the world’s most widely spoken languages. Whether for travel, work, or personal enrichment, this course offers a solid foundation in speaking, reading, writing, and understanding German. Learners will gain essential communication skills, from everyday greetings to basic conversations, allowing them to navigate a variety of real-world situations confidently. The course focuses on developing vocabulary, pronunciation, sentence construction, and listening comprehension through engaging and accessible lessons. By the end of the course, learners will be able to understand and communicate basic ideas in German, laying the groundwork for further study or everyday interactions. This course is ideal for those seeking a structured and supportive environment to start their German language journey and aims to deliver practical outcomes that can be applied across travel, education, and professional settings. Course Description The German Language Course for Beginners offers an engaging exploration into the fundamentals of German communication. Through a series of structured lessons, learners will cover key topics such as introductions, numbers, days of the week, everyday vocabulary, basic grammar rules, verb conjugations, and common expressions. The course presents material in a logical progression to ensure that learners build confidence step-by-step, with an emphasis on pronunciation and conversational fluency. Interactive exercises, cultural insights, and simple dialogues enhance the learning experience, fostering both comprehension and retention. By participating in this course, learners will acquire the foundational skills necessary to engage in basic conversations, understand simple written texts, and grasp the structure of the German language. Designed for complete beginners, this programme offers a supportive and stimulating learning environment, making it a valuable stepping stone for further language study, career development, or international travel. Course Modules Module 01: Introduction to the German Language Module 02: German Alphabet and Pronunciation Module 03: Basic Greetings and Introductions Module 04: Numbers, Dates, and Time Module 05: Essential Vocabulary for Everyday Situations Module 06: Basic Grammar: Articles, Nouns, and Verbs Module 07: Forming Simple Sentences and Questions Module 08: Common Phrases and Daily Expressions Module 09: Introduction to German Culture and Customs (See full curriculum) Who is this course for? Individuals seeking to learn German for personal, educational, or travel purposes. Professionals aiming to enhance their career prospects through multilingual skills. Beginners with an interest in European languages and cultures. Students preparing for further German language studies or international opportunities. Career Path Tourism and Hospitality Sector Roles International Customer Support Positions Language Tutoring or Educational Support Translation and Interpretation Assistance Administrative and Office Roles in International Companies

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 This course is designed for students with previous Citrix ADC experience, and best suited for individuals who will be deploying Citrix Application Delivery Management to administer a Citrix Networking environment or optimize Citrix ADC-managed application delivery traffic. Overview Manage multiple Citrix ADC platforms centrallyOrchestrate configuration changesReport on transactions passing through the Citrix ADC environmentVisualize infrastructure and plan expansion Master the deployment and usage of Citrix Application Delivery Management with this two-day management and optimization course. Students will gain the skills needed to automate and manage network services for scale out of application architectures, and to optimize Citrix ADC-managed application delivery traffic. The curriculum focuses on centrally managing multiple Citrix ADC platforms, orchestrating configuration changes, reporting on transactions, visualizing infrastructure and planning infrastructure expansion. Students will also learn how to implement Citrix ADC features, including caching, frontend optimization, Citrix ADC web logging and TCP/HTTP optimization, to optimize traffic managed by your Citrix networking environment. Citrix Application Delivery Management Introduction An introduction to Application Delivery Management Application Delivery Management Deployment and Configuration Deploying Application Delivery Management in High Availability Application Delivery Management Instance Management Managing and Monitoring Application Delivery Management An introduction to Application Delivery Management Application Delivery Management Deployment and Configuration Deploying Application Delivery Management in High Availability Application Delivery Management Instance Management Managing Citrix ADC Configuration Application Management StyleBooks Configuration Management Citrix ADC Web Logging Understanding Web Traffic Installing and configuring Citrix ADC Web Logging Troubleshooting Citrix ADC Web Logging Citrix ADC Integrated Caching Introduction to Integrated Caching Static and Dynamic Content Request and Response Process Flow Understanding Cache Policies Identifying Content Group Settings Front-End Optimization Improving Content Delivery Front-End Optimization Use Cases Understanding Minification CSS Optimizations Tuning and Optimizations Connections on the Citrix ADC Connection Profiles Queuing on the Citrix ADC Connection Tuning Practices

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