14101 Courses

Overview Adults Support Worker: Adults Support Worker Course Online Do you want to learn about the psychology of the elderly? Do you want to learn more about their needs and goals and to understand them better? Is this your first step toward a professional career as a caregiver or a psychologist, or do you want to learn how to care for an elderly relative at home? Then this Adults Support Worker course is ideal for you if you want to start a career in adult psychotherapy and counselling. This informative Adults Support Worker: Adults Support Worker course is an excellent way to get started in the field of adult counselling. The Adults Support Worker course starts with basic Adults Support Worker knowledge and gradually shares expertise. It will provide you with a comprehensive understanding of Adults Support Worker, including key concepts, strategies for using it, and in-depth knowledge. Our Adults Support Worker: Adults Support Worker course will give you a competitive advantage in your career, allowing you to stand out from all other applicants and employees. So what are you waiting for? Enrol in this Adults Support Worker course today! Main Course: Adults Support Worker Free Courses with this Adults Support Worker: Course 01: Mental Health Support Worker Course 02: Level 5 Mental Health Care - MCA and DOLS [ Note: Free PDF certificate as soon as completing the Adults Support Worker: Adults Support Worker course] Description Adults Support Worker: Adults Support Worker Course Online This Adults Support Worker course consists of 06 modules. Course Curriculum of Adults Support Worker: Adults Support Worker Course Module 01: Introduction to Adults Support Worker Module 02: Introduction to Psychology of Older Age - Part I Module 03: Psychology of Older Age - Part II Module 04: Impact of Mental Health in the Old Age Module 05: Dealing with Life Module 06: Enhancing Health and Wellbeing Certificate of Completion You will receive a course completion certificate for free as soon as you complete the Adults Support Worker: Adults Support Worker Course. Who is this course for? Adults Support Worker: Adults Support Worker Course Online Anyone who wants to learn about 'older age' psychology (gerontology). Anyone who is interested in various topics related to psychology. Requirements Adults Support Worker: Adults Support Worker Course Online To enrol in this Adults Support Worker: Adults Support Worker Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Adults Support Worker: Adults Support Worker Course. Be energetic and self-motivated to complete our Adults Support Worker: Adults Support Worker Course. Basic computer Skill is required to complete our Adults Support Worker: Adults Support Worker Course. If you want to enrol in our Adults Support Worker: Adults Support Worker Course, you must be at least 15 years old.

Environmental Engineering: Environmental Engineering Course Online Would you like to know the advanced principles and practices of environmental engineering? This Environmental Engineering: Environmental Engineering Course program will fully covers key areas of this subject. The Environmental Engineering: Environmental Engineering Course will descries about water and air quality management, waste treatment and other relevant topics. The Environmental Engineering: Environmental Engineering Course includes environmental impact assessment and sustainable engineering solutions. Students of Level 7 Environmental Engineering Diploma gain expertise in designing and implementing strategies to address environmental challenges. Also, the Environmental Engineering: Environmental Engineering Course considering the latest technologies and regulatory frameworks. The Environmental Engineering: Environmental Engineering Course curriculum emphasizes practical skills, fostering a deep understanding of environmental science and engineering concepts. Enrol our Environmental Engineering: Environmental Engineering Course to contribute effectively to the development and implementation of sustainable solutions in this sector! Main Course: Level 7 Environmental Engineering Diploma Free Courses included with Environmental Engineering: Environmental Engineering Course: Along with Environmental Engineering Course you will get free Level 2 Certificate in Understanding Climate Change and Environmental Awareness Special Offers of this Environmental Engineering: Environmental Engineering Course: This Environmental Engineering: Environmental Engineering Course includes a FREE PDF Certificate. Lifetime access to this Environmental Engineering: Environmental Engineering Course Instant access to this Environmental Engineering: Environmental Engineering Course 24/7 Support Available to this Environmental Engineering: Environmental Engineering Course Environmental Engineering: Environmental Engineering Course Online Advanced environmental engineering principles are taught at a high level through the Environmental Engineering: Environmental Engineering Course. This Environmental Engineering: Environmental Engineering Course also includes control of air and water quality. The Environmental Engineering: Environmental Engineering Course also covers sustainable solutions and waste treatment. Students who complete this Environmental Engineering: Environmental Engineering Course will have the knowledge and practical abilities necessary to tackle challenging environmental issues. Who is this course for? Environmental Engineering: Environmental Engineering Course Online This Environmental Engineering: Environmental Engineering Course is appropriate for professionals in the engineering, architectural, or construction fields who want to increase their knowledge and abilities. Requirements Environmental Engineering: Environmental Engineering Course Online To enrol in this Environmental Engineering: Environmental Engineering Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Environmental Engineering: Environmental Engineering Course. Be energetic and self-motivated to complete our Environmental Engineering: Environmental Engineering Course. Basic computer Skill is required to complete our Environmental Engineering: Environmental Engineering Course. If you want to enrol in our Environmental Engineering Course, you must be at least 15 years old. Career path Environmental Engineering: Environmental Engineering Course Online Possessing this Environmental Engineering: Environmental Engineering Course knowledge can boost the appeal of your resume and make you more marketable to employers.

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Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Architects and operators who build and manage data analytics pipelines Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a batch data analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Introduction to Amazon EMR Using Amazon EMR in analytics solutions Amazon EMR cluster architecture Interactive Demo 1: Launching an Amazon EMR cluster Cost management strategies Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage Storage optimization with Amazon EMR Data ingestion techniques Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR Apache Spark on Amazon EMR use cases Why Apache Spark on Amazon EMR Spark concepts Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell Transformation, processing, and analytics Using notebooks with Amazon EMR Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive Using Amazon EMR with Hive to process batch data Transformation, processing, and analytics Practice Lab 2: Batch data processing using Amazon EMR with Hive Introduction to Apache HBase on Amazon EMR Module 5: Serverless Data Processing Serverless data processing, transformation, and analytics Using AWS Glue with Amazon EMR workloads Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions Module 6: Security and Monitoring of Amazon EMR Clusters Securing EMR clusters Interactive Demo 3: Client-side encryption with EMRFS Monitoring and troubleshooting Amazon EMR clusters Demo: Reviewing Apache Spark cluster history Module 7: Designing Batch Data Analytics Solutions Batch data analytics use cases Activity: Designing a batch data analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Duration 2 Days 12 CPD hours This course is intended for This course is ideal for beginners and intermediate frontend developers who want to become full-stack developers. You will need some prior working knowledge of JavaScript and MongoDB as we skim over its basics and get straight to work. Overview At the end of this day, students should be able to: Understand the MEAN architecture Create RESTful APIs to complete CRUD tasks Build a blogging application with basic features Describe best practices to secure node applications Implement authentication and authorization Create simple animations using Angular Perform unit testing on Angular applications MongoDB, Express, Angular and Node.js Fundamentals begins by demystifying the MEAN architecture. You will review the features of the JavaScript technologies, frameworks, or libraries that make up a MEAN stack. You will also understand how to develop a RESTful API using Node.js, Express.js, and MongoDB Atlas. This course will enable you to discover how to build a blogging application using the MEAN stack. Next, you will learn about authentication using MEAN, and explore the features of Angular, such as pipes, reactive forms, modules and optimizing apps, animations and unit testing, and much more. By the end of the course, you will have all of the knowledge you need to become a pro at developing efficient web applications using JavaScript technologies. Introduction to the MEAN stack MEAN Architecture Demystification Getting Started with Node Activity 1: Creating an HTTP Server for a Blogging Application Understanding Callbacks, Event loop and EventEmitters in Node Understanding Buffers, Streams and Filesystem in Node Activity 2: Streaming Data to a File Developing RESTful APIs to perform CRUD operations Getting Started with RESTful APIs Getting started with MongoDB Atlas Activity 3: Connecting the Node Application with MongoDB Atlas Getting Started with Express Activity 4: Creating Express API Route and Controller Activity 5: Testing Fully Functional RESTful API Beginning Frontend Development with Angular CLI Getting Started with Angular CLI Using Components, Directives, Services, and Making HTTP Requests in Angular Activity 6: Designing the Frontend and Components for the Blogging Application Activity 7: Writing Services and Making HTTP Request Calls to an API Understanding Angular Forms and Routing Activity 8: Creating a Form Application Using the Reactive/Model-Driven Method Activity 9: Creating and Validating Different Forms Using the Template and Reactive Driven Method Activity 10: Implementing a Router for the Blogging Application Understanding MEAN Stack Security Node Security and Best Practices Node Application Authentication with JSON Web Token (JWT) Activity 11: Securing the RESTful API Node Application Authentication with Passport Activity 12: Creating a Login Page to Allow Authentication with Twitter Using Passport Strategies Angular Declarables, Bootstrapping, and Modularity Using Inbuilt Pipes, Custom Pipes, Custom Directives, and Observables Activity 13: Communicating Between Two Components Using Observable Angular Bootstrapping and Modularity Activity 14: Creating a Lazy Loaded Application Testing and Optimizing Angular Applications Angular Animations and Latest Angular Features Activity 15: Animating the Route Transition Between the Blog Post Page and View Post Page of the Blogging Application Optimizing Angular Applications Testing Angular Applications Activity 16: Performing Unit Testing on the App Root Component and Blog-Post Component Overview on the new features in Angular

Duration 4 Days 24 CPD hours This course is intended for Data Modelers Overview Please refer to course overview This offering provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the web, enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Framework Manager Model data and identifying related data Define requirements and modeling strategies Overview of IBM Cognos Framework Manager Create a baseline project Extend a model Prepare reusable metadata Model for predictable results in IBM Cognos Framework Manager Identify query issues Identify reporting traps Model virtual star schemas Use query subjects, modify relationships, and consolidate metadata using virtual objects Create calculations, filter data, and customize metadata for runtime Implement a time dimension and specify determinants Model for presentation in IBM Cognos Framework Manager Create a presentation view Examine data source query subject types and stored procedure query subject types Specify data security and package security Specify object security and dynamic data security Create analysis objects Manage OLAP data sources Advanced capabilities in IBM Cognos Framework Manager Explore SQL generation and the use of governors Examine the use of IBM Cognos SQL and generated SQL for DMR data Other query considerations Use session parameters, prompt macros, and security macro functions Use materialized views, minimize SQL, and enable Dynamic Query Mode (DQM) DQM, CQM, caching metadata, query processing, aggregate calculation, and other ways to improve performance Extended capabilities in IBM Cognos Framework Manager (Optional) Perform basic maintenance and management on a model Remap metadata to another source and import and link additional data sources Run scripts to automate or update a model and report on a model Segment a project, link a project, and branch a model Nest packages and specify package languages and functions Explore additional modeling techniques and customize metadata for a multilingual audience Additional course details: Nexus Humans B6152 IBM Cognos Framework Manager - Design Metadata Models v11.0.x 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 B6152 IBM Cognos Framework Manager - Design Metadata Models v11.0.x 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: Solutions architects and cloud architects seeking their AWS Certified Solutions Architect - Associate certification Customers and APN Partners who have 6 to 12 months of experience with AWS including a strong architecture background and experience Individuals who prefer an instructor led course for training and exam readiness Individuals who have not taken the Architecting on AWS course in the last ~6 months Overview In this course, you will learn to: Make architectural decisions based on AWS architectural principles and best practices Leverage AWS services to make your infrastructure scalable, reliable, and highly available Leverage AWS Managed Services to enable greater flexibility and resiliency in an infrastructure Make an AWS-based infrastructure more efficient to increase performance and reduce costs Use the Well-Architected Framework to improve architectures with AWS solutions Navigate the logistics of the examination process, exam structure, and question types Identify how questions relate to AWS architectural concepts Interpret the concepts being tested by an exam question This five-day, instructor-led course helps busy architects get away from the day-to-day to get focused and ready for their AWS Certified Solutions Architect ? Associate exam. Attendees learn the fundamentals of building IT infrastructure on AWS, so they can build scalable and resilient solutions in the cloud, by spending the first 3 days on the Architecting on AWS course. They?ll start getting in the exam readiness mindset with bonus end of module quizzes. Next, they?ll learn strategies to answer exam questions and avoid common mistakes with the Exam Readiness: AWS Certified Solutions Architect ? Associate half-day course. The course broadens attendees? knowledge of AWS services with deep dives into Amazon Redshift, Amazon Kinesis, and AWS Key Management Service, and then concludes with two quizzes and an instructor guided review of the AWS Certified Solutions Architect ? Associate practice exam. Architecting on AWS Module 1: Introduction Module 2: The Simplest Architectures Hands-On Lab 1: Hosting a Static Website Module 3: Adding a Compute Layer Module 4: Adding a Database Layer Hands-On Lab 2: Deploying a Web Application on AWS Module 5: Networking in AWS Part 1 Hands-On Lab 3: Creating a Virtual Private Cloud Architecting on AWS (continued) Module 6: Networking in AWS Part 2 Module 7: AWS Identity and Access Management (IAM) Module 8: Elasticity, High Availability, and Monitoring Hands-On Lab 4: Creating a Highly Available Environment Module 9: Automation Hands-On Lab 5: Automating Infrastructure Deployment with AWS CloudFormation Module 10: Caching Architecting on AWS (continued) Module 11: Building Decoupled Architectures Module 12: Microservices and Serverless Architectures Hands-On Lab 6: Implementing a Serverless Architecture with AWS Managed Services Module 13: RTP/RPO and Backup Recovery Setup Module 14: Optimizations and Review Exam Readiness: AWS Certified Solutions Architect -- Associate Module 0: The Exam Module 1: Design Resilient Architectures Module 2: Design Performant Architectures Module 3: Specify Secure Applications and Architectures Module 4: Design Cost-Optimized Architectures Module 5: Define Operationally Excellent Architectures Exam Readiness Additional deep dive of AWS services Quiz #1 Practice exam: AWS Certified Solutions Architect ? Associate Quiz #2 Wrap-up

Duration 4 Days 24 CPD hours This course is intended for Data Modelers Overview Please refer to course overview This offering provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using IBM Cognos Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the web, enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Framework Manager Model data and identifying related data Define requirements and modeling strategies Overview of IBM Cognos Framework Manager Create a baseline project Extend a model Prepare reusable metadata Model for predictable results in IBM Cognos Framework Manager Identify query issues Identify reporting traps Model virtual star schemas Use query subjects, modify relationships, and consolidate metadata using virtual objects Create calculations, filter data, and customize metadata for runtime Implement a time dimension and specify determinants Model for presentation in IBM Cognos Framework Manager Create a presentation view Examine data source query subject types and stored procedure query subject types Specify data security and package security Specify object security and dynamic data security Create analysis objects Manage OLAP data sources Advanced capabilities in IBM Cognos Framework Manager Explore SQL generation and the use of governors Examine the use of IBM Cognos SQL and generated SQL for DMR data Other query considerations Use session parameters, prompt macros, and security macro functions Use materialized views, minimize SQL, and enable Dynamic Query Mode (DQM) DQM, CQM, caching metadata, query processing, aggregate calculation, and other ways to improve performance Extended capabilities in IBM Cognos Framework Manager Perform basic maintenance and management on a model Remap metadata to another source and import and link additional data sources Run scripts to automate or update a model and report on a model Segment a project, link a project, and branch a model Nest packages and specify package languages and functions Explore additional modeling techniques and customize metadata for a multilingual audience Additional course details: Nexus Humans B6252 IBM Cognos Framework Manager: Design Metadata Models v11.1.x 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 B6252 IBM Cognos Framework Manager: Design Metadata Models v11.1.x 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.

The main subject areas of the course are: health effects of exposure to asbestos fibres types of asbestos and uses of asbestos in buildings types of asbestos surveys conducting safe and effective asbestos surveys bulk sampling risk assessing and managing asbestos-containing materials personal protection and decontamination

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Database architects Database administrators Database developers Data analysts and scientists Overview This course is designed to teach you how to: Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution Architect the data warehouse Identify performance issues, optimize queries, and tune the database for better performance Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data Module 1: Introduction to Data Warehousing Relational databases Data warehousing concepts The intersection of data warehousing and big data Overview of data management in AWS Hands-on lab 1: Introduction to Amazon Redshift Module 2: Introduction to Amazon Redshift Conceptual overview Real-world use cases Hands-on lab 2: Launching an Amazon Redshift cluster Module 3: Launching clusters Building the cluster Connecting to the cluster Controlling access Database security Load data Hands-on lab 3: Optimizing database schemas Module 4: Designing the database schema Schemas and data types Columnar compression Data distribution styles Data sorting methods Module 5: Identifying data sources Data sources overview Amazon S3 Amazon DynamoDB Amazon EMR Amazon Kinesis Data Firehose AWS Lambda Database Loader for Amazon Redshift Hands-on lab 4: Loading real-time data into an Amazon Redshift database Module 6: Loading data Preparing Data Loading data using COPY Data Warehousing on AWS AWS Classroom Training Concurrent write operations Troubleshooting load issues Hands-on lab 5: Loading data with the COPY command Module 7: Writing queries and tuning for performance Amazon Redshift SQL User-Defined Functions (UDFs) Factors that affect query performance The EXPLAIN command and query plans Workload Management (WLM) Hands-on lab 6: Configuring workload management Module 8: Amazon Redshift Spectrum Amazon Redshift Spectrum Configuring data for Amazon Redshift Spectrum Amazon Redshift Spectrum Queries Hands-on lab 7: Using Amazon Redshift Spectrum Module 9: Maintaining clusters Audit logging Performance monitoring Events and notifications Lab 8: Auditing and monitoring clusters Resizing clusters Backing up and restoring clusters Resource tagging and limits and constraints Hands-on lab 9: Backing up, restoring and resizing clusters Module 10: Analyzing and visualizing data Power of visualizations Building dashboards Amazon QuickSight editions and feature