3153 Design courses in Garforth delivered Live Online

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 Participants who have actual experience in the data centre and/or IT infrastructures are best suited. Attendance of the CDCP© course is recommended but not a requirement. Overview After completion of the course the participant will be able to: 1. Develop and review their data centre strategy 2. Use different risk assessment methodologies together with practical tips specifically for data centre migrations to reduce the risk during a data centre migration 3. Understand different migration strategies 4. Understand the legal aspects when migrating a data centre 5. Understand the importance of Business Service Reviews and Service Level Objectives 6. Size and design the target data centre 7. Understand the importance of detailed discovery and how dependencies influence migration waves 8. Understand the safety requirements during migration 19. Get lots of practical tips when moving to another data centre This course is designed to expose participants to a step-by-step methodology which will enable them to reduce the risks involved when undertaking a data centre migration. It will also give participants a lot of valuable practical hints and tips by trainers having extensive experience in moving and consolidating mission critical data centre. Data Centre Strategy Data centre lifecycle Reasons to migrate a data centre Alternatives to data centre migration Consolidation Outsourcing Cloud computing Upgrade existing data centre or build new Project Management Project management and methods Scope statement Statement Of Work (SOW) Work Breakdown Structure (WBS) Allocate time to the project Cost and estimation methodology Project communication Risk Management Risk management and methods Risk identification Risk assessment methodologies Qualitative approach Semi-quantitative approach Quantitative approach Risk evaluation Risk treatment Risk in data centre migrations Migration Strategies Different data centre migration strategies Heterogeneous migration Homogeneous migration Physical migration Different IT transformations Pre-migration transformation Migration transformation Post-migration transformation Legal Aspects Regulatory requirements Contractual considerations Legal aspects when decommissioning High Level Discovery & Planning The importance of Business Service Reviews The concept of Availability The concept of Recoverability The importance of Service Level Objectives Requirements on designing the target IT architecture Information needed for high level planning Design Target Data Centre Requirements for the target data centre Sizing the data centre Architectural requirements Cooling requirements Power requirements Security Detailed Discovery and Planning The importance of discovery Automated discovery tools Asset management Network and system dependencies Detailed migration planning Migration waves Staffing Warranties and insurance Safety Safety precautions Technical safety review Electrical safety Lifting Personal safety during migration Fire safety during migration Security Controversy between access and security Access control Managing security during migration Security during migration Key management Practical hints and tips Continuous improvement Implementation Rehearsal Route investigation Resourcing Logistics team Packing Transport Installing the equipment Post migration support End of Project Why project closure Lessons learned Phased completion of project Criteria for project closure The outcome of the project End of project Exam: Certified Data Centre Migration Specialist Actual course outline may vary depending on offering center. Contact your sales representative for more information.

Project Stakeholder Relationship Skills: In-House Training This course is designed to provide project managers with the ability to: Analyze the complexities of major stakeholder relationship categories Apply the most appropriate interpersonal relationship skills to the different categories of relationships Align the dynamic needs of the stakeholders with a project's objective throughout the project life cycle What you Will Learn Examine traditional and non-traditional ways to identify and assess stakeholders Explain how competence, character, and trust lead to project success and strong relationships with stakeholders Utilize 'Embodied Leadership' skills to build stakeholder relationships Apply stakeholder engagement best practices to case study and real-life scenarios Getting Started Stakeholders and project success Stakeholder management research Managing stakeholder relationships Identifying Stakeholders Stakeholder categories Stakeholder relationships across the project life cycle Tools and techniques for identifying stakeholders Assessing Stakeholders Assessing stakeholder relationships Recognizing stakeholder attitudes toward the project Analyzing stakeholders Using other types of stakeholder assessments Building Stakeholder Relationships The importance of psychological safety Building trust and getting results The anatomy of trust Navigating Challenging Situations Dynamics of conflict Responding to conflict Managing difficult conversations

Course Overview: This course provides a comprehensive introduction to the field of renewable energy, focusing on solar energy systems. Learners will explore the fundamentals of solar power, including system components, design, and application. With a practical approach, the course offers insights into both off-grid and on-grid systems, solar water pumping, and system protection. The course equips learners with essential skills for designing and optimising photovoltaic (PV) systems using industry-standard software like PVSyst, MATLAB, and ETAP. Upon completion, participants will be able to contribute to renewable energy projects, enhance their career prospects in the solar energy sector, and implement solar systems with a deeper understanding of the technological and environmental impacts. Course Description: This course delves into the key aspects of solar energy systems, offering a clear overview of essential topics such as solar panel components, battery storage, system design, and optimisation. Learners will gain in-depth knowledge of off-grid and on-grid solar energy systems, solar water pumping, and system protection. The course incorporates theoretical knowledge and system design techniques using industry-standard tools, including PVSyst, MATLAB, and ETAP. Additionally, students will learn how to design and simulate PV systems, as well as the design of system diagrams using Excel. By the end of this course, learners will have acquired the skills to confidently design and optimise solar energy systems for a range of applications, contributing to the growing renewable energy sector and ensuring sustainable energy solutions. Course Modules: Module 01: Basics of Solar Energy System Module 02: Batteries in PV System Module 03: Components and Design of Off Grid Solar Energy System Module 04: Designing of ON Grid Solar Energy System Module 05: Design of PV System Using PVSyst Programme Module 06: Solar Water Pumping System Module 07: Protection of PV System Module 08: Design Using Excel Sheet Module 09: Single Line Diagram of PV System Module 10: MATLAB and ETAP PV Simulation (See full curriculum) Who is this course for? Individuals seeking to enter the renewable energy sector. Professionals aiming to develop expertise in solar energy system design. Beginners with an interest in sustainable energy solutions. Engineers or technicians looking to broaden their knowledge of solar energy applications. Career Path Solar Energy System Designer Renewable Energy Consultant Solar Power Technician Project Manager in Renewable Energy Energy Analyst Sustainability Specialist

Immerse yourself in the ancient practice of yoga, a transformative journey that extends far beyond the mere physical postures. Our comprehensive yoga sessions are meticulously curated and led by seasoned professionals, offering a serene sanctuary tailored for the demands of modern-day professionals yearning for holistic balance and wellness. Delve into innate human abilities such as intuition, telepathy, clairvoyance, lucid dreaming, and energy healing. Uncover these dormant gifts existing within and enjoy awakening them fully.

Duration 1 Days 6 CPD hours This course is intended for The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don?t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful. This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. Prerequisites Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services. Specifically: Experience using computers and the internet. Interest in use cases for AI applications and machine learning models. A willingness to learn through hands-on exp... 1 - Fundamental AI Concepts Understand machine learning Understand computer vision Understand natural language processing Understand document intelligence and knowledge mining Understand generative AI Challenges and risks with AI Understand Responsible AI 2 - Fundamentals of machine learning What is machine learning? Types of machine learning Regression Binary classification Multiclass classification Clustering Deep learning Azure Machine Learning 3 - Fundamentals of Azure AI services AI services on the Azure platform Create Azure AI service resources Use Azure AI services Understand authentication for Azure AI services 4 - Fundamentals of Computer Vision Images and image processing Machine learning for computer vision Azure AI Vision 5 - Fundamentals of Facial Recognition Understand Face analysis Get started with Face analysis on Azure 6 - Fundamentals of optical character recognition Get started with Vision Studio on Azure 7 - Fundamentals of Text Analysis with the Language Service Understand Text Analytics Get started with text analysis 8 - Fundamentals of question answering with the Language Service Understand question answering Get started with the Language service and Azure Bot Service 9 - Fundamentals of conversational language understanding Describe conversational language understanding Get started with conversational language understanding in Azure 10 - Fundamentals of Azure AI Speech Understand speech recognition and synthesis Get started with speech on Azure 11 - Fundamentals of Azure AI Document Intelligence Explore capabilities of document intelligence Get started with receipt analysis on Azure 12 - Fundamentals of Knowledge Mining with Azure Cognitive Search What is Azure Cognitive Search? Identify elements of a search solution Use a skillset to define an enrichment pipeline Understand indexes Use an indexer to build an index Persist enriched data in a knowledge store Create an index in the Azure portal Query data in an Azure Cognitive Search index 13 - Fundamentals of Generative AI What is generative AI? Large language models What is Azure OpenAI? What are copilots? Improve generative AI responses with prompt engineering 14 - Fundamentals of Azure OpenAI Service What is generative AI Describe Azure OpenAI How to use Azure OpenAI Understand OpenAI's natural language capabilities Understand OpenAI code generation capabilities Understand OpenAI's image generation capabilities Describe Azure OpenAI's access and responsible AI policies 15 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution Additional course details: Nexus Humans AI-900T00 - Microsoft Azure AI Fundamentals 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 AI-900T00 - Microsoft Azure AI Fundamentals 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 This course is primarily for Developers, Developer Consultants, Help Desk/COE Support, Program/Project Manager, System Administrators, System Architects, and Technology Consultants. Overview Explaining scenarios and processes in SAP NetWeaver process integrationIdentify the technical communications modes and processesExplain business scenarios and the business hierarchy used by SAP In this course, students learn how to explain scenarios & processes in SAP NetWeaver process integration. They learn how to identify the technical communications modes & processes, as well as explain business scenarios & the business hierarchy used by SAP. Integration Basics Explaining Scenarios and Processes in SAP NetWeaver Process Integration Explaining Technical Communication Modes and Processes Explaining Business Scenarios Classical System-to-System Communication Communicating Between Two SAP Systems Communicating Between Two Non-SAP Systems Communicating Using Business Application Programming Interfaces (BAPIs) Communicating Using IDocs Processing IDocs Web Services Processing HTTP Requests Describing Simple Object Access Protocol (SOAP) Basics Analyzing Different Web Services Describing Inside-Out and Outside-In Web Services Explaining Service Oriented Architecture (SOA) Integration Technologies: On-Premise Process Integration (Design Time) Processing Integration Middleware Tools (PI Dual Stack) Installing Dual-Stack or Single-Stack Options Securing Objects Creating PI Objects Explaining Design Objects Modeling PI Scenarios Creating an Integration Scenario Configuring an Integration Scenario Displaying the Configuration Objects in the Integration Directory Integration Technologies: On-Premise Process Integration (Runtime) Connecting SAP NetWeaver PI with Proxies Creating File Adapters Executing Configuration Objects Monitoring Tools Integration Technologies: On-Premise Process Orchestration (PO) Explaining Business Process Management (BPM) Explaining Process Orchestration (PO) Explaining Advanced Adapter Engine Extended (AEX) Explaining Business Rules Management (BRM) Integration Technologies: On Demand Explaining SAP HANA Cloud Integration (HCI) Describing Eclipse-Based Access Using the Web UI to Access HCI SAP NetWeaver Gateway Explaining the SAP NetWeaver Gateway Scenario Explaining the SAP NetWeaver Gateway Development View Accessing an Open Data (OData) Service Additional course details: Nexus Humans BIT100 SAP NetWeaver Integration Technology Overview 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 BIT100 SAP NetWeaver Integration Technology Overview 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 1 Days 6 CPD hours This course is intended for The Power BI in a Day course is designed for beginners and intermediate users of Power BI. Overview #NAME? Students will discover the full capabilities of Power BI in a one-day, hands-on workshop. Please Note: This workshop is primarily self-directed and students will work at their own pace while having access to an instructor for questions. 1 - Accessing & Preparing data Data Set Power BI Desktop Power BI Desktop ? Accessing Data Power BI Desktop ? Data Preparation 2 - Data Modeling and Exploration Power BI Desktop ? Data Modeling and Exploration Power BI Desktop ? Data Exploration Continued References 3 - Data Visualization Power BI Desktop Power BI Desktop ? Data Visualization References 4 - Publishing & Accessing Reports Power BI Desktop ? Creating Mobile View Power BI Service Power BI Service ? Publishing Report Power BI Mobile ? Accessing Report on Mobile Device Power BI Service ? Collaboration and Distribution References 5 - Dashboard and Collaboration Power BI Service Building Dashboard References Additional course details: Nexus Humans Power BI: Dashboard in a Day 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 Power BI: Dashboard in a Day 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 1 Days 6 CPD hours This course is intended for The primary audience for this course is data professionals who are familiar with data modeling, extraction, and analytics. It is designed for professionals who are interested in gaining knowledge about Lakehouse architecture, the Microsoft Fabric platform, and how to enable end-to-end analytics using these technologies. Job role: Data Analyst, Data Engineer, Data Scientist Overview Describe end-to-end analytics in Microsoft Fabric Describe core features and capabilities of lakehouses in Microsoft Fabric Create a lakehouse Ingest data into files and tables in a lakehouse Query lakehouse tables with SQL Configure Spark in a Microsoft Fabric workspace Identify suitable scenarios for Spark notebooks and Spark jobs Use Spark dataframes to analyze and transform data Use Spark SQL to query data in tables and views Visualize data in a Spark notebook Understand Delta Lake and delta tables in Microsoft Fabric Create and manage delta tables using Spark Use Spark to query and transform data in delta tables Use delta tables with Spark structured streaming Describe Dataflow (Gen2) capabilities in Microsoft Fabric Create Dataflow (Gen2) solutions to ingest and transform data Include a Dataflow (Gen2) in a pipeline This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric. Introduction to end-to-end analytics using Microsoft Fabric Explore end-to-end analytics with Microsoft Fabric Data teams and Microsoft Fabric Enable and use Microsoft Fabric Knowledge Check Get started with lakehouses in Microsoft Fabric Explore the Microsoft Fabric Lakehouse Work with Microsoft Fabric Lakehouses Exercise - Create and ingest data with a Microsoft Fabric Lakehouse Use Apache Spark in Microsoft Fabric Prepare to use Apache Spark Run Spark code Work with data in a Spark dataframe Work with data using Spark SQL Visualize data in a Spark notebook Exercise - Analyze data with Apache Spark Work with Delta Lake Tables in Microsoft Fabric Understand Delta Lake Create delta tables Work with delta tables in Spark Use delta tables with streaming data Exercise - Use delta tables in Apache Spark Ingest Data with DataFlows Gen2 in Microsoft Fabric Understand Dataflows (Gen2) in Microsoft Fabric Explore Dataflows (Gen2) in Microsoft Fabric Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric Exercise - Create and use a Dataflow (Gen2) in Microsoft Fabric

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