382 Sciences courses in Cardiff 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 3 Days 18 CPD hours This course is intended for Organizations today demand a professional-level cybersecurity threat intelligence analyst who can extract the intelligence from data by implementing various advanced strategies. Such professional-level programs can only be achieved when the core of the curricula maps with and is compliant to government and industry published threat intelligence frameworks. Ethical Hackers Security Practitioners, Engineers, Analysts, Specialist, Architects, and Managers Threat Intelligence Analysts, Associates, Researchers, Consultants Threat Hunters SOC Professionals Digital Forensic and Malware Analysts Incident Response Team Members Any mid-level to high-level cybersecurity professionals with a minimum of 2 years of experience. Individuals from the information security profession and who want to enrich their skills and knowledge in the field of cyber threat intelligence. Individuals interested in preventing cyber threats. Overview This program will benefit students who are looking to build effective threat intelligence for their organization in order to combat modern-day cyber-attacks and prevent future attacks. Certified Threat Intelligence Analyst (C|TIA) is designed and developed in collaboration with cybersecurity and threat intelligence experts across the globe to help organizations identify and mitigate business risks by converting unknown internal and external threats into known threats. It is a comprehensive, specialist-level program that teaches a structured approach for building effective threat intelligence. Introduction to Threat Intelligence Understanding Intelligence Understanding Cyber Threat Intelligence Overview of Threat Intelligence Lifecycle and Frameworks Cyber Threats and Kill Chain Methodology Understanding Cyber Threats Understanding Advanced Persistent Threats (APTs) Understanding Cyber Kill Chain Understanding Indicators of Compromise (IoCs) Requirements, Planning, Direction, and Review Understanding Organization?s Current Threat Landscape Understanding Requirements Analysis Planning Threat Intelligence Program Establishing Management Support Building a Threat Intelligence Team Overview of Threat Intelligence Sharing Reviewing Threat Intelligence Program Data Collection and Processing Overview of Threat Intelligence Data Collection Overview of Threat Intelligence Collection Management Overview of Threat Intelligence Feeds and Sources Understanding Threat Intelligence Data Collection and Acquisition Understanding Bulk Data Collection Understanding Data Processing and Exploitation Data Analysis Overview of Data Analysis Understanding Data Analysis Techniques Overview of Threat Analysis Understanding Threat Analysis Process Overview of Fine-Tuning Threat Analysis Understanding Threat Intelligence Evaluation Creating Runbooks and Knowledge Base Overview of Threat Intelligence Tools Intelligence Reporting and Dissemination Overview of Threat Intelligence Reports Introduction to Dissemination Participating in Sharing Relationships Overview of Sharing Threat Intelligence Overview of Delivery Mechanisms Understanding Threat Intelligence Sharing Platforms Overview of Intelligence Sharing Acts and Regulations Overview of Threat Intelligence Integration

Duration 5 Days 30 CPD hours This course is intended for Network security engineers Network security architects ISE administrators Senior Security Operations Center (SOC) personnel responsible for Incidence Response Cisco integrators and partners Overview After taking this course, you should be able to: Describe the Cisco Identity Services Engine (ISE) Explain Cisco ISE deployment Describe Cisco ISE policy enforcement components Describe Cisco ISE policy configuration Troubleshoot Cisco ISE policy and third-party Network Access Device (NAD) support Configure guest access Configure hotspots and guest portals Describe the Cisco ISE profiler services Describe profiling best practices and reporting Configure a Cisco ISE BYOD solution Configure endpoint compliance Configure client posture services Configure Cisco ISE device administration Describe Cisco ISE TrustSec configurations The Implementing and Configuring Cisco Identity Services Engine (SISE) v4.0 course teaches you to deploy and use Cisco© Identity Services Engine (ISE) v3.x, an identity and access control policy platform that simplifies the delivery of consistent, highly secure access control across wired, wireless, and VPN connections. This hands-on course provides you with the knowledge and skills to implement and apply Cisco ISE capabilities to support use cases for Zero Trust security posture. These use cases include tasks such as policy enforcement, profiling services, web authentication and guest access services, BYOD, endpoint compliance services, and Terminal Access Controller Access Control Server (TACACS+) device administration. Through hands-on practice via lab exercises, you will learn how to use Cisco ISE to gain visibility into what is happening in your network, streamline security policy management, and contribute to operational efficiency. This course helps you prepare to take the Implementing and Configuring Cisco Identity Services Engine (300-715 SISE) exam, which leads to CCNP© Security and the Cisco Certified Specialist - Security Identity Management Implementation certifications. This course also earns you 40 Continuing Education (CE) credits toward recertification Course Outline Introducing Cisco ISE Architecture Introducing Cisco ISE Deployment Introducing Cisco ISE Policy Enforcement Components Introducing Cisco ISE Policy Configuration Troubleshooting Cisco ISE Policy and Third-Party NAD Support Introducing Web Authentication and Guest Services Configuring Hotspots and Guest Portals Introducing the Cisco ISE Profiler Introducing Profiling Best Practices and Reporting Configuring Cisco ISE BYOD Introducing Cisco ISE Endpoint Compliance Services Configuring Client Posture Services and Compliance Working With Network Access Devices Exploring Cisco TrustSec Additional course details: Nexus Humans Cisco Implementing and Configuring Cisco Identity Services Engine v4.0 (SISE) 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 Cisco Implementing and Configuring Cisco Identity Services Engine v4.0 (SISE) 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.

Overview Explore trading and hedging applications of barrier options across interest rate, FX, and equity markets. Who the course is for Executives of listed companies who want to enhance their knowledge and skills in ESG and sustainability. Corporate professionals who want to integrate ESG initiatives into their organizations and improve their ESG programs. ESG professionals who want to gain a deep understanding of ESG frameworks, reporting standards, and best practices Course Content To learn more about the day by day course content please request a brochure To learn more about schedule, pricing & delivery options, book a meeting with a course specialist now

Duration 2 Days 12 CPD hours This course is intended for New users of IBM SPSS Statistics Users who want to refresh their knowledge about IBM SPSS Statistics Anyone who is considering purchasing IBM SPSS Statistics Overview Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders This course guides students through the fundamentals of using IBM SPSS Statistics for typical data analysis. Students will learn the basics of reading data, data definition, data modification, data analysis, and presentation of analytical results. In addition to the fundamentals, students will learn shortcuts that will help them save time. This course uses the IBM SPSS Statistics Base; one section presents an add-on module, IBM SPSS Custom Tables. Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders Additional course details: Nexus Humans 0G53BG IBM SPSS Statistics Essentials (V26) 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 0G53BG IBM SPSS Statistics Essentials (V26) 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 content is appropriate for test automation engineering roles, test manager roles, test lead roles, test architect roles, as well as developer roles. This course assumes you have a foundational understanding of testing and the purpose of automation. This course will be beneficial to anyone who is accountable for assessing, planning, designing, and implementing an integrated set of technology (testing infrastructure) that supports development, testing, and deployment. Overview Working in an interactive learning environment, led by our expert facilitator, attendees will learn to: Document the current state of test automation in your organization Define a custom test automation plan and architecture to fit their situation Create an initial implementation plan Identify initial key measures Develop a metrics dashboard for tracking the value of test automation Lay out a future strategy and roadmap to get there Introduction to Test Automation is a one-day, hands-on event designed to provide participants with the skills required to develop a custom test automation plan and architecture for their organization. Throughout the course, students will examine and work through various practical examples, learning how to create an integrated test automation plan and develop a test automation architecture. Participants will also learn about the possible real-world challenges they may face while trying to accomplish their goals, exploring the practical positive aspects of engaging their technical team, along with the possible frustrations of experiencing too much isolation between test automators and test designers. Getting Started Automation beginnings Software as a series of imperfect translations The Compelling Business Needs for Automation Automation the next opportunity Islands of Automation Getting products to market more quickly, at the right costs and quality Automation Challenges and Requirements Automation Challenges Test Automation Key Requirements Foundational material for your automation plan Templates Questions Examples Virtual Consulting included with this course Automation plan vision and strategy Vision, Strategy, Approach Example Defining your end in mind Deciding where to start Engaging Others Conducting a current state tools inventory Assessing your current state - tools and processes Tools inventory example and template Radar Chart as a means of presenting current state information Consider the best automation approach Waterfall vs. agile cycles of work Aligning tools with your methodologies Strategies for Automating The Test Automation Pyramid Developing your test automation architecture Blocks of automation capabilities Islands of Automation Integrated Tools Architecture Template Integrated Tools Architecture Examples Test automation architecture examples Examples of different test automation architectures and frameworks Selenium Key Test Automation Architecture Characteristics Acceptance test-driven and behavior-driven testing overview Test automation approaches FitNesse Cucumber Gherkin script overview Tool workflow Considerations for what to automate and when Categories of tests that might be automated We have many tool choices Key points in Test Tool Architecture Planning Piloting and Implementing automation Selecting and evaluating tools and rolling them out Selling Automation - qualitative questions Selling Automation - quantitative questions Measuring automation benefits Measures in technical terms Measures in business terms Measures of testing vs. measures of test automation Next Steps A few keys to success

Duration 2 Days 12 CPD hours This course is intended for This course is designed for the Business Analyst professional who is involved with testing the functionality of technology projects. Overview Develop an understanding about basic concepts associated with User Acceptance TestingSee how UAT applies to the Software Development Lifecycle (SDLC)Recognize benefits of improved quality of deployed software using User Acceptance TestingIdentify the key roles, activities and deliverables which make up User Acceptance Testing Use a Business Use Case to define scenarios for testingCreate a UAT test plan and write UAT test cases with associated test dataUnderstand the process for testing functional and non-functional requirementsIdentify the challenges of testing vendor-supplied applications This course looks at the issues which drive the need for a UAT process & describes the components of the process. It is designed to help Business Analysts to develop an understanding of their role, the process, and the deliverables associated with UAT. Day 1 Software Testing - the Basics Understanding the Tester?s Terminology The UAT Planning Process Day 2 UAT Test Coverage Creating & Executing the UAT Test Cases Verifying the Test Results Testing Vendor-Supplied Applications Additional course details: Nexus Humans BA29 - User Acceptance Testing for Business Analysts 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 BA29 - User Acceptance Testing for Business Analysts 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 suited to marketeers, business analysts, and researchers who are interested in increasing their statistical knowledge. Overview After attending this course, delegates will understand how statistics can be used to provide valuable insight into their business, and be able to apply statistical methods to solve business problems. On returning to work delegates will immediately be able to make a difference to the way that their organisations make decisions. This course covers the statistical methods that analysts need to move from simple reporting on business problems to extracting insight to solve business problems. Course Outline The course will explore the following topics through a series of lectures and workshops: Summary statistics for both continuous data and categorical data Using and reporting confidence intervals Using hypothesis tests to answer business questions Using correlations to explore data relationships Simple prediction models Analysing categorical data Additional course details: Nexus Humans Data-driven Business Using Statistical Analysis 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 Data-driven Business Using Statistical Analysis 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.

About UX Academy: UX Academy provides live online hands-on training to help you take the next step in your career no matter what level you’re at. Offering Beginner, Intermediate UX courses, Product Design, Strategy and Voice Design developed in collaboration with Amazon.

Artificial Intelligence brings exciting new opportunities to the field of Conversational User Interfaces (CUI). Learn key concepts and proven design methods to deliver cutting-edge experiences and reach better business outcomes. Silvia Podesta is a Designer in the Client Engineering Team at IBM Nordics. She leverages design thinking, service and UX design to help clients identify opportunities for innovation and pioneer transformational experiences through IBM technology.