1297 Scientist courses in Cardiff delivered Online

Information on the risks and practical advice to address them TSC's eBooks, whitepapers, and reports cover some of the most important risks in information and cyber security — risks that constantly challenge information and cyber security professionals who work tirelessly to reduce them across their organisations and home users alike.

Information on the risks and practical advice to address them TSC's eBooks, whitepapers, and reports cover some of the most important risks in information and cyber security — risks that constantly challenge information and cyber security professionals who work tirelessly to reduce them across their organisations and home users alike.

About Course Breathe Easy: Mastering Air Pollution Control for a Sustainable Future Understand the Science of air pollution and how to mitigate its impact on climate change and human health with this Course. Dive into emission sources, control technologies, and Air quality management strategies with this Air Pollution Control Online Course. Learning Outcomes/Course Objectives: Grasp the science and consequences of air pollution. Understand the link between air pollution and climate change, its diverse sources, and its detrimental effects on public health. Master air pollution control tools and techniques. Explore efficient control technologies for particulate matter, greenhouse gases, and other pollutants, evaluating their effectiveness and applications. Strategize and implement air quality management plans. Learn sustainable air pollution control strategies, monitoring techniques, and regulatory frameworks for efficient air quality management. Champion change through public engagement and advocacy. Develop the skills to communicate air pollution risks, engage the public, and advocate for effective policies and regulations. Stay informed on emerging issues. Explore cutting-edge solutions and address future challenges in air pollution control, paving the way for a cleaner future. Target Audience: Environmental professionals: Air quality engineers, policymakers, sustainability consultants, and environmental scientists seeking to advance their knowledge and skills in air pollution mitigation. Public health professionals: Medical practitioners, public health advocates, and healthcare workers interested in understanding the health impacts of air pollution and promoting prevention strategies. Concerned citizens and students: Individuals passionate about environmental issues and climate change who seek actionable knowledge to advocate for cleaner air and a sustainable future. Anyone eager to understand and address the challenges of air pollution: This course empowers individuals from diverse backgrounds to contribute to solutions and advocate for a healthier planet. Requirements: Curiosity and passion for environmental sustainability. A genuine interest in understanding and addressing air pollution issues is key to unlocking the potential of this course. Basic understanding of scientific concepts. Familiarity with fundamental science principles will enhance your comprehension of the complex science behind air pollution. Openness to diverse perspectives. Embrace a commitment to learning from various viewpoints and perspectives to contribute to effective air quality management solutions. Enroll today and take a deep breath of confidence. This comprehensive Air Pollution Control Online Course equips you with the knowledge and skills to control air pollution. Lets take the next step in protecting our planet and its inhabitants for generations to come. What Will You Learn? Grasp the science and consequences of air pollution Master air pollution control tools and techniques Strategize and implement air quality management plans Champion change through public engagement and advocacy Stay informed on emerging issues Course Content Introduction to Air Pollution Control Introduction to Air Pollution Control Emission Sources and Control Technologies Emission Sources and Control Technologies Air Pollution Control Strategies and Techniques Air Pollution Control Strategies and Techniques Air Pollution Monitoring and Management Air Pollution Monitoring and Management Emerging Issues in Air Pollution Control Emerging Issues in Air Pollution Control Public Engagement and Policy Advocacy Public Engagement and Policy Advocacy Conclusion Conclusion A course by Xpert Learning RequirementsBasic understanding of scientific concepts: Familiarity with fundamental science principles will enhance your comprehension of the complex science behind air pollution. Audience Environmental professionals: Air quality engineers, policymakers, sustainability consultants, and environmental scientists seeking to advance their knowledge and skills in air pollution mitigation. Public health professionals: Medical practitioners, public health advocates, and healthcare workers interested in understanding the health impacts of air pollution and promoting prevention strategies. Concerned citizens and students: Individuals passionate about environmental issues and climate change who seek actionable knowledge to advocate for cleaner air and a sustainable future. Anyone eager to understand and address the challenges of air pollution: This course empowers individuals from diverse backgrounds to contribute to solutions and advocate for a healthier planet. Audience Environmental professionals: Air quality engineers, policymakers, sustainability consultants, and environmental scientists seeking to advance their knowledge and skills in air pollution mitigation. Public health professionals: Medical practitioners, public health advocates, and healthcare workers interested in understanding the health impacts of air pollution and promoting prevention strategies. Concerned citizens and students: Individuals passionate about environmental issues and climate change who seek actionable knowledge to advocate for cleaner air and a sustainable future. Anyone eager to understand and address the challenges of air pollution: This course empowers individuals from diverse backgrounds to contribute to solutions and advocate for a healthier planet.

About Course Master Environmental Impact Assessment (EIA) and Champion Sustainable Development with This Online Course Unleash your potential to understand, assess, and mitigate the environmental impacts of development projects with our comprehensive Environmental Impact Assessment (EIA) online course. Dive deep into legal frameworks, methodologies, real-world case studies, and best practices in order to equip yourself with the knowledge and skills to navigate the EIA process from A to Z. EIA Learning Outcomes/Course Objectives: Grasp the fundamentals of EIA: Understand the principles, purpose, and importance of EIA in ensuring sustainable development. Master the legal and regulatory landscape: Navigate relevant environmental laws, regulations, and policies governing the EIA process. Navigate the EIA process with expertise: Implement best practices in every stage of the EIA process, from screening and scoping to impact assessment, mitigation measures, and public engagement. Integrate social and cultural considerations: Assess the social and cultural implications of projects and ensure equitable distribution of benefits and burdens. Evaluate biophysical impacts: Analyze the potential impacts of projects on air, water, soil, flora, fauna, and ecosystem services. Manage cumulative and indirect effects: Identify and address the broader implications of projects, including cumulative and indirect effects on the environment. Develop effective mitigation and enhancement measures: Formulate practical strategies to minimize negative impacts and maximize positive environmental outcomes. Engage stakeholders effectively: Foster meaningful public participation and incorporate stakeholder feedback throughout the EIA process. Craft comprehensive Environmental Management Plans (EMPs): Design robust EMPs to monitor environmental impacts, implement mitigation measures, and ensure compliance. Navigate review, auditing, and decision-making: Understand the review and auditing processes and prepare for informed decision-making on project proposals. Stay ahead of the curve: Explore emerging trends and innovations in EIA, ensuring your skillset remains relevant in an evolving field. Target Audience: Environmental professionals: Consultants, scientists, engineers, and policymakers involved in conducting or reviewing EIAs. Project developers and proponents: Gain insights into the EIA process and its implications for project planning and approvals. NGOs and community organizations: Equip yourselves with the knowledge and tools to advocate for sustainable development and participate effectively in the EIA process. Students and individuals passionate about sustainability: Build a strong foundation in EIA and contribute to positive environmental change. Requirements: Curiosity and interest in environmental issues. A passionate interest in understanding and addressing environmental challenges is essential for engaging with this course. Basic understanding of scientific concepts. Familiarity with fundamental science principles will enhance your comprehension of complex environmental processes. Willingness to learn and adapt. Embrace a commitment to exploring new ideas and staying updated on best practices in the evolving field of EIA. Enroll today and become an EIA champion! This in-depth online course empowers you to navigate the EIA process with confidence. It also ensures sustainable development and a healthier planet for all. What Will You Learn? Grasp the fundamentals of EIA: Understand the principles, purpose, and importance of EIA in ensuring sustainable development. Master the legal and regulatory landscape: Navigate relevant environmental laws, regulations, and policies governing the EIA process. Navigate the EIA process with expertise: Implement best practices in every stage of the EIA process, from screening and scoping to impact assessment, mitigation measures, and public engagement. Integrate social and cultural considerations: Assess the social and cultural implications of projects and ensure equitable distribution of benefits and burdens. Evaluate biophysical impacts: Analyze the potential impacts of projects on air, water, soil, flora, fauna, and ecosystem services. Manage cumulative and indirect effects: Identify and address the broader implications of projects, including cumulative and indirect effects on the environment. Develop effective mitigation and enhancement measures: Formulate practical strategies to minimize negative impacts and maximize positive environmental outcomes. Engage stakeholders effectively: Foster meaningful public participation and incorporate stakeholder feedback throughout the EIA process. Craft comprehensive Environmental Management Plans (EMPs): Design robust EMPs to monitor environmental impacts, implement mitigation measures, and ensure compliance. Navigate review, auditing, and decision-making: Understand the review and auditing processes and prepare for informed decision-making on project proposals. Stay ahead of the curve: Explore emerging trends and innovations in EIA, ensuring your skillset remains relevant in an evolving field. Course Content Environmental Impact Assessment Environmental Impact Assessment Legal and Regulatory Frameworks Legal and Regulatory Frameworks EIA Process and Methodologies EIA Process and Methodologies Social and Cultural Considerations Social and Cultural Considerations Biophysical Impact Assessment Biophysical Impact Assessment Cumulative and Indirect Effects Cumulative and Indirect Effects Mitigation and Enhancement Measures Mitigation and Enhancement Measures Public Participation and Stakeholder Engagement Public Participation and Stakeholder Engagement Environmental Management Plans (EMPs) and Monitoring Environmental Management Plans (EMPs) and Monitoring EIA Review, Auditing, and Decision-making EIA Review, Auditing, and Decision-making Best Practices and Case Studies Best Practices and Case Studies Emerging Trends in EIA Emerging Trends in EIA A course by Xpert Learning RequirementsCuriosity and interest in environmental issuesBasic understanding of scientific concepts Audience Environmental professionals: Consultants, scientists, engineers, and policymakers involved in conducting or reviewing EIAs. Project developers and proponents: Gain insights into the EIA process and its implications for project planning and approvals. NGOs and community organizations: Equip yourselves with the knowledge and tools to advocate for sustainable development and participate effectively in the EIA process. Students and individuals passionate about sustainability: Build a strong foundation in EIA and contribute to positive environmental change. Audience Environmental professionals: Consultants, scientists, engineers, and policymakers involved in conducting or reviewing EIAs. Project developers and proponents: Gain insights into the EIA process and its implications for project planning and approvals. NGOs and community organizations: Equip yourselves with the knowledge and tools to advocate for sustainable development and participate effectively in the EIA process. Students and individuals passionate about sustainability: Build a strong foundation in EIA and contribute to positive environmental change.

Duration 4 Days 24 CPD hours This course is intended for This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Overview Skills gained in this training include:The features that Pig, Hive, and Impala offer for data acquisition, storage, and analysisThe fundamentals of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with HadoopHow Pig, Hive, and Impala improve productivity for typical analysis tasksJoining diverse datasets to gain valuable business insightPerforming real-time, complex queries on datasets Cloudera University?s four-day data analyst training course focusing on Apache Pig and Hive and Cloudera Impala will teach you to apply traditional data analytics and business intelligence skills to big data. Hadoop Fundamentals The Motivation for Hadoop Hadoop Overview Data Storage: HDFS Distributed Data Processing: YARN, MapReduce, and Spark Data Processing and Analysis: Pig, Hive, and Impala Data Integration: Sqoop Other Hadoop Data Tools Exercise Scenarios Explanation Introduction to Pig What Is Pig? Pig?s Features Pig Use Cases Interacting with Pig Basic Data Analysis with Pig Pig Latin Syntax Loading Data Simple Data Types Field Definitions Data Output Viewing the Schema Filtering and Sorting Data Commonly-Used Functions Processing Complex Data with Pig Storage Formats Complex/Nested Data Types Grouping Built-In Functions for Complex Data Iterating Grouped Data Multi-Dataset Operations with Pig Techniques for Combining Data Sets Joining Data Sets in Pig Set Operations Splitting Data Sets Pig Troubleshoot & Optimization Troubleshooting Pig Logging Using Hadoop?s Web UI Data Sampling and Debugging Performance Overview Understanding the Execution Plan Tips for Improving the Performance of Your Pig Jobs Introduction to Hive & Impala What Is Hive? What Is Impala? Schema and Data Storage Comparing Hive to Traditional Databases Hive Use Cases Querying with Hive & Impala Databases and Tables Basic Hive and Impala Query Language Syntax Data Types Differences Between Hive and Impala Query Syntax Using Hue to Execute Queries Using the Impala Shell Data Management Data Storage Creating Databases and Tables Loading Data Altering Databases and Tables Simplifying Queries with Views Storing Query Results Data Storage & Performance Partitioning Tables Choosing a File Format Managing Metadata Controlling Access to Data Relational Data Analysis with Hive & Impala Joining Datasets Common Built-In Functions Aggregation and Windowing Working with Impala How Impala Executes Queries Extending Impala with User-Defined Functions Improving Impala Performance Analyzing Text and Complex Data with Hive Complex Values in Hive Using Regular Expressions in Hive Sentiment Analysis and N-Grams Conclusion Hive Optimization Understanding Query Performance Controlling Job Execution Plan Bucketing Indexing Data Extending Hive SerDes Data Transformation with Custom Scripts User-Defined Functions Parameterized Queries Choosing the Best Tool for the Job Comparing MapReduce, Pig, Hive, Impala, and Relational Databases Which to Choose?

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 3 Days 18 CPD hours This course is intended for The EXIN BCS Artificial Intelligence Foundation certification is focused on individuals with an interest in, (or need to implement) AI in an organization, especially those working in areas such as science, engineering, knowledge engineering, finance, education or IT services. Overview You will be able to Describe how Artificial (AI) is Part of 'Universal Design', and 'The Fourth Industrial Revolution' Demonstrate Understanding of the Artificial Intelligence (AI) Intelligen Agent Description Explain the Benefits of Artificial Intelligence (AI) Describe how we Learn from Data - Functionality, Software and Hardware Demonstrate an Understanding that Artificial Intelligence (AI) (in Particular, Machine Learning (ML)) will Drive Humans and Machines to Work Together Describe a ''Learning from Experience'' Agile Approach to Projects Candidates should be able to demonstrate a knowledge and understanding in the application of ethical and sustainable Artificial Intelligence (AI):- Human-centric Ethical and Sustainable Human and Artificial Intelligence (AI) Ethical and Sustainable Human and Artificial Intelligence (AI) Recall the General Definition of Human and Artificial Intelligence (AI) Describe what are Ethics and Trustworthy Artificial Intelligence (AI) Describe the Three Fundamental Areas of Sustainability and the United Nationïs Seventeen Sustainability Goals Describe how Artificial Intelligence (AI) is Part of 'Universal Design', and 'The Fourth Industrial Revolution' Understand that Machine Learning (ML) is a Significant Contribution to the Growth of Artificial Intelligence (AI) Artificial Intelligence (AI) and Robotics Demonstrate Understanding of the Artificial Intelligence (AI) Intelligent Agent Description Describe what a Robot is Describe what an intelligent Robot is Applying the Benefits of Artificial Intelligence (AI) ? Challenges and Risks Describe how Sustainability Relates to Human-Centric Ethical Artificial Intelligence (AI) and how our Values will Drive our use of Artificial Intelligence (AI) and will Change Humans, Society and Organizations Explain the Benefits of Artifical Intelligence (AI) Describe the Challenges of Artificial Intelligence (AI) Projects Demonstrate Understanding of the Risks of Artificial Intelligence (AI) Projects List Opportunities for Artificial Intelligence (AI) Identify a Typical Funding Source for Artificial Intelligence (AI) Projects and Relate to the NASA Technology Readiness Levels (TRLs) Starting Artificial Intelligence (AI): how to Build a Machine Learning (ML) Toolbox ? Theory and Practice Describe how we Learn from Data - Functionality, Software and Hardware Recall which Rypical, Narrow Artificial Intelligence (AI) Capability is Useful in Machine Learning (ML9 and Artificial Intelligence (AI) AgentsïFunctionality The Management, Roles and Responsibilities of Humans and Machines Demonstrate an Understanding that Artificial Intelligence (AI) (in Particular, Machine Learning (ML)) will Drive Humans and Machines to Work Together List Future Directions of Humans and Machines Working Together Describe a ''Learning from Experience'' Agile Approach to Projects

Duration 0.5 Days 3 CPD hours This course is intended for This course is primarily designed for business leaders, consultants, product and project managers, and other decision-makers who are interested in growing the business by leveraging the power of AI. Other individuals who wish to explore basic AI concepts are also candidates for this course. This course is also designed to assist students in preparing for the CertNexus AIBIZ™ (Exam AIZ-210) credential. Overview In this course, you will identify ways in which AI can bring significant value to the business. You will: Describe AI fundamentals. Identify the functions of AI in business. Implement business requirements for AI. Artificial intelligence (AI) is not just another technology or process for the business to consider?it is a truly disruptive force, one that delivers an entirely new level of results across business sectors. Even organizations that resist adopting AI will feel its impact. If the organization wants to thrive and survive in this transforming business landscape, it will need to harness the power of AI. This course is designed to help business professionals conquer and move beyond the basics of AI to apply AI concepts for the benefit of the business. It will give you the essential knowledge of AI you'll need to steer the business forward. Lesson 1: AI Fundamentals Topic A: A Brief History of AI Topic B: AI Concepts Lesson 2: Functions of AI in Business Topic A: Improve User Experiences Topic B: Segment Audiences Topic C: Secure Assets Topic D: Optimize Processes Lesson 3: Implementing Business Requirements for AI Topic A: Identify Design Requirements Topic B: Identify Data Requirements Topic C: Identify Risks in Implementing AI Topic D: Develop an AI Strategy

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.