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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 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.

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.

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 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 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

About Course Environmental Engineering: A Career-Launching Course Are you passionate about protecting the environment? Do you want to make a difference in the world? If so, then environmental engineering is the perfect career for you. This online course will teach you the fundamentals of environmental engineering, from water and wastewater treatment to air pollution control and solid waste management. You will learn how to apply these principles to solve real-world problems, such as developing sustainable water systems, reducing air pollution, and managing hazardous waste. The course is developed by experienced environmental engineers who are passionate about their work. Their knowledge and expertise will help you develop the skills you need to succeed in this exciting field. Upon completion of this course, you will be well-prepared for a career in environmental engineering. You will have the knowledge and skills you need to design, implement, and manage environmental systems that protect our planet. Enroll today and start your journey to a more sustainable future! Here are some of the benefits of taking this course: Learn from experienced environmental engineers Gain the skills and knowledge you need for a career in environmental engineering Apply your knowledge to real-world problems Get hands-on experience with environmental engineering projects Network with other students and professionals in the field If you are interested in a career in environmental engineering, then this course is for you. Enroll today and start your journey to a more sustainable future! What Will You Learn? Understand the fundamentals of environmental engineering. This includes the basic principles of engineering, chemistry, and biology as they apply to environmental problems. Apply environmental engineering principles to solve real-world problems. This includes designing, implementing, and managing environmental systems such as water treatment plants, air pollution control systems, and solid waste management facilities. Communicate effectively about environmental issues. This includes being able to write reports, give presentations, and work with stakeholders to solve environmental problems. Work effectively in multidisciplinary teams. Environmental engineering problems often require the expertise of engineers, scientists, and other professionals. This course will teach you how to work effectively with others to solve these problems. Demonstrate professional and ethical behavior. As an environmental engineer, you will be responsible for protecting the health and safety of the public. This course will teach you the importance of professional and ethical behavior in environmental engineering. Course Content Introduction to Environmental Engineering Introduction to Environmental Engineering Environmental Chemistry and Microbiology Environmental Chemistry and Microbiology Water and Wastewater Treatment Water and Wastewater Treatment Air Pollution Control Air Pollution Control Solid Waste Management Solid Waste Management A course by Xpert Learning RequirementsBasic understanding of Chemistry and Biology. Audience Environmental Engineering Students Civil Engineering Students Individuals who have interest in Environmental Engineering Audience Environmental Engineering Students Civil Engineering Students Individuals who have interest in Environmental Engineering