12941 Courses

A webinar in which we explore the true cost of pointless stress and worry on our health, our happiness and our time and present the possibility of a future with more balance, more joy and better outcomes.

You can start your baby’s swimming journey as soon as you feel ready to visit a warm swimming pool. We have had babies taking their first swim at only four weeks old. The sooner you start swimming lessons for your baby the better their understanding and confidence in the water will be. Your baby’s first experience in a structured swimming lesson is a wonderful and gentle introduction to water sensory techniques. We will teach you how to be comfortable and confident holding, moving, floating and playing with your baby in the pool.

Our programme for toddlers is aimed at teaching your child water confidence, key lifesaving skills, a life long love of the water and building the first steps towards swimming unaided. In our sessions your child will benefit from increasing strength, coordination and exercises focused in progression and enjoyment at every lesson. We use songs and games to ensure your little one loves the time you spend together in the pool. We put emphasis on having lots of fun.

Providing Customer service products and services for businesses and other organisations including face-to-face telephone, digital and written contact and communications

"Join our free bodyweight workshop and learn effective exercises to improve your strength and flexibility without any equipment. Suitable for all fitness levels, this workshop is led by experienced trainers and offers a fun and challenging workout experience. Don't miss out on this opportunity to enhance your fitness journey!"

Carrying out manufacturing activities on multiple products with different specifications consecutively.

Introduction In today’s academic landscape, the integrity of one's work is more crucial than ever. With the prevalence of information readily available online, ensuring that your work is original can be challenging. This is where tools like a Plagiarism Checker come into play, offering invaluable assistance to students, researchers, and educators alike. These tools not only help in maintaining the authenticity of academic work but also bolster the credibility of the individual behind it. In this article, we'll explore the multifaceted role of plagiarism checker tools in academia, from essays to research papers. Understanding Plagiarism Definition of Plagiarism Plagiarism is the act of using someone else’s words, ideas, or expressions without proper acknowledgement. It’s a serious offence in academic and professional settings, leading to consequences ranging from loss of credibility to legal repercussions. Types of Plagiarism in Academic Writing Direct Plagiarism: Copying text verbatim without citation. Self-Plagiarism: Reusing one's previous work without acknowledgement. Mosaic Plagiarism: Borrowing phrases from a source without using quotation marks. Accidental Plagiarism: Unintentional failure to cite sources properly. Challenges Faced in Academic Writing Common Issues in Essay Writing Writing essays involves synthesizing information from various sources while presenting it in a unique voice. Common issues include unintentional plagiarism, inadequate citation, and difficulty in integrating sources seamlessly. Research Papers and Their Complexities Research papers require in-depth analysis, original research, and a comprehensive understanding of existing literature. Challenges include properly crediting sources, avoiding plagiarism, and maintaining originality. The Role of Plagiarism Checker Tools What is a Plagiarism Checker? A plagiarism checker is a tool designed to detect similarities between submitted text and existing content in its database. It scans documents and highlights matching phrases, helping users identify potential plagiarism. How Plagiarism Checkers Work Plagiarism checkers compare the text against a vast database of published works, websites, and academic papers. They use algorithms to detect similarities and provide a report detailing any matches found, indicating the percentage of copied content. Benefits of Using Plagiarism Checker Tools Ensuring Originality Plagiarism checker tools ensure that your work is original by detecting any unintentional copying from other sources. This helps in producing authentic and unique content. Enhancing Academic Credibility By verifying the originality of your work, plagiarism checkers enhance your academic credibility, demonstrating a commitment to integrity and scholarly excellence. Using Plagiarism Checker Tools for Essays How to Use a Plagiarism Checker for Essays Upload Your Document: Start by uploading your essay to the plagiarism checker. Run the Check: Initiate the plagiarism check and wait for the results. Review the Report: Analyze the report to identify any sections that need proper citation or rephrasing. Tips for Effective Essay Writing Plan Ahead: Outline your essay and plan your sources. Cite Properly: Use appropriate citation styles for references. Revise Thoroughly: Revise your essay to ensure clarity and originality. Utilizing Plagiarism Checker Tools for Research Papers Checking Research Papers for Plagiarism Prepare Your Draft: Ensure your research paper is ready for submission. Use a Plagiarism Checker: Upload and scan your paper. Address Plagiarism: Modify any flagged sections to enhance originality. Best Practices for Citing Sources Use a Consistent Style: Follow a specific citation style (APA, MLA, etc.). Credit All Sources: Ensure every piece of borrowed information is cited. Maintain a Reference List: Keep a comprehensive list of all references. Case Study: Impact of Plagiarism Checkers in Academia Real-Life Example of Plagiarism Detection In a notable case, a university discovered extensive plagiarism in student theses using plagiarism checkers. The tool identified significant matches with online sources, leading to disciplinary actions and highlighting the need for rigorous plagiarism checks. Lessons Learned from Case Studies Case studies reveal the importance of proactive plagiarism detection and the role of technology in maintaining academic integrity. They underscore the need for students and educators to use these tools regularly. Comparison of Popular Plagiarism Checker Tools Overview of Top Plagiarism Checkers Turnitin: Widely used in educational institutions for its comprehensive database and detailed reports. Grammarly: Combines grammar checking with plagiarism detection, ideal for writers and students. Copyscape: Popular for checking web content plagiarism, particularly useful for bloggers and online writers. Features and Pricing Turnitin: Offers extensive academic resources but can be expensive. Grammarly: Provides a user-friendly interface with moderate pricing. Copyscape: Cost-effective for simple plagiarism detection needs. The Future of Plagiarism Detection Advancements in Plagiarism Detection Technology Technological advancements are enhancing the accuracy and efficiency of plagiarism detection, with AI playing a pivotal role in identifying complex plagiarism patterns. The Role of AI in Plagiarism Checking AI-powered tools are capable of detecting paraphrasing and more nuanced forms of plagiarism, making them indispensable in the future of academic integrity. Academic Integrity and Ethics The Ethical Use of Plagiarism Checker Tools Using plagiarism checkers ethically involves ensuring that they are used to improve the originality of your work rather than to circumvent academic responsibilities. Encouraging Honest Academic Practices Educators should encourage the use of plagiarism checkers as a learning tool to promote honesty and diligence in academic work. Common Myths About Plagiarism Checker Tools Misconceptions and Clarifications “Plagiarism checkers are 100% accurate.”: While highly effective, they are not foolproof. “They can replace proper citation.”: Plagiarism checkers are a complement, not a substitute for proper citation practices. Addressing Fears and Concerns Concerns about privacy and the accuracy of plagiarism checkers can be mitigated by choosing reputable tools and understanding their limitations. Steps to Implement Plagiarism Checker Tools in Academia Integrating Tools into the Academic Workflow Institutions should incorporate plagiarism checkers into their academic processes, making them a standard part of assignment submission and evaluation. Training Students and Faculty Provide training on how to use plagiarism checkers effectively and ethically, ensuring everyone understands their role in upholding academic integrity. How New Assignment Help Utilizes Plagiarism Checker Tools Our Approach to Maintaining Originality At New Assignment Help, we use advanced plagiarism checker tools to ensure that every assignment is original and free from plagiarism. Our tools help students submit work with confidence, knowing it's unique. Benefits for Students Using New Assignment Help Students benefit from enhanced academic credibility, better grades, and a deeper understanding of proper citation practices by using our plagiarism detection services. Conclusion Plagiarism checker tools are invaluable in maintaining academic integrity and ensuring the originality of essays and research papers. As technology advances, these tools will continue to evolve, offering more sophisticated ways to detect and prevent plagiarism. Embracing these tools is essential for anyone serious about upholding academic standards and producing high-quality, credible work.

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

These events are designed to introduce the BOOK & basic ideas behind Understanding & Dealing with Everyday Racism The Six Stages Framework

These events are designed to work on the ideas introduced in Level 1: Understanding & Dealing with Everyday Racism The Six Stages Framework