Introduction When it comes to academic writing, referencing is crucial. It’s not just about giving credit where it’s due, but also about enhancing the credibility of your work. Among the various referencing styles, Harvard referencing for word essays is one of the most widely used, especially in the UK. But why is it so popular, and how can you master it? Let’s dive in! Understanding Harvard Referencing Harvard referencing is a system of citation that allows you to acknowledge the sources you’ve used in your academic writing. It’s an author-date system, which means you include the author’s surname and the year of publication within the text, and provide full details in a reference list at the end. Despite its name, Harvard references didn’t originate from Harvard University. The style was first used by a zoologist named Edward Laurens Mark in a paper published in 1881. Over time, it has evolved and become one of the most recognized citation styles worldwide. Harvard referencing consists of two main components: in-text citations and a reference list. In-text citations are brief and are placed within the body of your text, while the reference list provides full details of all the sources you’ve cited. The Basics of Harvard Referencing In-text citations in Harvard referencing include the author’s surname and the year of publication. If you’re quoting directly, you should also include the page number. For example: (Smith, 2020, p. 23). The reference list is where you provide full details of each source cited in your work. Each entry should include the author’s name, year of publication, title of the work, and other relevant information, depending on the type of source. A reference list includes only the sources you’ve directly cited in your text, while a bibliography may include all sources you’ve consulted, whether or not you’ve cited them. How to Cite Different Types of Sources When citing a book, you should include the author’s name, year of publication, title (in italics), edition (if applicable), place of publication, and publisher. For example: Smith, J. (2020). The Art of Referencing (2nd ed.). London: Academic Press. Journal articles should include the author’s name, year of publication, title of the article, title of the journal (in italics), volume number, issue number, and page numbers. For example: Brown, A. (2019). ‘Understanding Harvard Referencing’, Journal of Academic Writing, 12(3), pp. 45-67. For websites, include the author (or organization), year of publication (or last update), title of the webpage (in italics), and the URL. For example: University of Oxford. (2021). Harvard Referencing Guide. Available at: https://www.ox.ac.uk/harvard (Accessed: 10 September 2024). When citing a newspaper article, include the author’s name, year of publication, title of the article, title of the newspaper (in italics), date, and page number. For example: Doe, J. (2022). ‘The Future of Academic Writing’, The Times, 5 May, p. 12. For government documents, include the name of the government department, year of publication, title of the document (in italics), place of publication, and publisher. For example: UK Department for Education. (2020). Education Policy Report. London: HMSO. Cite conference papers by including the author’s name, year of publication, title of the paper, title of the conference (in italics), location, and date of the conference. For example: Jones, M. (2023). ‘Innovations in Academic Writing’, International Writing Conference, Manchester, 10-12 April. Harvard Referencing for Electronic Sources When citing e-books, the format is similar to print books, but you should include the format (e.g., Kindle) or the platform where it’s available. For example: Adams, R. (2018). Digital Referencing (Kindle ed.). Available at: Amazon.co.uk. For online journals, follow the same format as print journals, but include the DOI or the URL where the article can be accessed. For example: Taylor, S. (2021). ‘Harvard Referencing in the Digital Age’, Journal of Modern Research, 15(4), pp. 33-50. DOI: 10.1234/jmr.2021.0987. The format for websites remains the same as mentioned earlier, with the inclusion of the URL and the access date. For social media, include the author (or username), year, content of the post (in italics), platform, and the date of the post. For example: @AcademicWriterUK. (2023). The key to successful referencing is consistency. Twitter, 15 March. Advanced Harvard Referencing Techniques When you can’t access the original source and need to cite a secondary source, mention both the original and secondary source. For example: (Smith, 1989, cited in Brown, 2019). For works with multiple authors, list up to three authors in the in-text citation. For more than three, use “et al.” after the first author’s name. For example: (Jones, Smith, and Brown, 2020) or (Jones et al., 2020). If you’re citing different editions of a book, mention the edition in your reference. For example: Brown, A. (2018). Theories of Learning (3rd ed.). Oxford: Oxford University Press. If some information is missing, like the author or date, use “Anon.” for anonymous authors and “n.d.” for no date. Common Harvard Referencing Mistakes and How to Avoid Them Incorrect formatting can easily occur if you’re not careful. Make sure to follow the correct structure for each type of source, as this can significantly impact your grade. Leaving out essential details like the author’s name or the year of publication is a common mistake. Always double-check your references before submitting your work. Punctuation is crucial in Harvard referencing. Misplacing a comma or period can change the meaning of your citation. Pay attention to the details! Tools and Resources for Harvard Referencing Online citation generators can save you time, but be cautious—always double-check the generated citations for accuracy. Tools like EndNote or Zotero can help you manage your references and ensure consistency throughout your work. Many universities provide specific guidelines for Harvard referencing. Always refer to your institution’s guidelines to ensure you’re following the correct format. The Importance of Consistency in Harvard Referencing Consistency is key in Harvard referencing. Uniformity in your citations not only makes your work look professional but also enhances readability. Inconsistent referencing can confuse readers and may lead to a lower grade. Make sure your citations follow a consistent style throughout your work. Tips for Mastering Harvard Referencing Always double-check your references before submission. Small errors can add up and impact your overall grade. Keep a record of all the sources you consult. This will make it easier to create your reference list and avoid missing any citations. Using a Harvard style guide can help ensure that you’re following the correct format. It’s a handy tool for quick reference. Conclusion Mastering Harvard referencing may seem daunting at first, but with practice and attention to detail, it becomes second nature. Remember, proper referencing not only supports your arguments but also adds credibility to your work. So, take your time, be consistent, and use the resources available to you.
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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.
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 Although there are no mandatory prerequisites, the course is particularly suited for the following audiences: Cybersecurity engineer Cybersecurity investigator Incident manager Incident responder Network engineer SOC analysts currently functioning at entry level with 2+ years of experience Overview After taking this course, you should be able to: Describe the types of service coverage within a SOC and operational responsibilities associated with each. Compare security operations considerations of cloud platforms. Describe the general methodologies of SOC platforms development, management, and automation. Explain asset segmentation, segregation, network segmentation, micro-segmentation, and approaches to each, as part of asset controls and protections. Describe Zero Trust and associated approaches, as part of asset controls and protections. Perform incident investigations using Security Information and Event Management (SIEM) and/or security orchestration and automation (SOAR) in the SOC. Use different types of core security technology platforms for security monitoring, investigation, and response. Describe the DevOps and SecDevOps processes. Explain the common data formats, for example, JavaScript Object Notation (JSON), HTML, XML, CommaSeparated Values (CSV). Describe API authentication mechanisms. Analyze the approach and strategies of threat detection, during monitoring, investigation, and response. Determine known Indicators of Compromise (IOCs) and Indicators of Attack (IOAs). Interpret the sequence of events during an attack based on analysis of traffic patterns. Describe the different security tools and their limitations for network analysis (for example, packet capture tools, traffic analysis tools, network log analysis tools). Analyze anomalous user and entity behavior (UEBA). Perform proactive threat hunting following best practices. The Performing CyberOps Using Cisco Security Technologies (CBRCOR) v1.0 course guides you through cybersecurity fundamentals and prepares you for the role of Information Security Analyst on a Security Operations Center team. You?ll learn to automate for security using cloud platforms and how to apply your knowledge to real-world scenarios Course Outline Understanding Risk Management and SOC Operations Understanding Analytical Processes and Playbooks Investigating Packet Captures, Logs, and Traffic Analysis Investigating Endpoint and Appliance Logs Understanding Cloud Service Model Security Responsibilities Understanding Enterprise Environment Assets Threat Tuning Threat Researching and Threat Intelligence Practices Understanding APIs Understanding SOC Development and Deployment Models Performing Security Analytics and Reports in a SOC Malware Forensics Basics Threat Hunting Basics Additional course details: Nexus Humans Cisco Performing CyberOps Using Cisco Security Technologies (CBRCOR) v1.0 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 Performing CyberOps Using Cisco Security Technologies (CBRCOR) v1.0 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 3 Days 18 CPD hours This course is intended for Attendee roles might include: Software Developers/Programmers Data Scientists Machine Learning Engineers AI Researchers User Interface (UI) and User Experience (UX) Designers Technical Product Managers Technical Team Leads Overview Working in an interactive learning environment, led by our engaging AI expert you'll: Develop a strong foundational understanding of generative AI techniques and their applications in software development. Gain hands-on experience working with popular generative AI models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models. Master the use of leading AI libraries and frameworks, such as TensorFlow, Keras, and Hugging Face Transformers, for implementing generative AI models. Acquire the skills to design, train, optimize, and evaluate custom generative AI models tailored to specific software development tasks. Learn to fine-tune pre-trained generative AI models for targeted applications and deploy them effectively in various environments, including cloud-based services and on-premises servers. Understand and address the ethical, legal, and safety considerations of using generative AI, including mitigating biases and ensuring responsible AI-generated content. Prompt Engineering offers coders and software developers a competitive edge by empowering them to develop more effective and efficient AI-driven solutions in their projects. By harnessing the capabilities of cutting-edge AI models like GPT-4, coders can automate repetitive tasks, enhance natural language understanding, and even generate code suggestions, boosting productivity and creativity. In addition, mastering prompt engineering can contribute to improved job security, as professionals with these in-demand skills are highly sought after in the rapidly evolving tech landscape. Quick Start to Prompt Engineering for Coders and Software Developers is a one day course designed to get you quickly up and running with the prompting skills required to out AI to work for you in your development efforts. Guided by our AI expert, you?ll explore key topics such as text preprocessing, data cleansing, GPT-4 tokenization, input formatting, prompt design, and optimization, as well as ethical considerations in prompt engineering. In the hands-on labs you?ll explore tasks such as formatting inputs for GPT-4, designing and optimizing prompts for business applications, and implementing multi-turn conversations with AI. You?ll work with innovative tools like the OpenAI API, OpenAI Codex, and OpenAI Playground, enhancing your learning experience while preparing you for integrating prompt engineering into your professional toolkit. By the end of this immersive course, you?ll have the skills necessary to effectively use prompt engineering in your software development projects. You'll be able to design, optimize, and test prompts for various business tasks, integrate GPT-4 with other software platforms, and address ethical concerns in AI deployment. Generative AI represents an exhilarating frontier in artificial intelligence, specializing in the creation of new data instances, imitation of real data, and content generation. Its remarkable capabilities facilitate automated content creation, enriched user experiences, and groundbreaking solutions across diverse industries, ultimately fueling efficiency and transcending technological limits. By harnessing the power of generative AI, developers can craft dynamic content, produce code and documentation, refine user interfaces, and devise customized recommendations, empowering them to construct highly efficient and custom solutions for a wide range of applications. Designed for experienced programmers, Turbocharge Your Code! Generative AI Boot Camp for Developers is a three-day workshop-style course that teaches you the latest skills and tools required to master generative AI models, transforming the way you approach software development. In today's fast-paced technological landscape, generative AI has emerged as a game-changer, with leading companies like NVIDIA, OpenAI, and Google leveraging its capabilities to push the boundaries of innovation. By learning how to harness the power of generative models such as GANs, VAEs, and Transformer models, you will be able to generate code, documentation, and tests, enhance user interfaces, and create dynamic content that adapts to user needs. Our comprehensive curriculum covers everything from the fundamentals of generative AI to advanced techniques and ethical considerations, including hands-on labs where you will develop and deploy custom models using state-of-the-art AI tools and libraries like TensorFlow and Hugging Face Transformers. Throughout the course you'll focus on practical application and collaboration, building confidence with personalized guidance and real-time feedback from our expert live instructor. Upon completion, you will be equipped with the knowledge and experience necessary to develop and implement innovative generative AI models across various industries, improving existing products, creating new applications, and gaining highly-valuable skills in the rapidly advancing field of AI. Additional course details: Nexus Humans Turbocharge Your Code! Generative AI Boot Camp for Developers (TTAI2305) 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. 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