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Jumpstart your creative journey with our Adobe After Effects Complete Guide for Beginners. Master the basics from importing footage to exporting videos, and learn key animation techniques to bring your visual concepts to life. Perfect for aspiring graphic artists and video editors.

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.

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 1 Days 6 CPD hours Articulate Rise 360 is a elearning authoring tool that lets you create beautiful, fully-responsive interactive courses fast. All you need to use Rise is an internet connection and a web browser to get started. This one day workshop covers the full creation of a Rise project from beginning to end and demonstrates how you can customize the look of your course with different themes, create lessons, add blocks and integrate flashcards and quizzes. Getting Started with Rise Logging into Articulate Touring the Rise Interface Previewing a Rise Course Creating a New Rise Course Creating a Lesson Creating a Video Lesson Creating a Labeled Graphic Lesson Creating a Process Lesson Creating a Sorting Activity Lesson Creating a URL Embed Lesson Creating a Quiz lesson Customizing Lessons Understanding Blocks Image and Gallery Blocks Multimedia Blocks Interactive Blocks Divider Blocks Course Settings Customizing Theme Settings Customizing Label Settings Customizing Navigation Settings Sharing and Exporting Your Project Sharing a Rise Course Exporting a Rise Course Additional course details: Nexus Humans Articulate Rise 360 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 Articulate Rise 360 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 Whether you are already an instructional designer or just looking to get into the world of developing eLearning courses, this two-day course covers the full feature set of Articulate Storyline 360 and uses real world exercises to create projects from scratch. The course will include how to add interactivity to your slides via buttons, triggers, text entry areas, and hotspots. You'll also learn how to create quizzes, and how to publish your eLearning projects for the widest possible audience. The class will also explore Articulate Storyline's advance techniques and methods on Themes & Templates, Custom Navigation, Gamification, Advanced Quizzing, Accessibility and Reporting, and more. Exploring Articulate Storyline Explore a Finished Storyline Project Explore Slides and Panels Zoom and Magnify Explore Panels Preview the Entire Project Creating Projects Create a New Project Apply a Theme Apply a Content Master Slide Insert New Slides Create a New Content Master Slide Apply a Different Master Slide Layout to a Slide Import Content From PowerPoint Adding Content Create and Format a Text Box Work with a List Add an Image to a Slide Add a Shape to a Slide Customize a Shape Insert a Character Insert a Caption Interactivity Add Buttons to Slides Change Button States Create Layers Insert a Text Entry Field Triggers and Hotspots Delete Default Triggers Add a Trigger to a Button Hide Player Buttons Add Triggers to Layers Add a Hide Layer Trigger Add a Slide Trigger Add a Conditional Trigger Edit a Trigger Add a Hotspot and Lightbox Trigger Variables Manage a Variable Reference a Variable Create a Variable Manipulate a Variable with a Trigger Create a True/False Variable Create a Trigger to Change a True/False Variable Add a Condition to an Existing Trigger Play Audio with a Conditional Trigger Add a Condition to a Button Audio, Animation and Video Add Voiceover Audio to a Slide Change Slide Audio Edit Slide Audio Add Silence Record Voiceover Audio Control Object Timing Animate an Object Control Animation Options Insert Video Delay Object Start Times Trim Video Animate a Video Add a Slide Transition Quizzes Insert a Multiple Choice Slide Insert a Matching Drag-and-Drop Slide Insert a Freeform Drag and Drop Quiz Slide Insert a Quiz Result Slide

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

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

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.

Τhis is a customised course offered only to advanced adult learners who speak and write Greek in an advanced or proficient level. The course is supported by readers, newspaper articles, audio and video files.

What will you learn in this course? Comprehend academic lectures, interviews, articles, and literature. Understand anything written or spoken. Summarise texts. Express yourselves spontaneously in all situations either simple or complex. The main topics to be covered in this course are: entertainment, tourism, travel, news, social & political issues, relationships, technology, philosophy, science, greek culture & history and much more...