7839 Feedback courses in Edinburgh delivered Online

Course Overview Learn the Latest Skills | Acknowledged by CPD & QLS | MCQ Based Exam & Tutor Support | Interactive Video Training  Flowers are a symbol of love and affection that can give you an instant mood boost. People all over the world exchange or give flowers as gifts, use them for decorative purposes and celebrate occasions. This Floristry and Flower Arrangement is a comprehensive, instructor-guided course, designed to provide a detailed understanding of the nature of the related sector and your key roles within it. You may find that working as a florist is a great option and a very lucrative business. This Floristry and Flower Arrangement Training course starts off with an introductory section on floristry.  You will learn to think differently with each flower you utilize through the creative process. This course is appropriate for seasoned florists as well as those new to the floral field because it will show you how to use fundamental floral abilities in the most beautiful contemporary style. What Will You Learn? How to use floral tools and supplies Recognize different flowers and plants and how to take care of them How to make floral arrangements such as bouquets, corsage, fruit baskets and basket gardens Different elements of floral design Starting your own floral business What classes are included in this package? Earn a digital certificate upon successful completion There are no set schedules, so you can work at your own pace. Our email and live chat specialists are available to assist you 24 hours a day, 7 days a week. On weekdays, you'll have access to a full-time tutor. Learn in a user-friendly, cutting-edge online learning environment. High-quality e-learning study materials Benefit from instant feedback through mock exams and multiple-choice assessments This course and/or training programme has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course and/or training programme is not regulated by Ofqual and is not an accredited qualification. Your training provider will be able to advise you on any further recognition, for example progression routes into further and/or higher education. For further information please visit the Learner FAQs on the Quality Licence Scheme website. Who Should Take This Course? This course will expand your competence and boost your CV with vital abilities and an endorsed lesson attesting to your understanding, whether you're an existing practitioner or an aspiring expert. Career Path Training offered by the Floristry and Flower Arrangement Training could potentially benefit a range of roles, but would particularly enhance careers in: Florist Floral Designer Plant Engineer Event Planners Floral Technologist Floral Grower Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessments Assignment Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post. Endorsed Certificate of Achievement from the Quality Licence Scheme Once the course has been completed and the assessment has been passed, all students are entitled to receive an endorsed certificate. This will provide proof that you have completed your training objectives, and each endorsed certificate can be ordered and delivered to your address for only £119. Please note that overseas students may be charged an additional £10 for postage. Endorsement This course and/or training programme has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course and/or training programme is not regulated by Ofqual and is not an accredited qualification. Your training provider will be able to advise you on any further recognition, for example progression routes into further and/or higher education. For further information please visit the Learner FAQs on the Quality Licence Scheme website. Method of Assessment On successful completion of the Floristry and Flower Arrangement Training, you will be required to sit an online multiple-choice assessment. You will need to score 60% or above to pass the course. After successfully passing the exam, you will be able to apply for a Quality Licence Scheme endorsed certificate of achievement. The assessment will be evaluated automatically and the results will be given to you immediately. Retake fee If you do not pass the exam first time, you can purchase the Retake Exam for £1.99 and try again. Course Content Introduction to the Course Introduction to Floristry Services Provided by Florists Flowers and Plants Flower Care and Treatment Choosing Popular Flowers and Fillers Elements and Principles of Design How to Make Floral Arrangements Making Bouquet, Corsage, Fruit Basket & Basket Garden Wedding Floristry Making Funeral Flower Arrangements Beautiful Floral Designs Getting a Job in the Floristry Industry Starting Your Own Floristry Business Conclusion to the Course

Enhance your training & mentoring skills with this CPD-accredited, QLS-endorsed course. Gain expertise & career growth with flexible learning.

Duration 1 Days 6 CPD hours This course is intended for Learners taking this course are interested in employee experiences or Microsoft Viva and want to learn how to assess, plan, strategize, design, and manage digital employee experiences that use Microsoft Viva, Microsoft Teams, SharePoint, and Power Platform. A learner in this role will collaborate with multiple teams to scope, design, and implement new digital employee experiences, such as onboarding, career and skill development, rewards and recognition, employee wellbeing, and employee retention. Learners should have a foundational understanding of Microsoft technologies, including Microsoft 365, Teams, SharePoint, and a deep understanding of Microsoft Viva features and capabilities. They may have experience in one or more of the following disciplines: human resources, people development, change management, information technology, or culture development. Overview By the end of this module, you'll be able to: Evaluate existing systems and identify requirements Identify stakeholders and users Recommend employee experience solutions and strategies Describe the four experience areas of Connection, Growth, Purpose, and Insights supported by Viva. Explain what Microsoft Viva apps are. Identify resources needed to set up each Viva app. Create an adoption plan to use Viva to solve business scenarios for the four employee experience areas of Connection, Insight, Purpose, and Growth. Describe the main features of Viva Connections List technical requirements/prerequisites for Viva Connections implementation Explain the differences between desktop and mobile experiences Identify 2-3 business use cases for Viva Connections Identify key stakeholders for the deployment of Viva Connections Align and prioritize scenarios for Viva Connections Plan and design for the Dashboard, the Feed, and Resources by scenarios and audiences Consider how your organization will scale adoption Assess your organization's existing learning experiences. Plan and strategize for Viva Learning. Coordinate the implementation of Viva Learning. Recommend an adoption strategy for Viva Learning. In this course, you'll learn how to bring people together to create an optimal employee experience that enables your organization to improve productivity, develop empathetic leadership, and transform how employees feel about their work. In your organization today, are people being treated well, or are their needs neglected? Are your teams aligned on goals with a sense of purpose? Are you driving the business outcomes that you need? The Microsoft Viva employee experience platform provides the infrastructure to create the culture of trust, collaboration, well-being, and active listening that you envision. This training course will provide Microsoft Employee Experience Platform Specialists with a comprehensive overview of Microsoft Viva, as well as Microsoft 365, Teams, and SharePoint. It will cover how to identify requirements for designing experiences for employee onboarding, career and skill development, rewards and recognition, compensation and benefits, employee wellbeing, and employee retention. It will also cover how to design solutions to meet these requirements, and how to collaborate with senior executive leadership, human resources, IT, adoption and change management, and learning and organizational development departments. Finally, it will cover how to continuously improve employee experiences based on data-driven insights and feedback. Design digital employee experiences Introduction Case study - Tailwind Traders Evaluate current employee experiences Consider employee privacy and data requirements Assemble business stakeholders and define goals Explore Viva experience areas Understand Viva licensing Knowledge check Summary and resources Introduction to the Microsoft Viva suite Introduction to Microsoft Viva Understand Viva apps Get started with Microsoft Viva Use Viva to keep everyone informed, included, and inspired Use Viva to get actionable insights to foster well-being and productivity Use Viva to align people's work to team and organization goals Use Viva to help employees learn, grow, and succeed Knowledge check Summary Introduction to Viva Connections Introduction What do users experience? When to use Viva Connections? What technical requirements must be met to deploy Viva Connections? Knowledge check Summary Plan for Viva Connections Introduction Build your team and meet requirements Analyze tasks and scenarios for Viva Connections Plan for Viva Connections Dashboard, Feed and Resources Plan to announce, launch, and scale adoption Knowledge check Summary Design skilling and growth experiences with Viva Learning Introduction Case study - Tailwind Traders Plan for Viva Learning Assemble Viva Learning admins and stakeholders Understand content sources with Viva Learning Coordinate setup and configuration of Viva Learning Develop adoption strategies for Viva Learning Develop an org-wide learning culture Knowledge check Summary and resources Additional course details: Nexus Humans MS-080T00: Employee Experience Platform Specialist 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 MS-080T00: Employee Experience Platform Specialist 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.

Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career Path After completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions. Course Content Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Machine Learning using Python : A Bootcamp 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

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. 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 Turbocharge Your Code! Generative AI Boot Camp for Developers (TTAI2305) 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.

Helping customers buy products or services from retail organisations such as department stores, garden centres, high street chains, supermarkets and online and mail order businesses.

Managing the movement of goods across all sectors and distances for a range of customers from private individuals and sole traders through to large global organisations.

Duration 3 Days 18 CPD hours This course is intended for This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.

Develop more advanced training skills such as expert presentation, facilitation and coaching skills. Course overview Duration: 2 days (13 hours) This workshop is for people who want to take their personal skills as a trainer to the next level. It builds on the Underscore Level 1 Train the Trainer course.  In this Level 2 course delegates will develop more advanced training skills such as expert presentation, facilitation and coaching skills. In the modern world learning is often delivered in blended learning formats and this course will introduce delegates to the challenges of blended learning and how to introduce a range of delivery methods into programmes. Attendees will learn how to write more complex learning plans and integrate different methods and media into their plans. Objectives  By the end of the course you will be able to: Describe your Personal Training Style Explain how personality affects communication styles Use techniques to read delegates and adapt communications for greater impact Recognise the ‘games people play’ and how to deal with difficult behaviour Use techniques to establish credibility and enhance your reputation Identify the right approach to take when faced with a range of challenges Use advanced Presentation Skills Use facilitation and coaching skills for experiential workshops Use modern Training Methods and Media Deliver memorable training Note: Delegates attending this programme will be asked to complete an online psychometric in advance of attending the programme in order to help understand personal training styles Content Understanding your Personal Training Style Receive feedback from online Psychometric Understand personal training styles Understand personal communication and working style Understand the impact this has on audience Learn how to adapt your style for greater impact Growing your reputation as a trainer Your Training Persona Training Confidence Training Reputation Trainer Brand Understand the ‘Games People Play’ An introduction to Transactional Analysis (TA) for Trainers Using TA to:Contract for learningUnderstand Trainee AudienceUnderstand interpersonal stylesUnderstand working and thinking stylesWorking in groupsCreativity and innovation Developing deeper Trainer Skills Presentation Magic – making your presentations more effective Facilitation skills for workshops Coaching skills for classrooms and virtual training Delivering experiential workshops Modern Training Methods and Media Incorporating blended learning into your programmes Using Social Learning Using Videos Using Virtual Tools Using CBT and e-learning Pre-course work 1: Complete and online Psychometric Pre-course work 2: Deliver and record a 5-10-minute training session in your workplace on your phone and bring it with you Note: there is an option to have addition 1 hour coaching for delegates to support workplace learning after the course.

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