115 Natural Language Processing (NLP) courses in London delivered Online

Dive into the transformative world of Artificial Intelligence through the course titled 'Foundations of Artificial Intelligence: Building Intelligent Systems.' This comprehensive curriculum sweeps across an array of subjects, from the rudimentary introduction to AI to the intricate nuances of building AI applications. Embrace a holistic understanding of core modules like Machine Learning, Natural Language Processing, and Robotics. The content, framed meticulously, beckons those inquisitive minds eager to craft, innovate, and change the world with AI's limitless possibilities. Deepen your conceptual clarity with two-part modules that delve into Knowledge Representation and Machine Learning, ensuring that learners grasp intricate details without feeling overwhelmed. With sections dedicated to Computer Vision and Deep Learning, individuals will find themselves proficiently navigating the vibrant ecosystems these technologies encompass. Finally, a spotlight on AI applications ensures that learners not only acquire theoretical wisdom but also grasp how AI integrates into real-world scenarios. By the culmination of this course, participants will stand at the forefront of AI innovations, armed with the acumen to shape a future where intelligent systems intertwine seamlessly with our daily lives. This foundation lays the groundwork for boundless exploration in the Artificial Intelligence realm Learning Outcomes Upon completion of this course, participants will be able to: Gain comprehensive insights into the fundamental principles of Artificial Intelligence. Understand the critical mathematical concepts underpinning AI technologies. Develop proficiency in various AI knowledge representation methods. Acquire a solid foundation in Machine Learning, Deep Learning, and Natural Language Processing techniques. Familiarise with the applications and integrations of AI in Robotics and Computer Vision. Why buy this Foundations of Artificial Intelligence: Building Intelligent Systems? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Foundations of Artificial Intelligence: Building Intelligent Systems there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Foundations of Artificial Intelligence: Building Intelligent Systems course for? This Foundations of Artificial Intelligence: Building Intelligent Systems does not require you to have any prior qualifications or experience. You can just enrol and start learning. Aspiring AI enthusiasts keen on building a robust foundation in the subject. Technologists aiming to pivot into AI-centric roles. Researchers eager to enhance their knowledge spectrum in intelligent systems. University students studying computer science or related disciplines, looking to supplement their academic pursuits. Entrepreneurs eyeing opportunities in AI-driven ventures. Prerequisites This Foundations of Artificial Intelligence: Building Intelligent Systems does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Foundations of Artificial Intelligence: Building Intelligent Systems was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path AI Research Scientist - Average Salary Range: £60,000 - £85,000 per annum Machine Learning Engineer - Average Salary Range: £55,000 - £80,000 per annum NLP Specialist - Average Salary Range: £50,000 - £75,000 per annum Computer Vision Engineer - Average Salary Range: £52,000 - £77,000 per annum Robotics Engineer - Average Salary Range: £48,000 - £73,000 per annum AI Application Developer - Average Salary Range: £54,000 - £79,000 per annum Course Curriculum Module 01: Introduction to Artificial Intelligence Introduction to Artificial Intelligence 00:21:00 Module 02: Mathematics for AI Mathematics for AI 00:17:00 Module 03: Knowledge Representation in AI - Part 1 Knowledge Representation in AI - Part 1 00:18:00 Module 04: Knowledge Representation in AI - Part 2 Knowledge Representation in AI - Part 2 00:16:00 Module 05: Machine Learning - Part 1 Machine Learning - Part 1 00:16:00 Module 06: Machine Learning - Part 2 Machine Learning - Part 2 00:15:00 Module 07: Deep Learning Deep Learning 00:16:00 Module 08: Natural Language Processing Natural Language Processing 00:22:00 Module 09: Computer Vision Computer Vision 00:14:00 Module 10: Robotics Robotics 00:18:00 Module 11: Building AI Applications Building AI Applications 00:24:00

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This comprehensive course unlocks the boundless potential of LangChain, Pinecone, OpenAI, and LLAMA 2 LLM, guiding you from AI novice to expert. Dive into 15 different practical projects, from dynamic chatbots to data analysis tools, and cultivate a profound understanding of AI, empowering your journey into the future of language-based applications.

Artificial neural networks (ANNs) are the most powerful machine learning algorithms available today. They are capable of learning complex relationships in data, and they have been used to achieve state-of-the-art results in a wide variety of fields, including image recognition, natural language processing, and speech recognition. The Future of Machine Learning is Here! This Project on Deep Learning - Artificial Neural Network course will teach you how to build and train ANNs from scratch. You will learn about the different components of an ANN, such as the input layer, hidden layers, and output layer. You will also learn about the different activation functions that can be used in ANNs, and you will see how to optimise ANNs for different tasks. In addition to the theoretical concepts, you will also get experience with ANNs. You will work on a project where you will build an ANN to classify images. You will use the TensorFlow library to build your ANN, and you will see how to train your ANN on a dataset of images. By the end of this Project on Deep Learning - Artificial Neural Network course, you will have a deep understanding of ANNs and how to use them. You will be able to build your own ANNs to solve a variety of problems. You will also be able to use the TensorFlow library to build and train ANNs. So what are you waiting for? Enrol in this course today and start learning about the future of machine learning!   Learning Outcomes: Through this comprehensive course, you should be able to: Understand the fundamental concepts of deep learning and artificial neural networks. Install and configure an artificial neural network framework. Preprocess and structure data for optimal model performance. Encode data effectively for neural network training and predictions. Build and deploy artificial neural networks for real-world applications. Address data imbalance challenges and optimise model accuracy.   Who is this course for? This Project on Deep Learning - Artificial Neural Network course is ideal for: Data scientists and machine learning practitioners seeking to expand their knowledge. Software engineers interested in leveraging deep learning techniques. Students pursuing a career in artificial intelligence and machine learning. Professionals looking to enhance their skills in neural network development. Individuals with a passion for exploring advanced machine learning techniques.   Career Path  Our course will prepare you for a range of careers, including: Deep Learning Engineer: £40,000 - £100,000 per year. Machine Learning Researcher: £45,000 - £120,000 per year. Data Scientist: £50,000 - £110,000 per year. Artificial Intelligence Specialist: £55,000 - £130,000 per year. Software Engineer (specialising in AI): £45,000 - £100,000 per year. Research Scientist (Machine Learning): £50,000 - £120,000 per year. AI Consultant: £60,000 - £150,000 per year. Certification After studying the course materials of the Project on Deep Learning - Artificial Neural Network (ANNs) there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Prerequisites This Project on Deep Learning - Artificial Neural Network (ANNs) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Project on Deep Learning - Artificial Neural Network (ANNs) was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.   Course Curriculum Section 01: Introduction Introduction of Project 00:03:00 Section 02: ANN Installation Setup Environment for ANN 00:11:00 ANN Installation 00:09:00 Section 03: Data Preprocessing Import Libraries and Data Preprocessing 00:11:00 Data Preprocessing 00:07:00 Data Preprocessing Continue 00:10:00 Section 04: Data Encoding Data Exploration 00:10:00 Encoding 00:07:00 Encoding Continue 00:06:00 Preparation of Dataset for Training 00:04:00 Section 05: Steps to Build ANN Steps to Build ANN Part 1 00:06:00 Steps to Build ANN Part 2 00:06:00 Steps to Build ANN Part 3 00:06:00 Steps to Build ANN Part 4 00:09:00 Section 06: Predictions and Imbalance-Learn Predictions 00:11:00 Predictions Continue 00:08:00 Resampling Data with Imbalance-Learn 00:09:00 Resampling Data with Imbalance-Learn Continue 00:08:00

Our goal with this course is to teach advanced Vietnamese.

Overview: UI Design for Voice Assistants: Creating Conversational Interfaces   Welcome to the future of user interfaces! In today's digital landscape, voice assistants are becoming increasingly prevalent, revolutionizing the way users interact with technology. Our comprehensive course, 'UI Design for Voice Assistants: Creating Conversational Interfaces,' equips you with the knowledge and skills needed to craft engaging and intuitive conversational experiences.   Module 1: Introduction to Voice Assistants and Conversational UI Get acquainted with the fundamentals of voice assistants and conversational user interfaces. Explore the evolution of voice technology and its impact on user interactions. Learn about the key principles and challenges of designing for conversational UI.   Module 2: User-Centered Design for Voice Assistants Put the user at the center of your design process. Discover techniques for understanding user needs, behaviors, and preferences in the context of voice interactions. Learn how to conduct user research and usability testing to create user-centric voice experiences.   Module 3: Designing Effective Voice Interactions Master the art of crafting natural and meaningful voice interactions. Explore best practices for structuring conversations, managing dialogue flow, and providing clear prompts and feedback. Dive into the psychology of conversation and learn how to create engaging user experiences.   Module 4: Speech Recognition and Natural Language Understanding (NLU) Gain insights into the underlying technologies powering voice assistants. Understand the principles of speech recognition and natural language understanding (NLU). Learn how to leverage NLU to interpret user inputs accurately and respond intelligently.   Module 5: Designing Voice User Interfaces (VUI) Learn the principles of designing intuitive voice user interfaces (VUI). Explore techniques for organizing information, designing navigation systems, and creating voice commands. Understand how to optimize VUI for accessibility and inclusivity.   Module 6: Visual Design for Voice Assistants Explore the role of visual design in enhancing the user experience of voice assistants. Learn how to leverage visual elements such as typography, color, and layout to complement voice interactions. Discover strategies for designing multimodal interfaces that seamlessly integrate voice and visual components.   Whether you're a seasoned UI/UX designer looking to expand your skill set or a newcomer eager to dive into the world of voice interfaces, our course provides a comprehensive foundation for designing compelling conversational experiences. Join us and embark on a journey to shape the future of human-computer interaction with UI Design for Voice Assistants: Creating Conversational Interfaces. Course Curriculum Module 1_ Introduction to Voice Assistants and Conversational UI Introduction to Voice Assistants and Conversational UI 00:00 Module 2_ User-Centered Design for Voice Assistants User-Centered Design for Voice Assistants 00:00 Module 3_ Designing Effective Voice Interactions Designing Effective Voice Interactions 00:00 Module 4_ Speech Recognition and Natural Language Understanding (NLU) Speech Recognition and Natural Language Understanding (NLU) 00:00 Module 5_ Designing Voice User Interfaces (VUI) Designing Voice User Interfaces (VUI) 00:00 Module 6_ Visual Design for Voice Assistants Visual Design for Voice Assistants 00:00

Looking to bring your AI knowledge to life in a visually powerful way? Our Hands-on Machine Learning Project – Auto Image Captioning for Social Media Course takes you deep into the fascinating world of machine-generated descriptions. With social media driving more engagement through visuals than ever, this course helps you grasp how AI can generate captions that not only describe but also engage, contextualise, and communicate effectively. The focus is sharply tuned to image captioning technology and its role in today’s media-driven, attention-tight landscape. Expect to work your way through a structured learning journey where you’ll explore the building blocks of machine learning and how these elements are applied in automated image captioning. Whether you're aiming to polish your ML project portfolio or understand how AI is quietly shaping the way content is created and consumed online, this course gives you just the right amount of edge — no gimmicks, no fluff, just what matters. All content is delivered fully online, making it a flexible and accessible way to deepen your understanding of AI-powered communication tools used across social media platforms. Learning Outcomes: Develop an auto image captioning system using machine learning. Preprocess image and caption data. Define and evaluate the model. Deploy your machine learning app on AWS EC2 instance.Gain real-world experience in machine learning app development. The Hands-on Machine Learning Project - Auto Image Captioning for Social Media Platform course is designed to give you a comprehensive understanding of how to develop an auto image captioning system using machine learning. The course covers topics such as importing libraries, preprocessing text and image data, defining and evaluating the model, and deploying your machine learning app on AWS EC2 instance. You'll have access to the caption dataset and image dataset for training and test purposes, providing you with hands-on experience in machine learning app development. This course is perfect for aspiring data scientists, machine learning engineers, and developers who want to gain real-world experience in machine learning app development. With the skills and knowledge gained from this course, you'll be able to create your own auto image captioning system and start a career in the exciting field of machine learning. Hands on Machine Learning Project - Auto Image Captioning for Social Media Course Curriculum Section 01: Introduction Introduction to Course Section 02: Building the Auto Image Captioning Import the Libraries Accessing the Caption Dataset for Training Accessing the Image DataSet for Training Preprocessing the Text Data Pre-Process and Load Captions Data Loading the Captions for Training and Test Data Preprocessing of Image Data Loading Features for Train and Test Dataset Text Tokenization and Sequence Text Data Generators Define the Model Evaluation of Model Test the Model Section 03: Deployment of Machine Learning App Create Streamlit App Streamlit Prediction Test Streamlit App Deploy Streamlit on AWS EC2 Instance How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Aspiring data scientists. Machine learning engineers. Developers interested in machine learning app development. Anyone interested in the field of machine learning. Professionals looking to upskill in the latest technology. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Data Scientist: £40,000 to £80,000 per year. Machine Learning Engineer: £55,000 to £90,000 per year. Software Developer: £30,000 to £60,000 per year. Artificial Intelligence Developer: £40,000 to £80,000 per year. Computer Vision Engineer: £45,000 to £85,000 per year. Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Duration 1 Days 6 CPD hours This course is intended for This introductory-level course is great for experienced technical professionals working in a wide range of industries, such as software development, data science, marketing and advertising, finance, healthcare, and more, who are looking to use the latest AI and machine learning techniques in their day to day. The hands-on labs in this course use Python, so you should have some familiarity with Python scripting basics. Overview Working in an interactive learning environment, led by our engaging OpenAI expert you'll: Understand the capabilities and products offered by OpenAI and how to access them through the OpenAI API. set up an OpenAI environment on Azure, including creating an Azure virtual machine and configuring the environment to connect to Azure resources. Gain hands-on experience building a GPT-3 based chatbot on Azure and implement advanced natural language processing capabilities. Use the OpenAI API to access GPT-3 and generate high-quality text Learn how to use Whisper to improve the quality of text generation. Understand the capabilities of DALL-E and use it to generate images for unique and engaging visuals. Geared for technical professionals, Quick Start to Azure AI Basics for Technical Users is a fun, fast paced course designed to quickly get you up to speed with OpenAI?s powerful tools and functionality, and to provide hands-on experience in setting up an OpenAI environment on Azure. Guided by our AI expert, you?ll explore the capabilities of OpenAI's GPT-3, Whisper and DALL-E, and build a chatbot on Azure. It will provide you with the knowledge and resources to continue your journey in AI and machine learning and have a good understanding of the potential of OpenAI and Azure for your projects. First, you?ll dive into the world of OpenAI, learning about its products and the capabilities they offer. You'll also discover how Azure's offerings for AI and machine learning can complement OpenAI's tools and resources, providing you with a powerful combination for your projects. And don't worry if you're new to Azure, we'll walk you through the process of setting up an account and creating a resource group. As you progress through the course, you'll get the chance to work with OpenAI's GPT-3, one of the most advanced large language models available today. You'll learn how to use the OpenAI API to access GPT-3 and discover how to use it to generate high-quality text quickly and easily. And that's not all, you'll also learn how to build a GPT-3 based chatbot on Azure, giving you the opportunity to implement advanced natural language processing capabilities in your chatbot projects. The course will also cover OpenAI Whisper, an OpenAI tool that can improve the quality of text generation, allowing you to create more coherent and natural language content. And you will learn about OpenAI DALL-E, an OpenAI tool that can generate images, giving you the ability to create unique and engaging visuals to enhance your content and projects. Introduction to OpenAI and Azure Explore OpenAI and its products, as well as Azure's offerings for AI and Machine Learning, allowing you to understand the tools and resources available to you for your AI projects. Explore OpenAI and its products Explore Azure and its offerings for AI and Machine Learning Get Hands-On: Setting up an OpenAI environment on Azure Walk through the process of setting up an OpenAI environment on Azure, giving you the hands-on experience needed to start building your own projects using OpenAI and Azure. Create an Azure virtual machine and installing the OpenAI SDK Configure the OpenAI environment and connecting to Azure resources Explore OpenAI GPT-3 Learn about GPT-3, one of OpenAI's most powerful language models, and how to use it to generate high quality text, giving you the ability to create natural language content quickly and easily. Review GPT-3 and its capabilities Use the OpenAI API to access GPT-3 Get Hands-on: Building a GPT-3 based chatbot on Azure Learn how to build a GPT-3 based chatbot on Azure, giving you the opportunity to learn how to implement advanced natural language processing capabilities in your chatbot projects. Setup an Azure Function and creating a chatbot Integrate GPT-3 with the chatbot OpenAI Whisper Explore Whisper, an OpenAI tool that can improve the quality of text generation, allowing you to create more coherent and natural language content. Explore Whisper and its capabilities Use Whisper to improve the quality of text generation OpenAI DALL-E Explore DALL-E, an OpenAI tool that can generate images, giving you the ability to create unique and engaging visuals to enhance your content and projects. Explore DALL-E and its capabilities Use the OpenAI API to access DALL-E What?s Next: Keep Going! Other ways OpenAI can impact your day to day Explore great places to check for expanded tools and add-ons for Azure OpenAI Where to go for help and support Quick Look at Generative AI and its Business Implications Understanding Generative AI Generative AI in Business Ethical considerations of Generative AI

Duration 1 Days 6 CPD hours This course is intended for Anyone whose role requires them to use existing Power BI Reports or Dashboards to consume the contents. Roles can include management at all levels, team leaders or anyone who needs to commission the production of reports or dashboards. It is assumed that attendees on the course are familiar with charts. Please note that this course is not suitable for new Excel users, delegates need Ability to create charts Ability to use filters in data Overview This course covers the use of Power BI Desktop and the Power BI service hosted in Office 365 to identify core features, terminology and processes applicable when using reports or dashboards.Delegates will learn how to: Power BI Concepts and Main Features How a report is created Navigating reports and dashboards How to apply filters and slicers To use Insights, Analytics and Natural Language Queries Power BI provides a variety of methods for using reports and dashboards within which data can be viewed and analyzed visually. Getting Started with Power BI Power BI Concepts and Versions Introduction to Main Features: Jargon buster From Data to Reports and Dashboards Visualizations Overview Visualizations Available Visualizations as Filter Reports and Dashboards Similarities and differences Understanding what you are looking at Understanding what you are looking at Using a Report in Power BI Filters, sorting and using slicers See the actual data See Data and See Records Drill visualizations Off the shelf data analysis Quick Conditional Formatting Analytics lines Use Insight for Increases and Decrease Forecast Analytics Changing calculations and Show As Working with Dashboards Dashboards in Power BI Defined How is a dashboard different from a report? Working in the Dashboard window

Duration 2 Days 12 CPD hours This course is intended for This is an Intermediate PowerBI course geared for experienced users who wish to leverage the tool's more advanced capabilities Overview This course is about 50% hands-on lab and 50% lecture, designed to train attendees in essential PowerBI data handling functions and reporting skills, coupling the most current, effective techniques with the soundest practices. Attendees of this course will gain practical examples from the experienced instructor who has deployed and configured Power BI reporting in a wide variety of businesses. Working in a hands-on learning environment led by our expert facilitator, students will learn how to: Create Advanced Power BI Reports Advanced understanding of the data schemas and extracting data Perform advanced transformations of data or any data schema Utilize time-phased data in the creation of complex analyses Create new measures using DAX Filter data using row-level security Create and deploy content packs Use Power BI to integrate with line-of-business applications Next Level Power BI for Experienced Users is a two day, course that provides attendees already experienced with Microsoft Power BI basics with a hands-on exploration of intermediate and beyond level features. This course is geared for attendees ready to learn the advanced techniques that you, your business analysts, and your stakeholders need to create complex information from projects, program, and portfolio reporting to utilizing time-phased data and, potentially, data from your enterprise?s other line-of-business tools. Get Project Online Data Select and mine relevant tables with ODATA Advanced ODATA data mining Importing other data formats Advanced Editing of data queries Advanced Data Transformations Managing table relationships Creating & using data hierarchies Creating custom columns and measures and metrics for filtering and reporting Creating Power BI Reports Using advanced visualizations Configuring drill-down Modifying visual interactions Importing and creating custom visuals Configure Power BI Security Creating Dashboard and row-level security Utilizing Filtering using row-level security Publishing Reports and Dashboards Building Mobile Reporting Creating and deploying content packs Configuring natural language query