104 Natural Language Processing (NLP) courses

The comprehensive Complete U&P AI - Natural Language Processing (NLP) with Python has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Complete U&P AI - Natural Language Processing (NLP) with Python today, and learn from the very best the industry has to offer! This best selling Complete U&P AI - Natural Language Processing (NLP) with Python has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Complete U&P AI - Natural Language Processing (NLP) with Python is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Complete U&P AI - Natural Language Processing (NLP) with Python is CPD-accredited, so you can be confident you're completing a quality training course  will boost your CV and enhance your career potential. The Complete U&P AI - Natural Language Processing (NLP) with Python is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Complete U&P AI - Natural Language Processing (NLP) with Python, you will be awarded a certificate of completion  as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Complete U&P AI - Natural Language Processing (NLP) with Python will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Complete U&P AI - Natural Language Processing (NLP) with Python to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.  Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

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.

Take your first step toward Natural Language Processing with this beginner-to-pro course. Gain an in-depth understanding of deep learning models for NLP with the help of examples. Learn the essential concepts from the absolute beginning with complete unraveling along with examples in Python.

This course will help you prepare for the AI-900 Exam: Microsoft Azure AI Fundamentals. We will cover the complete exam syllabus as updated in April 2021 with sample questions.

Duration 1 Days 6 CPD hours This course is intended for The audience for this course includes software developers and data scientists who need to use large language models for generative AI. Some programming experience is recommended, but the course will be valuable to anyone seeking to understand how the Azure OpenAI service can be used to implement generative AI solutions. Note Generative AI is a fast-evolving field of artificial intelligence, and the Azure OpenAI service is subject to frequent changes. The course materials are maintained to reflect the latest version of the service at the time of writing. Azure OpenAI Service provides access to OpenAI's powerful large language models such as GPT; the model behind the popular ChatGPT service. These models enable various natural language processing (NLP) solutions to understand, converse, and generate content. Users can access the service through REST APIs, SDKs, and Azure OpenAI Studio. In this course, you'll learn how to provision Azure OpenAI service, deploy models, and use them in generative AI applications. Prerequisites * Familiarity with Azure and the Azure portal. * Experience programming with C# or Python. 1 - GET STARTED WITH AZURE OPENAI SERVICE * Access Azure OpenAI Service * Use Azure OpenAI Studio * Explore types of generative AI models * Deploy generative AI models * Use prompts to get completions from models * Test models in Azure OpenAI Studio's playgrounds 2 - BUILD NATURAL LANGUAGE SOLUTIONS WITH AZURE OPENAI SERVICE * Integrate Azure OpenAI into your app * Use Azure OpenAI REST API * Use Azure OpenAI SDK 3 - APPLY PROMPT ENGINEERING WITH AZURE OPENAI SERVICE * Understand prompt engineering * Write more effective prompts * Provide context to improve accuracy 4 - GENERATE CODE WITH AZURE OPENAI SERVICE * Construct code from natural language * Complete code and assist the development process * Fix bugs and improve your code 5 - GENERATE IMAGES WITH AZURE OPENAI SERVICE * What is DALL-E? * Explore DALL-E in Azure OpenAI Studio * Use the Azure OpenAI REST API to consume DALL-E models 6 - USE YOUR OWN DATA WITH AZURE OPENAI SERVICE * Understand how to use your own data * Add your own data source * Chat with your model using your own data ADDITIONAL COURSE DETAILS: Nexus Humans AI-050T00: Develop Generative AI Solutions with Azure OpenAI Service 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 AI-050T00: Develop Generative AI Solutions with Azure OpenAI Service 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 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - PREPARE TO DEVELOP AI SOLUTIONS ON AZURE * Define artificial intelligence * Understand AI-related terms * Understand considerations for AI Engineers * Understand considerations for responsible AI * Understand capabilities of Azure Machine Learning * Understand capabilities of Azure AI Services * Understand capabilities of the Azure Bot Service * Understand capabilities of Azure Cognitive Search 2 - CREATE AND CONSUME AZURE AI SERVICES * Provision an Azure AI services resource * Identify endpoints and keys * Use a REST API * Use an SDK 3 - SECURE AZURE AI SERVICES * Consider authentication * Implement network security 4 - MONITOR AZURE AI SERVICES * Monitor cost * Create alerts * View metrics * Manage diagnostic logging 5 - DEPLOY AZURE AI SERVICES IN CONTAINERS * Understand containers * Use Azure AI services containers 6 - ANALYZE IMAGES * Provision an Azure AI Vision resource * Analyze an image * Generate a smart-cropped thumbnail 7 - CLASSIFY IMAGES * Provision Azure resources for Azure AI Custom Vision * Understand image classification * Train an image classifier 8 - DETECT, ANALYZE, AND RECOGNIZE FACES * Identify options for face detection analysis and identification * Understand considerations for face analysis * Detect faces with the Azure AI Vision service * Understand capabilities of the face service * Compare and match detected faces * Implement facial recognition 9 - READ TEXT IN IMAGES AND DOCUMENTS WITH THE AZURE AI VISION SERVICE * Explore Azure AI Vision options for reading text * Use the Read API 10 - ANALYZE VIDEO * Understand Azure Video Indexer capabilities * Extract custom insights * Use Video Analyzer widgets and APIs 11 - ANALYZE TEXT WITH AZURE AI LANGUAGE * Provision an Azure AI Language resource * Detect language * Extract key phrases * Analyze sentiment * Extract entities * Extract linked entities 12 - BUILD A QUESTION ANSWERING SOLUTION * Understand question answering * Compare question answering to Azure AI Language understanding * Create a knowledge base * Implement multi-turn conversation * Test and publish a knowledge base * Use a knowledge base * Improve question answering performance 13 - BUILD A CONVERSATIONAL LANGUAGE UNDERSTANDING MODEL * Understand prebuilt capabilities of the Azure AI Language service * Understand resources for building a conversational language understanding model * Define intents, utterances, and entities * Use patterns to differentiate similar utterances * Use pre-built entity components * Train, test, publish, and review a conversational language understanding model 14 - CREATE A CUSTOM TEXT CLASSIFICATION SOLUTION * Understand types of classification projects * Understand how to build text classification projects 15 - CREATE A CUSTOM NAMED ENTITY EXTRACTION SOLUTION * Understand custom named entity recognition * Label your data * Train and evaluate your model 16 - TRANSLATE TEXT WITH AZURE AI TRANSLATOR SERVICE * Provision an Azure AI Translator resource * Specify translation options * Define custom translations 17 - CREATE SPEECH-ENABLED APPS WITH AZURE AI SERVICES * Provision an Azure resource for speech * Use the Azure AI Speech to Text API * Use the text to speech API * Configure audio format and voices * Use Speech Synthesis Markup Language 18 - TRANSLATE SPEECH WITH THE AZURE AI SPEECH SERVICE * Provision an Azure resource for speech translation * Translate speech to text * Synthesize translations 19 - CREATE AN AZURE AI SEARCH SOLUTION * Manage capacity * Understand search components * Understand the indexing process * Search an index * Apply filtering and sorting * Enhance the index 20 - CREATE A CUSTOM SKILL FOR AZURE AI SEARCH * Create a custom skill * Add a custom skill to a skillset 21 - CREATE A KNOWLEDGE STORE WITH AZURE AI SEARCH * Define projections * Define a knowledge store 22 - PLAN AN AZURE AI DOCUMENT INTELLIGENCE SOLUTION * Understand AI Document Intelligence * Plan Azure AI Document Intelligence resources * Choose a model type 23 - USE PREBUILT AZURE AI DOCUMENT INTELLIGENCE MODELS * Understand prebuilt models * Use the General Document, Read, and Layout models * Use financial, ID, and tax models 24 - EXTRACT DATA FROM FORMS WITH AZURE DOCUMENT INTELLIGENCE * What is Azure Document Intelligence? * Get started with Azure Document Intelligence * Train custom models * Use Azure Document Intelligence models * Use the Azure Document Intelligence Studio 25 - GET STARTED WITH AZURE OPENAI SERVICE * Access Azure OpenAI Service * Use Azure OpenAI Studio * Explore types of generative AI models * Deploy generative AI models * Use prompts to get completions from models * Test models in Azure OpenAI Studio's playgrounds 26 - BUILD NATURAL LANGUAGE SOLUTIONS WITH AZURE OPENAI SERVICE * Integrate Azure OpenAI into your app * Use Azure OpenAI REST API * Use Azure OpenAI SDK 27 - APPLY PROMPT ENGINEERING WITH AZURE OPENAI SERVICE * Understand prompt engineering * Write more effective prompts * Provide context to improve accuracy 28 - GENERATE CODE WITH AZURE OPENAI SERVICE * Construct code from natural language * Complete code and assist the development process * Fix bugs and improve your code 29 - GENERATE IMAGES WITH AZURE OPENAI SERVICE * What is DALL-E? * Explore DALL-E in Azure OpenAI Studio * Use the Azure OpenAI REST API to consume DALL-E models 30 - USE YOUR OWN DATA WITH AZURE OPENAI SERVICE * Understand how to use your own data * Add your own data source * Chat with your model using your own data 31 - FUNDAMENTALS OF RESPONSIBLE GENERATIVE AI * Plan a responsible generative AI solution * Identify potential harms * Measure potential harms * Mitigate potential harms * Operate a responsible generative AI solution

In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks (RNNs). You will learn about sequence data, forecasting, Elman Unit, GRU, and LSTM. You will also learn how to work with image classification and how to get stock return predictions using LSTMs. We will also cover Natural Language Processing (NLP) and learn about text preprocessing and classification.

Master Data Science skills using Python and real time project and go from Beginner to Super Advance level

In this self-paced course, you will learn how to use TensorFlow 2 to build convolutional neural networks (CNNs). You will learn how to apply CNNs to several practical image recognition datasets and learn about techniques that help improve performance, such as batch normalization, data augmentation, and transfer learning.

This course will help you learn the programming fundamentals with Python 3. It is designed for beginners in Python and is a complete masterclass. This course will help you understand Python GUI, data science, full-stack web development with Django, machine learning, artificial intelligence, Natural Language Processing, and Computer Vision.