58 Computer Vision courses

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

Learn to build highly sophisticated deep learning and Computer Vision applications with PyTorch

In today's world, artificial intelligence is used widely to save time and work more professionally. If you are

Computer vision (CV), a subfield of computer science, focuses on replicating the complex functionalities of the human visual system. This course provides a comprehensive understanding of Computer Vision from the beginning using Python and helps you in becoming an expert.

24 Hour Flash Deal **25-in-1 Computer Vision: C++ and OpenCV with GPU support Mega Bundle** Computer Vision: C++ and OpenCV with GPU support Enrolment Gifts **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter ** Take the initial steps toward a successful long-term career by studying the Computer Vision: C++ and OpenCV with GPU support package online with Studyhub through our online learning platform. The Computer Vision: C++ and OpenCV with GPU support bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass. This Computer Vision: C++ and OpenCV with GPU support course provides complete 360-degree training on Computer Vision: C++ and OpenCV with GPU support. You'll get not one, not two, not three, but twenty-five Computer Vision: C++ and OpenCV with GPU support courses included in this course. Plus Studyhub's signature Forever Access is given as always, meaning these Computer Vision: C++ and OpenCV with GPU support courses are yours for as long as you want them once you enrol in this course This Computer Vision: C++ and OpenCV with GPU support Bundle consists the following career oriented courses: * Course 01: Computer Vision: C++ and OpenCV with GPU support * Course 02: Python 3 Programming * Course 03: Machine Learning Course with Python * Course 04: Data Science & Machine Learning with R * Course 05: Robotics - Sensors * Course 06: Digital Electric Circuits & Intelligent Electrical Devices * Course 07: AutoCAD Programming using VB.NET with Windows Forms * Course 08: Learn MySQL from Scratch for Data Science and Analytics * Course 09: Data Structure * Course 10: Electronic Device and Circuits Protection Training * Course 11: Computer Science with Python Course * Course 12: IT Administration and Networking * Course 13: Foundations of IT Security: Protecting Digital Assets * Course 14: SQL Database Management * Course 15: Deep Learning Neural Network with R * Course 16: Computer Networks Security from Scratch to Advanced * Course 17: Electronic & Electrical Devices Maintenance & Troubleshooting * Course 18: Embedded Systems with 8051 Microcontroller * Course 19: MATLAB Simulink for Electrical Power Engineering * Course 20: Solidworks: Beginner to Advanced * Course 21: Info Graphics Web Design - Affinity Designer Training * Course 22: Diploma in Python Programming * Course 23: Penetration Testing with OWASP ZAP: Mastery course * Course 24: Unreal Engine 4 * Course 25: Blender 3D Character Modeling & Rendering The Computer Vision: C++ and OpenCV with GPU support course has been prepared by focusing largely on Computer Vision: C++ and OpenCV with GPU support career readiness. 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Here's what you get: * Step by step Computer Vision: C++ and OpenCV with GPU support lessons * One to one assistance from Computer Vision: C++ and OpenCV with GPU supportprofessionals if you need it * Innovative exams to test your knowledge after the Computer Vision: C++ and OpenCV with GPU supportcourse * 24/7 customer support should you encounter any hiccups * Top-class learning portal * Unlimited lifetime access to all twenty-five Computer Vision: C++ and OpenCV with GPU support courses * Digital Certificate, Transcript and student ID are all included in the price * PDF certificate immediately after passing * Original copies of your Computer Vision: C++ and OpenCV with GPU support certificate and transcript on the next working day * Easily learn the Computer Vision: C++ and OpenCV with GPU support skills and knowledge you want from the comfort of your home CPD 250 CPD hours / points Accredited by CPD Quality Standards WHO IS THIS COURSE FOR? This Computer Vision: C++ and OpenCV with GPU support training is suitable for - * Students * Recent graduates * Job Seekers * Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Computer Vision: C++ and OpenCV with GPU support REQUIREMENTS To participate in this Computer Vision: C++ and OpenCV with GPU support course, all you need is - * A smart device * A secure internet connection * And a keen interest in Computer Vision: C++ and OpenCV with GPU support CAREER PATH You will be able to kickstart your Computer Vision: C++ and OpenCV with GPU support career because this course includes various courses as a bonus. This Computer Vision: C++ and OpenCV with GPU support is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Computer Vision: C++ and OpenCV with GPU support career opportunities. CERTIFICATES CPD ACCREDITED CERTIFICATE Digital certificate - Included * CPD Accredited e-Certificate - Free * CPD Accredited Hardcopy Certificate - Free * Enrolment Letter - Free * Student ID Card - Free

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The Computer Vision course with C++ and OpenCV with GPU support provides an introduction to computer vision and its applications using C++ and OpenCV with GPU acceleration. Students will learn about setting up the necessary environments, basic examples, background segmentation, object detection with OpenCV's ML module using C++ and CUDA, and optical flow. LEARNING OUTCOMES: 1. Set up the required environments for C++ and OpenCV with GPU support. 2. Understand the fundamentals of computer vision and its applications. 3. Implement background segmentation techniques to extract relevant objects from the environment. 4. Use OpenCV's ML module with C++ and CUDA to perform object detection efficiently. 5. Apply optical flow algorithms to track object movements and analyze motion patterns. WHY BUY THIS COMPUTER VISION: C++ AND OPENCV WITH GPU SUPPORT? 1. Unlimited access to the course for forever 2. Digital Certificate, Transcript, student ID all included in the price 3. Absolutely no hidden fees 4. Directly receive CPD accredited qualifications after course completion 5. Receive one to one assistance on every weekday from professionals 6. Immediately receive the PDF certificate after passing 7. Receive the original copies of your certificate and transcript on the next working day 8. Easily learn the skills and knowledge from the comfort of your home CERTIFICATION After studying the course materials of the Computer Vision: C++ and OpenCV with GPU support 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 COURSE FOR? This Computer Vision: C++ and OpenCV with GPU support course is ideal for * Students * Recent graduates * Job Seekers * Anyone interested in this topic * People already working in the relevant fields and want to polish their knowledge and skill. PREREQUISITES This Computer Vision: C++ and OpenCV with GPU support does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Computer Vision: C++ and OpenCV with GPU support 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 As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Computer Vision: C++ and OpenCV with GPU support is a great way for you to gain multiple skills from the comfort of your home. COURSE CURRICULUM Unit 01: Set up Necesssary Environments Module 01: Driver installation 00:06:00 Module 02: Cuda toolkit installation 00:01:00 Module 03: Compile OpenCV from source with CUDA support part-1 00:06:00 Module 04: Compile OpenCV from source with CUDA support part-2 00:05:00 Module 05: Python environment for flownet2-pytorch 00:09:00 Unit 02: Introduction with a few basic examples! Module 01: Read camera & files in a folder (C++) 00:11:00 Module 02: Edge detection (C++) 00:08:00 Module 03: Color transformations (C++) 00:07:00 Module 04: Using a trackbar (C++) 00:06:00 Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++) 00:13:00 Unit 03: Background segmentation Module 01: Background segmentation with MOG (C++) 00:04:00 Module 02: MOG and MOG2 cuda implementation (C++ - CUDA) 00:03:00 Module 03: Special app: Track class 00:06:00 Module 04: Special app: Track bgseg Foreground objects 00:08:00 Unit 04: Object detection with openCV ML module (C++ CUDA) Module 01: A simple application to prepare dataset for object detection (C++) 00:08:00 Module 02: Train model with openCV ML module (C++ and CUDA) 00:13:00 Module 03: Object detection with openCV ML module (C++ CUDA) 00:06:00 Unit 05: Optical Flow Module 01: Optical flow with Farneback (C++) 00:08:00 Module 02: Optical flow with Farneback (C++ CUDA) 00:06:00 Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA) 00:05:00 Module 04: Optical flow with Nvidia Flownet2 (Python) 00:05:00 Module 05: Performance Comparison 00:07:00 Additional Resource Resources - Computer Vision: C++ and OpenCV with GPU support 00:00:00 Assignment Assignment - Computer Vision: C++ and OpenCV with GPU support 00:00:00

OVERVIEW This comprehensive course on Computer Vision: C++ and OpenCV with GPU support will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Computer Vision: C++ and OpenCV with GPU support comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. HOW WILL I GET MY CERTIFICATE? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. WHO IS THIS COURSE FOR? There is no experience or previous qualifications required for enrolment on this Computer Vision: C++ and OpenCV with GPU support. It is available to all students, of all academic backgrounds. REQUIREMENTS Our Computer Vision: C++ and OpenCV with GPU support is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. CAREER PATH Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. COURSE CURRICULUM 5 sections • 22 lectures • 02:31:00 total length •Module 01: Driver installation: 00:06:00 •Module 02: Cuda toolkit installation: 00:01:00 •Module 03: Compile OpenCV from source with CUDA support part-1: 00:06:00 •Module 04: Compile OpenCV from source with CUDA support part-2: 00:05:00 •Module 05: Python environment for flownet2-pytorch: 00:09:00 •Module 01: Read camera & files in a folder (C++): 00:11:00 •Module 02: Edge detection (C++): 00:08:00 •Module 03: Color transformations (C++): 00:07:00 •Module 04: Using a trackbar (C++): 00:06:00 •Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++): 00:13:00 •Module 01: Background segmentation with MOG (C++): 00:04:00 •Module 02: MOG and MOG2 cuda implementation (C++ - CUDA): 00:03:00 •Module 03: Special app: Track class: 00:06:00 •Module 04: Special app: Track bgseg Foreground objects: 00:08:00 •Module 01: A simple application to prepare dataset for object detection (C++): 00:08:00 •Module 02: Train model with openCV ML module (C++ and CUDA): 00:13:00 •Module 03: Object detection with openCV ML module (C++ CUDA): 00:06:00 •Module 01: Optical flow with Farneback (C++): 00:08:00 •Module 02: Optical flow with Farneback (C++ CUDA): 00:06:00 •Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA): 00:05:00 •Module 04: Optical flow with Nvidia Flownet2 (Python): 00:05:00 •Module 05: Performance Comparison: 00:07:00

This course is a quick starter for anyone looking to delve into optical character recognition, image recognition, object detection, and object recognition using Python without having to deal with all the complexities and mathematics associated with a typical deep learning process.

This course is designed for beginners or anyone who wants to get started with Python-based face recognition. In this course, you will learn how to perform face detection from images, face detection from real-time videos, emotion detection, age-gender prediction, face recognition from images and real-time videos, and more!