54 Azure Machine Learning courses

Picture this: A vast cloud realm, brimming with data, all ready to weave tales of insight and wisdom. Welcome aboard our 'Microsoft Azure Machine Learning' odyssey! This isn't just a course; it's a canvas where technology meets art. Unravel the mysteries of Azure Machine Learning Studio, dance with data modules, and play with predictions about incomes and the price tags of fancy cars. Ready for a whirlwind romance with data? Learning Outcomes * Become best pals with Microsoft Azure Machine Learning Studio - it's cooler than it sounds! * Play detective with a variety of puzzling machine learning modules. * Predict tomorrow! Well, not literally, but we'll dabble in forecasting incomes and car prices. * Revel in the drama of data as we churn stories from raw numbers. * Flip through the fascinating pages of notebooks in Azure, a bibliophile's techy delight. WHY CHOOSE THIS MICROSOFT AZURE MACHINE LEARNING COURSE? * Unlimited access to the course for a lifetime. * Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. * Structured lesson planning in line with industry standards. * Immerse yourself in innovative and captivating course materials and activities. * Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. * Flexibility to complete the Microsoft Azure Machine Learning Course at your own pace, on your own schedule. * Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. WHO IS THIS MICROSOFT AZURE MACHINE LEARNING COURSE FOR? * Tech aficionados itching to ride the cloud wave. * Curious data wizards eager to add Azure spells to their grimoire. * Project champs on a quest for the perfect cloud platform. * Code artists seeking to stitch machine learning into their digital tapestry. * Future stars of tech, dreaming big and aiming higher. CAREER PATH * Azure Machine Learning Maestro - £45,000 - £65,000 * Data Alchemist - £50,000 - £72,000 * Cloud Castle Architect - £70,000 - £92,000 * Machine Learning Magician - £55,000 - £78,000 * Storyteller of Stats - £60,000 - £85,000 * Azure Artisan - £40,000 - £60,000 PREREQUISITES This Microsoft Azure Machine Learning does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Microsoft Azure Machine Learning 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. CERTIFICATION After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. COURSE CURRICULUM Azure Machine Learning Module 01: Introduction to Microsoft Azure Machine Learning Studio and Administration 00:22:00 Module 02: Various Modules in Machine Learning 00:13:00 Module 03: Prediction of Income (Automated Tutorial) 00:33:00 Module 04: Prediction of Automobile Price using Linear Regression Algorithm 00:59:00 Module 05: Dataset Processing and Analysis (Sample-1) 00:57:00 Module 06: Cross Validation for Regression (Sample-2) 00:28:00 Module 07: Clustering Group Iris data (Sample-3) 00:17:00 Module 08: Introduction on Notebook in Microsoft Azure Machine Learning Studio 00:18:00 Assignment Assignment - Microsoft Azure Machine Learning 00:00:00

Duration 1 Days 6 CPD hours This course is intended for The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don?t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful. This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. Prerequisites Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services. Specifically: * Experience using computers and the internet. * Interest in use cases for AI applications and machine learning models. * A willingness to learn through hands-on exp... 1 - FUNDAMENTAL AI CONCEPTS * Understand machine learning * Understand computer vision * Understand natural language processing * Understand document intelligence and knowledge mining * Understand generative AI * Challenges and risks with AI * Understand Responsible AI 2 - FUNDAMENTALS OF MACHINE LEARNING * What is machine learning? * Types of machine learning * Regression * Binary classification * Multiclass classification * Clustering * Deep learning * Azure Machine Learning 3 - FUNDAMENTALS OF AZURE AI SERVICES * AI services on the Azure platform * Create Azure AI service resources * Use Azure AI services * Understand authentication for Azure AI services 4 - FUNDAMENTALS OF COMPUTER VISION * Images and image processing * Machine learning for computer vision * Azure AI Vision 5 - FUNDAMENTALS OF FACIAL RECOGNITION * Understand Face analysis * Get started with Face analysis on Azure 6 - FUNDAMENTALS OF OPTICAL CHARACTER RECOGNITION * Get started with Vision Studio on Azure 7 - FUNDAMENTALS OF TEXT ANALYSIS WITH THE LANGUAGE SERVICE * Understand Text Analytics * Get started with text analysis 8 - FUNDAMENTALS OF QUESTION ANSWERING WITH THE LANGUAGE SERVICE * Understand question answering * Get started with the Language service and Azure Bot Service 9 - FUNDAMENTALS OF CONVERSATIONAL LANGUAGE UNDERSTANDING * Describe conversational language understanding * Get started with conversational language understanding in Azure 10 - FUNDAMENTALS OF AZURE AI SPEECH * Understand speech recognition and synthesis * Get started with speech on Azure 11 - FUNDAMENTALS OF AZURE AI DOCUMENT INTELLIGENCE * Explore capabilities of document intelligence * Get started with receipt analysis on Azure 12 - FUNDAMENTALS OF KNOWLEDGE MINING WITH AZURE COGNITIVE SEARCH * What is Azure Cognitive Search? * Identify elements of a search solution * Use a skillset to define an enrichment pipeline * Understand indexes * Use an indexer to build an index * Persist enriched data in a knowledge store * Create an index in the Azure portal * Query data in an Azure Cognitive Search index 13 - FUNDAMENTALS OF GENERATIVE AI * What is generative AI? * Large language models * What is Azure OpenAI? * What are copilots? * Improve generative AI responses with prompt engineering 14 - FUNDAMENTALS OF AZURE OPENAI SERVICE * What is generative AI * Describe Azure OpenAI * How to use Azure OpenAI * Understand OpenAI's natural language capabilities * Understand OpenAI code generation capabilities * Understand OpenAI's image generation capabilities * Describe Azure OpenAI's access and responsible AI policies 15 - 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 ADDITIONAL COURSE DETAILS: Nexus Humans AI-900T00 - Microsoft Azure AI Fundamentals 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-900T00 - Microsoft Azure AI Fundamentals 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.

The comprehensive Microsoft Azure Machine Learning 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 Microsoft Azure Machine Learning today, and learn from the very best the industry has to offer! This best selling Microsoft Azure Machine Learning has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Microsoft Azure Machine Learning is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Microsoft Azure Machine Learning 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 Microsoft Azure Machine Learning 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 Microsoft Azure Machine Learning, 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 Microsoft Azure Machine Learning 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 Microsoft Azure Machine Learning 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 4 Days 24 CPD hours This course is intended for This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. Overview Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow. Prerequisites Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Working with containers AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience. 1 - DESIGN A DATA INGESTION STRATEGY FOR MACHINE LEARNING PROJECTS * Identify your data source and format * Choose how to serve data to machine learning workflows * Design a data ingestion solution 2 - DESIGN A MACHINE LEARNING MODEL TRAINING SOLUTION * Identify machine learning tasks * Choose a service to train a machine learning model * Decide between compute options 3 - DESIGN A MODEL DEPLOYMENT SOLUTION * Understand how model will be consumed * Decide on real-time or batch deployment 4 - DESIGN A MACHINE LEARNING OPERATIONS SOLUTION * Explore an MLOps architecture * Design for monitoring * Design for retraining 5 - EXPLORE AZURE MACHINE LEARNING WORKSPACE RESOURCES AND ASSETS * Create an Azure Machine Learning workspace * Identify Azure Machine Learning resources * Identify Azure Machine Learning assets * Train models in the workspace 6 - EXPLORE DEVELOPER TOOLS FOR WORKSPACE INTERACTION * Explore the studio * Explore the Python SDK * Explore the CLI 7 - MAKE DATA AVAILABLE IN AZURE MACHINE LEARNING * Understand URIs * Create a datastore * Create a data asset 8 - WORK WITH COMPUTE TARGETS IN AZURE MACHINE LEARNING * Choose the appropriate compute target * Create and use a compute instance * Create and use a compute cluster 9 - WORK WITH ENVIRONMENTS IN AZURE MACHINE LEARNING * Understand environments * Explore and use curated environments * Create and use custom environments 10 - FIND THE BEST CLASSIFICATION MODEL WITH AUTOMATED MACHINE LEARNING * Preprocess data and configure featurization * Run an Automated Machine Learning experiment * Evaluate and compare models 11 - TRACK MODEL TRAINING IN JUPYTER NOTEBOOKS WITH MLFLOW * Configure MLflow for model tracking in notebooks * Train and track models in notebooks 12 - RUN A TRAINING SCRIPT AS A COMMAND JOB IN AZURE MACHINE LEARNING * Convert a notebook to a script * Run a script as a command job * Use parameters in a command job 13 - TRACK MODEL TRAINING WITH MLFLOW IN JOBS * Track metrics with MLflow * View metrics and evaluate models 14 - PERFORM HYPERPARAMETER TUNING WITH AZURE MACHINE LEARNING * Define a search space * Configure a sampling method * Configure early termination * Use a sweep job for hyperparameter tuning 15 - RUN PIPELINES IN AZURE MACHINE LEARNING * Create components * Create a pipeline * Run a pipeline job 16 - REGISTER AN MLFLOW MODEL IN AZURE MACHINE LEARNING * Log models with MLflow * Understand the MLflow model format * Register an MLflow model 17 - CREATE AND EXPLORE THE RESPONSIBLE AI DASHBOARD FOR A MODEL IN AZURE MACHINE LEARNING * Understand Responsible AI * Create the Responsible AI dashboard * Evaluate the Responsible AI dashboard 18 - DEPLOY A MODEL TO A MANAGED ONLINE ENDPOINT * Explore managed online endpoints * Deploy your MLflow model to a managed online endpoint * Deploy a model to a managed online endpoint * Test managed online endpoints 19 - DEPLOY A MODEL TO A BATCH ENDPOINT * Understand and create batch endpoints * Deploy your MLflow model to a batch endpoint * Deploy a custom model to a batch endpoint * Invoke and troubleshoot batch endpoints

Duration 1 Days 6 CPD hours This course is intended for This course is designed for data scientists with experience of Python who need to learn how to apply their data science and machine learning skills on Azure Databricks. Overview After completing this course, you will be able to: Provision an Azure Databricks workspace and cluster Use Azure Databricks to train a machine learning model Use MLflow to track experiments and manage machine learning models Integrate Azure Databricks with Azure Machine Learning Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this course, students will learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning. INTRODUCTION TO AZURE DATABRICKS * Getting Started with Azure Databricks * Working with Data in Azure Databricks TRAINING AND EVALUATING MACHINE LEARNING MODELS * Preparing Data for Machine Learning * Training a Machine Learning Model MANAGING EXPERIMENTS AND MODELS * Using MLflow to Track Experiments * Managing Models MANAGING EXPERIMENTS AND MODELS * Using MLflow to Track Experiments * Managing Models INTEGRATING AZURE DATABRICKS AND AZURE MACHINE LEARNING * Tracking Experiments with Azure Machine Learning * Deploying Models

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

Welcome to the world of machine learning, Java, and Python programming! This exciting bundle offers a comprehensive learning experience with a variety of courses that will equip you with the knowledge and skills needed to excel in these fields. Within this bundle, you will find a total of eight courses, including three QLS-endorsed courses and five relevant CPD QS-accredited courses. The three QLS-endorsed courses in this bundle are the Machine Learning with Python course, the Introduction to Java course, and the Diploma in Python Programming. These courses have been carefully curated and designed to provide you with a solid foundation in machine learning and programming using both Java and Python. Upon completion of these courses, you will receive hardcopy certificates to showcase your achievement. In addition to the QLS-endorsed courses, this bundle also includes five CPD QS-accredited courses. These courses are highly relevant to the field and will further enhance your understanding and expertise. They include Azure Machine Learning, Complete Python Machine Learning & Data Science Fundamentals, Machine Learning Model Using AWS SageMaker Canvas, Statistics & Probability for Data Science & Machine Learning, and 2021 Data Science & Machine Learning with R from A-Z. Key Features of the Machine Learning, Java and Python Programming Bundle: * 3 QLS-Endorsed Courses: We proudly offer 3 QLS-endorsed courses within our Machine Learning, Java and Python Programming bundle, providing you with industry-recognized qualifications. Plus, you'll receive a free hardcopy certificate for each of these courses. * QLS Course 01: Machine Learning with Python * QLS Course 02: Introduction to Java * QLS Course 03: Diploma in Python Programming * 5 CPD QS Accredited Courses: Additionally, our bundle includes 5 relevant CPD QS accredited courses, ensuring that you stay up-to-date with the latest industry standards and practices. * Course 01: Azure Machine Learning * Course 02: Complete Python Machine Learning & Data Science Fundamentals * Course 03: Machine Learning Model Using AWS SageMaker Canvas * Course 04: Statistics & Probability for Data Science & Machine Learning * Course 05: 2021 Data Science & Machine Learning with R from A-Z * In Addition, you'll get Five Career Boosting Courses absolutely FREE with this Bundle. * Course 01: Professional CV Writing * Course 02: Job Search Skills * Course 03: Self-Esteem & Confidence Building * Course 04: Professional Diploma in Stress Management * Course 05: Complete Communication Skills Master Class * Convenient Online Learning: Our Machine Learning, Java and Python Programming courses are accessible online, allowing you to learn at your own pace and from the comfort of your own home. Learning Outcomes: * Gain a comprehensive understanding of machine learning principles and algorithms. * Develop proficiency in programming with Python and Java, and apply these skills to real-world projects. * Explore the fundamentals of data science and statistical analysis. * Learn how to leverage cloud-based platforms, such as Azure and AWS, for machine learning tasks. * Build and deploy machine learning models using various frameworks and tools. * Acquire practical knowledge in data preprocessing, feature selection, and model evaluation techniques. * Gain expertise in using R for data science and machine learning applications. This bundle combines the power of machine learning, Java programming, and Python programming to provide you with a comprehensive skill set in these high-demand fields. With a total of eight courses, including three QLS-endorsed and five CPD QS-accredited courses, this bundle covers all the essential topics and techniques needed to succeed. Whether you are a beginner looking to enter the world of machine learning and programming or an experienced professional seeking to expand your knowledge and skills, this bundle has something for everyone. From understanding the fundamentals to applying advanced algorithms, you will gain a deep understanding of machine learning principles and the ability to develop robust applications using Java and Python. CPD 250 CPD hours / points Accredited by CPD Quality Standards WHO IS THIS COURSE FOR? * Individuals interested in starting a career in machine learning, Java programming, or Python programming. * Professionals seeking to enhance their skills and stay updated with the latest trends in these fields. * Students pursuing degrees in computer science, data science, or related disciplines. * Anyone looking to broaden their knowledge and explore the exciting field of machine learning and programming. CAREER PATH * Machine Learning Engineer: £45,000 - £90,000 per year * Data Scientist: £40,000 - £80,000 per year * Java Developer: £30,000 - £70,000 per year * Python Developer: £35,000 - £75,000 per year * Cloud Solutions Architect: £50,000 - £100,000 per year * Statistical Analyst: £35,000 - £65,000 per year CERTIFICATES DIGITAL CERTIFICATE Digital certificate - Included HARD COPY CERTIFICATE Hard copy certificate - Included

I Asked A Python Programmer For A Joke. He Said, 'Import Antigravity' | 10 QLS Endorsed Courses for Python Programmer | 10 QLS Endorsed Hard Copy Certificates Included | Lifetime Access | Installment Payment | Tutor Support

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.

10 QLS Endorsed Courses for Programming | 10 Endorsed Certificates Included | Life Time Access