Azure AI Engineer Online Training - AI-102 Certification Training

1. What are the core services included in Azure AI? Introduction: Azure AI is a comprehensive suite of artificial intelligence (AI) services and tools provided by Microsoft, designed to help organizations of all sizes incorporate AI into their applications and workflows without needing extensive coding expertise. The platform's core services cater to different AI capabilities such as machine learning, cognitive services, and automation, enabling users to harness the power of AI with minimal development effort. In this article, we’ll explore the core services included in Azure AI, with a focus on their features and how they can be leveraged by individuals and businesses without extensive coding knowledge. AI- 102 Certification Training 1. Azure Machine Learning Azure Machine Learning (Azure ML) is a cloud-based service that allows users to build, train, and deploy machine learning models. It provides a streamlined, end-to-end environment for machine learning, supporting both beginners and experienced professionals. Key Features: No-Code/Low-Code Environment: Azure ML Studio allows users to drag and drop components to create machine learning pipelines. This visual interface is perfect for those without coding skills, as it eliminates the need to write code to build and experiment with models. Automated Machine Learning (Auto ML): With Auto ML, users can automatically select the best models and algorithms based on the provided data. This reduces the complexity of model selection and tuning, making it accessible to those with minimal AI expertise.

2. Model Training and Deployment: Once models are created, Azure ML provides tools for deploying them in a scalable manner. Users can deploy models as APIs that can be easily integrated into applications. AI-102 Microsoft Azure AI Training Integration with Popular Tools: For those who do have coding knowledge, Azure ML integrates seamlessly with popular data science tools such as Python, Jupiter Notebooks, and R. Use Cases: Predictive analytics for businesses to forecast trends. Automated customer segmentation based on past behaviour. 2. Azure Cognitive Services Azure Cognitive Services is a collection of APIs that provide pre-built models for vision, speech, language, and decision-making AI capabilities. These services allow developers to integrate AI into their applications without needing to build and train models from scratch. Key Cognitive Service Categories:  Vision: Services like Computer Vision, Face API, and Custom Vision allow users to analyse images, detect objects, and recognize faces. These APIs are useful for a range of applications, such as automating quality control processes in manufacturing or enhancing security systems with facial recognition.  Speech: Azure offers Speech-to-Text, Text-to-Speech, and Speech Translation services that can be used to add conversational AI capabilities to apps. These services enable automatic transcription, real-time translation, and voice-based interaction without requiring specialized development expertise.  Language: Natural Language Processing (NLP) services like Text Analytics, Translator, and Language Understanding (LUIS) help in understanding and generating human language. These are ideal for creating chat bots, sentiment analysis tools, or translation services. Azure AI-102 Training in Hyderabad  Decision: These services, such as Personalizer and Anomaly Detector, provide intelligent decision-making capabilities recommendations or identifying anomalies in real-time. by analysing data and making No-Code Capabilities:  All cognitive services can be accessed via APIs, which can be integrated into applications through simple HTTP requests. For those who prefer a visual interface, services like Custom Vision provide a web-based portal where users can upload images and train models without writing any code. Use Cases:  Automating customer service through AI-driven chat bots.  Enhancing accessibility with speech-to-text features for the hearing impaired. 3. Azure Bot Service

3. Azure Bot Service allows users to create conversational AI (chat bots) for use across various platforms, such as websites, Microsoft Teams, Slack, and more. It integrates with Bot Framework Composer, a visual design tool that simplifies the chat bot development process. Key Features:  Low-Code/No-Code Development: Bot Framework Composer offers a drag-and-drop interface where users can design conversation flows and logic without needing to write code.  Multi-Channel Integration: Bots created using Azure Bot Service can be deployed across multiple platforms with minimal configuration, ensuring seamless communication with users no matter where they interact.  AI-Driven Interactions: By integrating with Azure Cognitive Services (such as LUIS for language understanding), chat bots can have more natural conversations and understand context better. Azure AI-102 Training Institute in Hyderabad Use Cases:  Creating customer support catboats that resolve queries without human intervention.  Automating internal help desks for IT support within organizations. 4. Azure Form Recognizer Azure Form Recognizer is a specialized AI service that automates data extraction from documents such as forms, invoices, and receipts. By leveraging AI models that have been pre- trained to recognize specific types of documents, users can automate data entry tasks without writing complex code. Key Features:  Document Processing with No-Code: Users can upload documents via a web interface, and the service will extract relevant data such as names, dates, or amounts. This reduces the time spent on manual data entry.  Custom Models: Form Recognizer allows for custom models to be trained on specific document types by providing a few sample documents. Azure AI-102 Online Training  Pre-built Models: For common document types like receipts and invoices, pre-built models are available, meaning users can get started without any setup or training. Use Cases:  Automating invoice processing and reducing manual entry errors.  Extracting data from scanned documents for archival purposes. 5. Azure Open AI Service Azure Open AI Service brings the power of GPT-3 and other large language models to Azure, allowing users to build AI applications that understand and generate natural language. Key Features:

4. Customizable Language Models: While the underlying models are already pre- trained on vast amounts of data, Azure Open AI Service allows users to fine-tune them for specific use cases, such as customer support or content creation. No-Code Interfaces: The service can be used via APIs, allowing developers to integrate it into applications without needing to understand the underlying machine learning mechanisms. Microsoft Azure AI Engineer Training Use Cases:  Automating content generation for blogs, marketing materials, or product descriptions.  Creating AI assistants that can hold human-like conversations. Conclusion Azure AI offers a wide array of services that make it easy for businesses and individuals to integrate AI capabilities into their workflows and applications without extensive coding knowledge. Azure Machine Learning, Cognitive Services, Bot Service, Form Recognizer, and Azure Open AIService all provide powerful tools with user-friendly, low-code/no-code interfaces. These services democratize AI, allowing users from various backgrounds to leverage AI technologies and accelerate innovation. From automating customer service with catboats to extracting data from documents, Azure AI’s core services empower organizations to be more efficient, innovative, and competitive regardless of their technical expertise. Visualpath is the Best Software Online Training Institute in Hyderabad. Avail complete Azure AI Engineer Associate (AI-102) worldwide. You will get the best course at an affordable cost. Attend Free Demo Call on - +91-9989971070. WhatsApp: https://www.whatsapp.com/catalog/917032290546/ Visit https://visualpathblogs.com/ Visit:https://visualpath.in/microsoft-azure-ai-102-online-training.html