Text Analytics with Azure and Python: Sentiment and Key Phrase Extraction
Learn to extract emotional tone and critical keywords from unstructured text using Azure AI services and modern Python SDKs.
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Unstructured text data is growing rapidly, but extracting meaningful insights from customer reviews, feedback, and social media can be overwhelming. This written course guides you through unlocking the power of Natural Language Processing using Azure's cloud-based text analytics and Python. By reading through clear explanations and practicing with step-by-step code snippets, you will transition from a beginner to confidently building text analysis workflows that analyze sentiment and extract key phrases automatically. What you'll learn: Understand foundational NLP concepts, including sentiment scoring, opinion mining, and key phrase extraction; Configure Azure Text Analytics resources and manage API credentials securely; Write clean Python code using modern SDKs and type hints to send text data to the cloud; Analyze text to determine positive, negative, or neutral sentiment at both document and sentence levels; Extract key phrases to quickly summarize the main topics of large text volumes; Practice handling API responses, parsing JSON structures, and managing rate limits. The course starts with essential terminology and setup before walking you through practical, written coding exercises that demonstrate real-world text analysis workflows. This course is designed for beginner developers, data enthusiasts, and analysts who want to learn text mining without needing a deep background in machine learning. No prior cloud experience is required, though basic Python familiarity is helpful. Start reading today to turn raw text into actionable business intelligence.
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