Discover the foundational principles of Natural Language Processing (NLP) and how to leverage Microsoft Azure’s advanced AI services to build NLP-driven applications. This course provides a comprehensive introduction to NLP concepts, techniques, and the role of NLP in AI. You will learn how to utilize Azure’s powerful tools for text processing, tokenization, and language modeling to create intelligent, language-aware applications.

What You Will Learn:

• Introduction to NLP and Microsoft Azure: Get acquainted with Natural Language Processing and its significance in AI-driven applications. Understand how Microsoft Azure integrates with NLP to provide scalable and efficient solutions.
• Overview of Natural Language Processing (NLP): Explore the core principles of NLP, including how machines understand and interpret human language. Learn about key applications such as sentiment analysis, language translation, and text summarization.
• Role of NLP in AI-driven Applications: Discover how NLP contributes to various AI applications, enhancing user interactions and automating complex language-based tasks.
• Introduction to Microsoft Azure AI and NLP Services: Familiarize yourself with Azure’s suite of AI services designed for NLP, including Azure Cognitive Services and Azure Machine Learning, and understand their capabilities in processing and analyzing text data.
• Fundamentals of Natural Language Processing: Dive into essential NLP concepts and techniques, including text preprocessing, tokenization, and the use of language models.
• Key NLP Concepts and Techniques: Learn about critical techniques in NLP, such as named entity recognition, part-of-speech tagging, and dependency parsing.
• Text Preprocessing and Tokenization: Understand the steps involved in preparing text data for analysis, including cleaning, normalization, and breaking text into meaningful units.
• Language Models and Embeddings: Explore how language models and embeddings represent and process text data to capture semantic meaning and context, enabling more sophisticated NLP tasks.

Key Features:

• Comprehensive overview of NLP concepts and techniques with practical examples.
• Introduction to Microsoft Azure’s NLP services, providing hands-on experience with Azure’s AI tools.
• Detailed exploration of text preprocessing, tokenization, and language models for building NLP applications.

Who Should Take This Course:

• Developers and data scientists interested in integrating NLP capabilities into their applications using Azure.
• AI professionals and IT specialists looking to enhance their understanding of NLP and its implementation in cloud-based environments.
• Students and enthusiasts who want to gain practical knowledge of NLP and Azure’s AI services.

Prerequisites:

No prior experience with NLP or Azure is required. Basic knowledge of AI concepts is helpful but not essential.

Course Format:

• Duration: 2 hours
• Level: Beginner to Intermediate
• Delivery: Self-paced course with hands-on labs and real-world examples

By the end of this course, you'll be equipped to leverage Azure’s NLP services to build intelligent applications that understand and process human language with greater accuracy and efficiency.