AI-3003: Training Build a natural language processing solution with Azure AI Services

Course: 3003

Learn how Build a natural language processing solution with Azure AI Services

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March 10

9:00 AM – 4:00 PM CST

April 7

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May 5

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June 9

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July 7

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August 11

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September 15

9:00 AM – 4:00 PM CST

October 13

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Natural Language Processing Solution with Azure AI
Natural Language Processing Solution with Azure AI

Overview

Learn how to use Build a natural language processing solution with Azure AI Services

Audience Profile

There are no prerequisites for this course. This course is ideal for data scientists, AI engineers, and developers who want to create custom AI solutions using Azure AI Studio. Whether you are just getting started with AI or are an experienced professional who wants to build advanced AI applications, this course provides you with the practical skills and knowledge to harness the power of generative AI in your own projects!

Course Overview

This course, AI-3003, provides an in-depth exploration of natural language processing (NLP) techniques and how to implement them using Azure AI Services. Participants will learn foundational NLP concepts, advanced techniques, and practical skills for building and deploying NLP solutions in various applications.

Course Objectives

By the end of this course, participants will be able to:

  1. Understand the fundamental concepts of natural language processing.
  2. Use Azure AI Services to develop NLP models.
  3. Apply NLP techniques in real-world applications.
  4. Deploy and monitor NLP solutions on Azure.

Course Outline

Module 1: Introduction to Natural Language Processing

  • Overview of NLP and its applications
  • Key challenges in NLP and their solutions
  • Understanding NLP terminology and concepts

Module 2: Setting Up Azure for NLP

  • Introduction to Azure AI Services
  • Setting up an Azure account and resource management
  • Overview of Azure Cognitive Services for NLP

Module 3: Text Preprocessing and Data Preparation

  • Text tokenization, lemmatization, and stemming
  • Stop words, punctuation removal, and text normalization
  • Data cleansing and feature extraction for NLP

Module 4: Understanding Language Models

  • Overview of language models and their applications
  • Introduction to pre-trained models (BERT, GPT, T5)
  • Fine-tuning language models for specific tasks using Azure Machine Learning

Module 5: Sentiment Analysis with Azure Cognitive Services

  • Overview of sentiment analysis in NLP
  • Using Azure Text Analytics for sentiment analysis
  • Hands-on: Building a sentiment analysis application

Module 6: Entity Recognition and Named Entity Recognition (NER)

  • Understanding entity recognition and NER
  • Using Azure Text Analytics for entity recognition
  • Hands-on: Extracting entities from text using Azure AI

Module 7: Building a Custom NLP Model

  • Introduction to custom model development on Azure
  • Using Azure Machine Learning to train custom NLP models
  • Model evaluation and optimization techniques

Module 8: Implementing Language Translation

  • Overview of language translation with NLP
  • Using Azure Translator Text API for translation tasks
  • Hands-on: Building a translation tool with Azure AI

Module 9: Speech-to-Text and Text-to-Speech Solutions

  • Introduction to speech-to-text and text-to-speech technology
  • Using Azure Speech Services for NLP applications
  • Hands-on: Converting audio to text and vice versa with Azure AI

Module 10: Deploying NLP Solutions

  • Packaging and deploying NLP models on Azure
  • Using Azure Kubernetes Service (AKS) for NLP model deployment
  • Hands-on: Deploying a custom NLP model as a web service

Module 11: Monitoring and Improving NLP Models

  • Model monitoring and performance evaluation
  • Implementing model retraining and updates
  • Best practices for maintaining NLP solutions on Azure

Module 12: Real-World Applications and Case Studies

  • Industry case studies of NLP applications
  • Group discussion on real-world NLP challenges
  • Final project: Building and deploying an end-to-end NLP solution on Azure

Assessment

  • Quizzes: After each module to reinforce learning.
  • Hands-on Labs: Practical exercises for building and deploying NLP solutions.
  • Final Project: Develop a complete NLP solution using Azure AI Services.

Prerequisites

  • Basic knowledge of Python programming.
  • Familiarity with machine learning concepts is recommended.
  • An active Azure account for hands-on practice.

 

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