Natural Language Processing in Microsoft Azure from Coursera

Natural language processing supports applications that can see, hear, speak with, and understand users. Using text analytics, translation, and language understanding services, Microsoft Azure makes it easy to build applications that support natural language.

In this course, you will learn how to use the Text Analytics service for advanced natural language processing of raw text for sentiment analysis, key phrase extraction, named entity recognition, and language detection. You will learn how to recognize and synthesize speech by using Azure Cognitive Services. You will gain an understanding of how automated translation capabilities in an AI solution enable closer collaboration by removing language barriers. You will be introduced to the Language Understanding service, and shown how to create applications that understand language.

This course will help you prepare for Exam AI-900: Microsoft Azure AI Fundamentals. This is the fourth course in a five-course program that prepares you to take the AI-900 certification exam. This course teaches you the core concepts and skills that are assessed in the AI fundamentals exam domains.

This beginner course is suitable for IT personnel who are just beginning to work with Microsoft Azure and want to learn about Microsoft Azure offerings and get hands-on experience with the product. Microsoft Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Microsoft Azure Data Scientist Associate or Microsoft Azure AI Engineer Associate, but it is not a prerequisite for any of them.

This course is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience is not required; however, some general programming knowledge or experience would be beneficial. To be successful in this course, you need to have basic computer literacy and proficiency in the English language. You should be familiar with basic computing concepts and terminology, general technology concepts, including machine learning and artificial intelligence concepts.

What's inside

Syllabus

Text and Speech Processing with Azure AI Services

In this module, you will learn how to use the Text Analytics service for advanced natural language processing over raw text for sentiment analysis, key phrase extraction, named entity recognition, and language detection. You will also learn how to recognize and synthesize speech by using Azure Cognitive Services.

Work with Language in Azure AI

In this module, we'll introduce you to the Language Understanding service, and show how to create applications that understand language.

Explore conversational AI

In this module, you will learn how to use Conversational AI ito create artificial intelligence workloads that deals with dialogs between AI agents and human users.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Suitable for absolute beginners to Microsoft Azure who want to learn about the product and gain hands-on experience

Fosters fluency in the English language

Develops foundational knowledge for learners who want to take the Microsoft Azure AI Fundamentals Exam

Advisable to have some general programming knowledge or experience

Does not require data science or software engineering experience

Reviews summary

Well-received azure nlp course

Learners say that this Natural Language Processing in Microsoft Azure course is great for beginners. According to students, the course provides a good and basic foundation in NLP. Learners especially appreciate the simple and engaging lessons. Most find that the exams and assignments are fair and helpful as well.

Assessments aid in understanding.

"Excellent"

"VG !"

Great for those new to NLP.

"Good for beginners because it is veru basic."

"Good basic knowledge about NPL for beginner"

Materials are easy to understand

"simple and great"

"Incredible thanks"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Natural Language Processing in Microsoft Azure with these activities:

Review Pre-Requisite Text Analytics Skills

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Refreshes skills in pre-requisite text mining skills needed for this course.

Browse courses on Natural Language Processing

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Review key text mining concepts such as tokenization, stemming, and lemmatization.
Complete practice problems in text mining using a programming language of your choice.

Read 'Natural Language Processing with Python' by Bird et al.

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Provides a comprehensive overview of NLP concepts and techniques, complementing the course materials.

View Natural Language Processing with Python:... on Amazon

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Read the relevant chapters on text mining, natural language understanding, and machine learning.
Complete the exercises and practice problems in the book.

Complete Microsoft Learn Modules on Text Analytics

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Provides hands-on experience with Microsoft's Azure Text Analytics service, a core component of this course.

Browse courses on Azure Cognitive Services

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Create an Azure account and provision a Text Analytics service.
Follow the Microsoft Learn modules on Text Analytics, completing the exercises and quizzes.
Experiment with different text analytics scenarios using the Text Analytics API.

Five other activities

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Join a Study Group for Collaborative Learning

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Provides opportunities to discuss course materials, clarify concepts, and reinforce learning through group discussions.

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Join or create a study group with other students enrolled in the course.
Schedule regular meetings to discuss assigned readings, concepts, and practice problems.
Facilitate peer-to-peer learning by taking turns presenting topics and leading discussions.

Attend an Azure AI Workshop

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Offers hands-on exposure to Azure AI technologies, enhancing practical understanding of course concepts.

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Identify and register for an Azure AI workshop.
Attend the workshop and actively participate in the exercises and discussions.

Create a Comprehensive Study Guide

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Synthesizes course materials into a personalized study aid, improving retention and understanding.

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Review all lecture notes, readings, and assignments.
Organize and summarize key concepts, definitions, and examples.
Incorporate practice questions, quizzes, and self-reflection exercises.

Develop a Sentiment Analysis Application

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Applies course concepts to a practical project, reinforcing understanding of sentiment analysis techniques.

Browse courses on Sentiment Analysis

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Design a simple user interface for the application.
Implement the sentiment analysis functionality using the Text Analytics API or an alternative.
Test and evaluate the application's accuracy and performance.
Deploy the application to a hosting platform.

Contribute to an Open-Source NLP Project

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Provides real-world experience in NLP and contributes to the open-source community, fostering deeper understanding.

Browse courses on Natural Language Toolkit

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Identify an open-source NLP project on platforms like GitHub.
Familiarize yourself with the project's codebase and documentation.
Identify a feasible contribution, such as fixing a bug or adding a new feature.
Submit a pull request with your contribution and participate in the review process.

Career center

Learners who complete Natural Language Processing in Microsoft Azure will develop knowledge and skills that may be useful to these careers:

Natural Language Engineer

A Natural Language Engineer designs, develops and deploys NLP systems. As part of this, they may focus on doing the requirements gathering, project scoping and documentation, defining system specifications, designing algorithms, coding, debugging and testing NLP solutions, and deploying them in the production environment. This course may be useful in helping you develop some of the skills needed for this role, including how to use text analytics and translation services.

See salaries and explore the career path for Natural Language Engineer

Machine Learning Engineer

Machine Learning Engineers build and carry out the machine learning models that power many of the automated systems used by businesses and consumers today. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure Cognitive Services.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use various techniques to gather, analyze, interpret, and communicate data to help businesses understand and solve problems. This course may be useful in helping you develop some of the skills needed for this role, including how to use the Text Analytics service for advanced natural language processing.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts clean, analyze, and interpret data to help businesses track, understand, and improve their performance. This course may be useful in helping you develop some of the skills needed for this role, including how to use the Text Analytics service.

See salaries and explore the career path for Data Analyst

Software Engineer

Software Engineers design, develop, test, and maintain software systems. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI Services.

See salaries and explore the career path for Software Engineer

Technical Writer

Technical Writers create user manuals, technical reports, and other documentation to help people understand how to use products and services. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI to improve the clarity and effectiveness of your writing.

See salaries and explore the career path for Technical Writer

Sales Engineer

Sales Engineers help customers understand and select products and services that meet their needs. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI to demonstrate the value of your products and services.

See salaries and explore the career path for Sales Engineer

Quality Assurance Analyst

Quality Assurance Analysts test software to ensure that it meets quality standards. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI to automate your testing processes.

See salaries and explore the career path for Quality Assurance Analyst

Research Analyst

Research Analysts conduct research to provide insights that can be used to make informed decisions. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI to gather and analyze data.

See salaries and explore the career path for Research Analyst

Customer Experience Specialist

Customer Experience Specialists work with customers to resolve issues, provide support, and improve their overall experience with a product or service. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI to improve customer service.

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Information Security Analyst

Information Security Analysts protect computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI to detect and respond to security threats.

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Project Manager

Project Managers plan, execute, and close projects. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI to manage your projects more effectively.

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Business Analyst

Business Analysts define, analyze, and document the requirements of business systems, and develop solutions to improve business processes. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI to analyze data and solve business problems.

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Marketing Manager

Marketing Managers develop and execute marketing campaigns to promote products and services. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI to target your marketing efforts and measure their effectiveness.

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Product Manager

Product Managers manage the development and launch of products by working with teams to define product features, set priorities, and develop roadmaps. This course may be useful in helping you develop some of the skills needed for this role, including how to use Azure AI to build better products.

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Natural Language Processing in Microsoft Azure

What's inside

Syllabus

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Reviews summary

Well-received azure nlp course

Activities

Career center

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