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Cloudswyft

Applied Artificial Intelligence: Natural Language Processing

Cloudswyft via FutureLearn

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Overview

Gain an understanding of generative AI

This course is part of the Advanced and Applied AI on Microsoft Azure ExpertTrack, helping you develop AI and machine learning skills and prepare you for the relevant Microsoft microcredentials.

Have you ever asked Siri a question? Or told Alexa to play a song? If so, you’ve experienced the most powerful and advanced examples of Natural Language Processing (NLP) that exist today.

NLP is fast becoming a part of our day-to-day lives and is a crucial component of AI. In this course, you’ll get an understanding of the core problems in NLP and learn how to solve critical NLP tasks.

Discover Natural Language Processing (NLP)

Natural language processing (NLP) is a field of artificial intelligence (AI) machine learning and computational linguistics.

During the course, you’ll learn how NLP is one of the most important technologies of the Information Age. You’ll gain a deeper understanding of this aspect of AI by delving into its sub areas including; natural language understanding, machine translation, semantics, and syntactic passing as well as natural language emulation and dialectal systems.

Understand vision and language joint learning

You’ll also be introduced to vision and language joint learning and inference problems to learn more about the issues of NLP.

As well as this, you’ll cover multimodal intelligence tasks and learn how to apply deep learning models on image captioning and visual question answering.

Apply deep learning models to solve NLP problems

By the end of the course, you will understand that NLP, though extremely powerful, also comes with many problems.

You’ll learn how to apply deep learning models to solve problems such as machine translation and conversation as well as applying deep reinforcement learning models on natural language applications.

This course is ideal for anyone who wants to become familiar with this emerging domain of artificial intelligence (AI), including data scientists, analytics managers, data analysts, data engineers, and data architects.

Natural Language Processing plays a critical role in supporting machine-human interactions. It is becoming increasingly integral to most areas of AI and advanced cloud based system development.

Syllabus

  • Course Introduction
    • About this Course
    • Introduction to NLP
    • NLP and Text Processing
    • Neural Models for Machine Translation and Conversation Generation
    • CloudSwyft Hands-On Lab 1
    • Wrapping up the week
  • Deep Semantic Similarity Model (DSSM)
    • Deep Semantic Similarity Model and its Applications
    • Deep Semantic Similarity Model for Information Retrieval
    • Deep Semantic Similarity Model for Entity Ranking
    • CloudSwyft Hands-On Lab 2
    • Deep Reinforcement Learning
    • Vision-Language Multimodal Intelligence
    • Wrapping up the Week
  • Natural Language Understanding
    • Natural Language Understanding
    • Continuous Word Representation
    • Neural Knowledge Base Embedding
    • Knowledge-Based Question Answering
    • CloudSwyft Hands-On Lab 3
    • Wrapping up the Week & Course Completion

Taught by

Daniela Piedrahita

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