Applied Artificial Intelligence: Natural Language Processing
- Offered byFutureLearn
Applied Artificial Intelligence: Natural Language Processing at FutureLearn Overview
Duration | 3 weeks |
Total fee | ₹900 |
Mode of learning | Online |
Credential | Certificate |
Applied Artificial Intelligence: Natural Language Processing at FutureLearn Highlights
- Duration 3 weeks
- Weekly study 6 hours
- Included in an ExpertTrack Course 3 of 4
Applied Artificial Intelligence: Natural Language Processing at FutureLearn Course details
- 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.
- 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.
- 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.
- 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.
Applied Artificial Intelligence: Natural Language Processing at FutureLearn Curriculum
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
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