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Jay Alammar,
Arpan Chakraborty,
Luis Serrano,
and
Dana Sheahen
Take Udacity's Introduction to Natural Language Processing course and learn voice user interface techniques and build a speech recognition model using deep neural networks.
Prerequisite details
Read more
Take Udacity's Introduction to Natural Language Processing course and learn voice user interface techniques and build a speech recognition model using deep neural networks.
Prerequisite details
Read more
Take Udacity's Introduction to Natural Language Processing course and learn voice user interface techniques and build a speech recognition model using deep neural networks.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Intermediate Python
- Neural network basics
- Basic probability
- Object-oriented programming basics
- Deep learning framework proficiency
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/qftu3q/communicating
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What's inside
Syllabus
Introduce the course outline and the course prerequisite
Get acquainted with the principles and applications of VUI, and get introduced to Alexa skills.
Read more
Syllabus
Introduce the course outline and the course prerequisite
Get acquainted with the principles and applications of VUI, and get introduced to Alexa skills.
Read more
Build your own Alexa skill and deploy it!
Learn how an automatic speech recognition (ASR) pipeline works.
Build a deep neural network that functions as part of an end-to-end automatic speech recognition pipeline.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines principles and applications of voice user interface (VUI), including Alexa skills
Introduces the automatic speech recognition (ASR) pipeline and its components
Covers a range of topics related to natural language processing (NLP), including VUI, ASR, and deep neural networks
Taught by experienced instructors in the field of NLP
Requires prior knowledge in intermediate Python, neural network basics, basic probability, object-oriented programming basics, and deep learning framework proficiency
Save this course
Save Communicating with Natural Language to your list so you can find it easily later:
Save
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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 Communicating with Natural Language with these
activities:
Complete the Udacity NLP Fundamentals course
Show steps
This guided tutorial will provide you with a solid foundation in the fundamentals of NLP, which will be essential for your success in this course.
Browse courses on
Natural Language Processing
Show steps
-
Enroll in the Udacity NLP Fundamentals course.
-
Complete all of the video lectures.
-
Complete all of the practice exercises.
Compile a list of resources on voice user interfaces (VUIs)
Show steps
Compiling a list of resources on VUIs will help you stay up-to-date on the latest developments in this field and expand your knowledge beyond the scope of this course.
Show steps
-
Search for online resources on VUIs, such as articles, tutorials, and videos.
-
Organize your resources into a list or spreadsheet.
-
Share your list of resources with other students or online communities.
Review linear regression and neural networks
Show steps
Reviewing the basics of linear regression and neural networks will strengthen your foundation for this course's content.
Browse courses on
Linear Regression
Show steps
-
Read through your notes or textbooks on linear regression.
-
Work through practice problems on linear regression.
-
Review your notes or textbooks on neural networks.
-
Complete practice problems on neural networks.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete practice exercises on speech recognition
Show steps
Completing practice exercises on speech recognition will help you develop the skills necessary to build a speech recognition model as part of this course.
Browse courses on
Speech Recognition
Show steps
-
Find practice exercises online or in textbooks.
-
Complete as many practice exercises as possible.
-
Review your answers and identify areas where you need improvement.
Build a simple chatbot using NLTK
Show steps
Building a simple chatbot will give you hands-on experience with NLP techniques and help you apply the concepts you learn in this course.
Browse courses on
Chatbot
Show steps
-
Choose a topic for your chatbot.
-
Gather and prepare a dataset for your chatbot.
-
Design and implement your chatbot using NLTK.
-
Test and evaluate your chatbot.
Mentor a junior student or peer on NLP concepts
Show steps
Mentoring others will reinforce your understanding of NLP concepts and help you develop your communication and leadership skills.
Browse courses on
Mentoring
Show steps
-
Identify a junior student or peer who is interested in learning about NLP.
-
Meet with your mentee regularly to discuss NLP concepts and answer their questions.
-
Provide feedback and guidance on your mentee's progress.
Contribute to an open-source NLP project
Show steps
Contributing to an open-source NLP project will give you real-world experience with NLP techniques and help you build your portfolio.
Browse courses on
Open Source
Show steps
-
Identify an open-source NLP project that interests you.
-
Join the project's community and learn about their development process.
-
Identify a way to contribute to the project, such as fixing a bug or adding a new feature.
-
Submit a pull request with your contribution.
Complete the Udacity NLP Fundamentals course
Show steps
This guided tutorial will provide you with a solid foundation in the fundamentals of NLP, which will be essential for your success in this course.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Enroll in the Udacity NLP Fundamentals course.
- Complete all of the video lectures.
- Complete all of the practice exercises.
Compile a list of resources on voice user interfaces (VUIs)
Show steps
Compiling a list of resources on VUIs will help you stay up-to-date on the latest developments in this field and expand your knowledge beyond the scope of this course.
Show steps
Show steps
Show steps
- Search for online resources on VUIs, such as articles, tutorials, and videos.
- Organize your resources into a list or spreadsheet.
- Share your list of resources with other students or online communities.
Review linear regression and neural networks
Show steps
Reviewing the basics of linear regression and neural networks will strengthen your foundation for this course's content.
Browse courses on
Linear Regression
Show steps
Show steps
Show steps
- Read through your notes or textbooks on linear regression.
- Work through practice problems on linear regression.
- Review your notes or textbooks on neural networks.
- Complete practice problems on neural networks.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete practice exercises on speech recognition
Show steps
Completing practice exercises on speech recognition will help you develop the skills necessary to build a speech recognition model as part of this course.
Browse courses on
Speech Recognition
Show steps
Show steps
Show steps
- Find practice exercises online or in textbooks.
- Complete as many practice exercises as possible.
- Review your answers and identify areas where you need improvement.
Build a simple chatbot using NLTK
Show steps
Building a simple chatbot will give you hands-on experience with NLP techniques and help you apply the concepts you learn in this course.
Browse courses on
Chatbot
Show steps
Show steps
Show steps
- Choose a topic for your chatbot.
- Gather and prepare a dataset for your chatbot.
- Design and implement your chatbot using NLTK.
- Test and evaluate your chatbot.
Mentor a junior student or peer on NLP concepts
Show steps
Mentoring others will reinforce your understanding of NLP concepts and help you develop your communication and leadership skills.
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Identify a junior student or peer who is interested in learning about NLP.
- Meet with your mentee regularly to discuss NLP concepts and answer their questions.
- Provide feedback and guidance on your mentee's progress.
Contribute to an open-source NLP project
Show steps
Contributing to an open-source NLP project will give you real-world experience with NLP techniques and help you build your portfolio.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Identify an open-source NLP project that interests you.
- Join the project's community and learn about their development process.
- Identify a way to contribute to the project, such as fixing a bug or adding a new feature.
- Submit a pull request with your contribution.
Career center
Learners who complete Communicating with Natural Language will develop knowledge and skills
that may be useful to these careers:
Alexa Skills Developer
Alexa Skills Developer
Alexa Skills Developers create custom skills for Amazon's Alexa voice assistant. These developers use the Alexa Skills Kit to integrate their skills with Alexa. The Communicating with Natural Language course may be helpful for career development as an Alexa Skills Developer as it will give you hands-on experience building and deploying Alexa skills.
Natural Language Processing Researcher
Natural Language Processing Researcher
Natural Language Processing Researchers develop new techniques for natural language processing. These researchers often specialize in particular subfields of natural language processing, such as speech recognition. The Communicating with Natural Language course may be helpful career development for those wishing to enter this field by providing a solid foundation in the principles of natural language processing and the techniques used in developing speech recognition models.
Natural Language Understanding Engineer
Natural Language Understanding Engineer
Natural Language Understanding Engineers develop and maintain natural language understanding systems. These engineers need a deep understanding of natural language processing techniques, including speech recognition. The Communicating with Natural Language course gives you hands-on experience training deep learning models for natural language processing tasks, including speech recognition, so you may find the course helpful for career development as a Natural Language Understanding Engineer.
Speech Scientist
Speech Scientist
Speech Scientists specialize in computer techniques for modeling speech, and for developing voice-activated systems. These scientists use machine learning to make their models more intelligent and accurate. The Communicating with Natural Language course gives you hands-on experience training deep learning models for natural language processing tasks, so you may find the course helpful for career development as a Speech Scientist.
Voice User Interface Designer
Voice User Interface Designer
Voice User Interface Designers design and develop voice-activated interfaces for a wide range of devices, such as smartphones, smart speakers, and vehicles. These designers often collaborate with other professionals, including software engineers and speech scientists. The Communicating with Natural Language course may be helpful for career development as a Voice User Interface Designer by giving you hands-on experience building end-to-end natural language processing pipelines using deep neural networks.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. These engineers need a deep understanding of the models they implement. The Communicating with Natural Language course provides a deep dive on the principles and applications of machine learning as applied to natural language processing, so you may find the course helpful for career development as a Machine Learning Engineer.
Computational Linguist
Computational Linguist
Computational Linguists apply computer science techniques to the analysis of natural language. These professionals often use their skills in machine learning to develop and improve language processing tools. The Communicating with Natural Language course may be helpful for career development as a Computational Linguist by giving you hands-on experience building end-to-end natural language processing pipelines using deep neural networks.
Dialogue Systems Developer
Dialogue Systems Developer
Dialogue Systems Developers design and develop dialogue systems, which are computer systems that can engage in natural language conversations with humans. These developers use a variety of techniques, including natural language processing and machine learning. The Communicating with Natural Language course gives you hands-on experience building end-to-end natural language processing pipelines using deep neural networks, so you may find the course helpful for career development as a Dialogue Systems Developer.
Software Engineer
Software Engineer
Software Engineers design, develop, test, and maintain software systems. These engineers often specialize in particular software paradigms, such as natural language processing. The Communicating with Natural Language course gives you hands-on experience building end-to-end natural language processing pipelines using deep neural networks, so you may find the course helpful for career development as a Software Engineer specializing in natural language processing.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. These managers often specialize in particular product areas, such as natural language processing. The Communicating with Natural Language course may be helpful for career development as a Product Manager specializing in natural language processing by giving you a solid foundation in the principles of natural language processing and the techniques used in developing natural language processing products.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. These managers often specialize in particular project types, such as software development or data science projects. The Communicating with Natural Language course may be helpful for career development as a Project Manager specializing in natural language processing projects by giving you a solid foundation in the principles of natural language processing and the techniques used in developing natural language processing products.
Data Scientist
Data Scientist
Data Scientists use statistical knowledge to extract insights from data. Machine learning and deep learning are often used on the job. The Communicating with Natural Language course gives you hands-on experience training deep learning models for natural language processing tasks, so you may find the course helpful for career development as a Data Scientist.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data. These analysts often use machine learning to build predictive models. The Communicating with Natural Language course gives you hands-on experience training deep learning models for natural language processing tasks, so you may find the course helpful for career development as a Quantitative Analyst.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. These analysts often use machine learning to build predictive models. The Communicating with Natural Language course gives you hands-on experience training deep learning models for natural language processing tasks, so you may find the course helpful for career development as a Data Analyst.
Business Analyst
Business Analyst
Business Analysts help businesses improve their operations by identifying and solving problems. These analysts often use data analysis and machine learning to identify inefficiencies and opportunities for improvement. The Communicating with Natural Language course gives you hands-on experience training deep learning models for natural language processing tasks, so you may find the course helpful for career development as a Business Analyst.
For more career information including salaries, visit:
OpenCourser.com/course/qftu3q/communicating
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Communicating with Natural Language.
Classic textbook on speech and language processing. It covers a wide range of topics, including speech production and perception, natural language understanding, and machine translation. It valuable resource for anyone interested in learning more about these topics.
Provides a comprehensive overview of deep learning techniques for natural language processing. It covers a wide range of topics, including word embeddings, recurrent neural networks, and transformers. It valuable resource for anyone interested in learning more about this field.
Provides a comprehensive overview of natural language processing techniques, including speech recognition, natural language understanding, and machine translation. It valuable reference for anyone interested in learning more about this field.
Provides a comprehensive overview of statistical natural language processing. It covers a wide range of topics, including probability theory, machine learning, and natural language processing applications. It valuable resource for anyone interested in learning more about this field.
Provides a comprehensive overview of natural language processing for social media. It covers a wide range of topics, including text mining, sentiment analysis, and social network analysis. It valuable resource for anyone interested in learning more about this field.
Provides a comprehensive overview of machine translation techniques. It covers a wide range of topics, including statistical machine translation, neural machine translation, and evaluation metrics. It valuable resource for anyone interested in learning more about this field.
Provides a comprehensive overview of speech recognition techniques. It covers a wide range of topics, including acoustic modeling, language modeling, and decoding algorithms. It valuable resource for anyone interested in learning more about this field.
Provides a comprehensive overview of reinforcement learning for natural language processing. It covers a wide range of topics, including Markov decision processes, value functions, and policy search. It valuable resource for anyone interested in learning more about this field.
Provides a practical introduction to natural language processing. It covers a wide range of topics, including text classification, sentiment analysis, and named entity recognition. It valuable resource for anyone interested in building natural language processing applications.
Comprehensive guide to the Natural Language Toolkit (NLTK), a popular open-source library for natural language processing. It covers a wide range of topics, including tokenization, stemming, parsing, and machine learning. It valuable resource for anyone interested in using NLTK for natural language processing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/qftu3q/communicating
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Effort
4 weeks
Level
Advanced
Via
Udacity
Instructors
Jay Alammar
Arpan Chakraborty
Luis Serrano
Dana Sheahen
Language
English
Good to know
Examines principles and applications of voice user interface (VUI), including Alexa skills
Introduces the automatic speech recognition (ASR) pipeline and its components
Covers a range of topics related to natural language processing (NLP), including VUI, ASR, and deep neural networks
Taught by experienced instructors in the field of NLP
Requires prior knowledge in intermediate Python, neural network basics, basic probability, object-oriented programming basics, and deep learning framework proficiency
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