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Seonmin Park
In this course, students will understand characteristics of language through big data. Students will learn how to collect and analyze big data, and find linguistic features from the data. A number of approaches to the linguistic analysis of written and spoken texts will be discussed.
Read more
In this course, students will understand characteristics of language through big data. Students will learn how to collect and analyze big data, and find linguistic features from the data. A number of approaches to the linguistic analysis of written and spoken texts will be discussed.
Read more
In this course, students will understand characteristics of language through big data. Students will learn how to collect and analyze big data, and find linguistic features from the data. A number of approaches to the linguistic analysis of written and spoken texts will be discussed.
The class will consist of lecture videos which are approximately 1 hour and a quiz for each week. There will be a final project which requires students to conduct research on text data and language.
Register for this course and see more details by visiting:
OpenCourser.com/course/h72wai/big
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What's inside
Syllabus
Introduction to Big Data and Language
Spoken and Written Data
Corpus and Register
Read more
Syllabus
Introduction to Big Data and Language
Spoken and Written Data
Corpus and Register
Read more
Parts of Speech
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines linguistic features of written and spoken texts, which is standard in academia
Taught by Dr. Seonmin Park, who is well-known for their work in natural language processing (NLP)
Emphasizes the use of technology to analyze language, which aligns with current trends in the digital humanities field
Introduces essential concepts and techniques for linguistic analysis, building a solid foundation for further study in the field
Requires students to conduct research on language data, providing practical experience in data analysis and interpretation
May require background knowledge in programming and statistics, which could be a potential barrier for some students
Save this course
Save Big data and Language 1 to your list so you can find it easily later:
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Reviews summary
Big data and language 1: linguistics basics
Learners say that Big Data and Language 1 is a solid entry-level course for those interested in language analysis, corpus study, and linguistic fundamentals. The course begins with a grammar review, then explores concepts in Big data and NLP. Learners appreciate clear explanations and engaging lectures, but some mention the instructor may encounter language barriers from time to time. Overall, learners describe the course as well-structured and informative, making it a good choice for those seeking a basic understanding of language and its relation to Big data.
Course content is suitable for beginners.
"Great course for beginners interested to understand some basic theory of Linguistics."
Instructor provides clear explanations.
"The professor is very clear, and the explanations are very accessible."
Course content is clear and easy to understand.
"Great way to introduce basic concepts necessary for language analysis/corpus study."
"The presenter does a great job of breaking down some of the complicated concepts for beginners."
Course offers a good overview of Big data and language.
"A good introduction to big data and corpus linguistics"
Course has a few grammatical mistakes.
"There were quite a few grammatical mistakes, which I find hard to excuse on a course about Linguistics"
Course instructor's English language skills could be improved.
"However, the trainer/teacher struggled to communicate in some areas, most likely owing to language barriers (i.e., English)."
Course could include more additional study material like lectures.
"This course is basically general review of grammar in the level of sentence and text with the variations of written and spoken ways."
Course provides too much focus on grammar, not enough on Big data.
"I expected more discussions on big data, methodologies and tools to analyze big data rather than lectures on grammar."
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 Big data and Language 1 with these
activities:
Read 'Introduction to Natural Language Processing, 2nd Edition' by Jurafsky and Martin
Show steps
This comprehensive reference book provides a strong foundation for understanding natural language processing techniques.
View
Speech and Language Processing
on Amazon
Show steps
-
Read the assigned chapters and take notes.
-
Complete the exercises and assignments in the book.
Revisit linguistic terminology
Show steps
Revising these essential concepts will lay a solid foundation for understanding the course material.
Browse courses on
Parts of speech
Show steps
-
Review notes or textbooks from previous linguistics courses.
-
Take practice quizzes or exercises to test your understanding.
Develop a glossary of linguistic terms
Show steps
Creating a personal glossary will enhance your understanding and retention of key concepts.
Browse courses on
Parts of speech
Show steps
-
Identify and define important linguistic terms.
-
Organize the terms into a coherent structure.
-
Refer to your glossary regularly while studying.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Explore online resources
Show steps
Familiarizing yourself with specialized tools and techniques will extend your capabilities in the field.
Browse courses on
Big Data Analysis
Show steps
-
Search for online tutorials on linguistic analysis of big data.
-
Follow the tutorials to learn how to use specific software or techniques.
-
Apply what you've learned to analyze sample texts.
Analyze sample texts
Show steps
Applying linguistic principles to real-world examples will enhance your analytical skills and deepen your comprehension.
Browse courses on
Text Analysis
Show steps
-
Find sample texts from various sources (e.g., news articles, blog posts, literary works).
-
Identify and label the parts of speech and other linguistic features.
-
Look for patterns and correlations in the usage of linguistic features.
Join a study group
Show steps
Engaging with peers can provide diverse perspectives, enhance understanding, and motivate learning.
Show steps
-
Connect with classmates through online forums or social media.
-
Set up regular study sessions to discuss course material, share insights, and work on assignments.
-
Provide support and encouragement to each other.
Participate in a tutoring program
Show steps
Teaching others can reinforce your understanding and identify areas where you need further improvement.
Show steps
-
Volunteer as a tutor for introductory linguistics courses.
-
Provide support and guidance to students with their assignments and understanding of concepts.
Analyze a text corpus
Show steps
Conducting your own analysis will deepen your understanding of linguistic patterns and provide practical experience.
Browse courses on
Corpus Linguistics
Show steps
-
Choose a research question and gather a relevant text corpus.
-
Apply linguistic analysis techniques to extract and interpret data.
-
Draw conclusions and present your findings.
Contribute to a linguistic data science project
Show steps
Hands-on involvement in open-source projects provides valuable experience and fosters collaboration.
Browse courses on
Natural Language Processing
Show steps
-
Identify a linguistic data science project that interests you.
-
Join the project community and learn about their goals and methods.
-
Contribute to the project by writing code, analyzing data, or providing documentation.
Read 'Introduction to Natural Language Processing, 2nd Edition' by Jurafsky and Martin
Show steps
This comprehensive reference book provides a strong foundation for understanding natural language processing techniques.
View
Speech and Language Processing
on Amazon
Show steps
Show steps
Show steps
- Read the assigned chapters and take notes.
- Complete the exercises and assignments in the book.
Revisit linguistic terminology
Show steps
Revising these essential concepts will lay a solid foundation for understanding the course material.
Browse courses on
Parts of speech
Show steps
Show steps
Show steps
- Review notes or textbooks from previous linguistics courses.
- Take practice quizzes or exercises to test your understanding.
Develop a glossary of linguistic terms
Show steps
Creating a personal glossary will enhance your understanding and retention of key concepts.
Browse courses on
Parts of speech
Show steps
Show steps
Show steps
- Identify and define important linguistic terms.
- Organize the terms into a coherent structure.
- Refer to your glossary regularly while studying.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Explore online resources
Show steps
Familiarizing yourself with specialized tools and techniques will extend your capabilities in the field.
Browse courses on
Big Data Analysis
Show steps
Show steps
Show steps
- Search for online tutorials on linguistic analysis of big data.
- Follow the tutorials to learn how to use specific software or techniques.
- Apply what you've learned to analyze sample texts.
Analyze sample texts
Show steps
Applying linguistic principles to real-world examples will enhance your analytical skills and deepen your comprehension.
Browse courses on
Text Analysis
Show steps
Show steps
Show steps
- Find sample texts from various sources (e.g., news articles, blog posts, literary works).
- Identify and label the parts of speech and other linguistic features.
- Look for patterns and correlations in the usage of linguistic features.
Join a study group
Show steps
Engaging with peers can provide diverse perspectives, enhance understanding, and motivate learning.
Show steps
Show steps
Show steps
- Connect with classmates through online forums or social media.
- Set up regular study sessions to discuss course material, share insights, and work on assignments.
- Provide support and encouragement to each other.
Participate in a tutoring program
Show steps
Teaching others can reinforce your understanding and identify areas where you need further improvement.
Show steps
Show steps
Show steps
- Volunteer as a tutor for introductory linguistics courses.
- Provide support and guidance to students with their assignments and understanding of concepts.
Analyze a text corpus
Show steps
Conducting your own analysis will deepen your understanding of linguistic patterns and provide practical experience.
Browse courses on
Corpus Linguistics
Show steps
Show steps
Show steps
- Choose a research question and gather a relevant text corpus.
- Apply linguistic analysis techniques to extract and interpret data.
- Draw conclusions and present your findings.
Contribute to a linguistic data science project
Show steps
Hands-on involvement in open-source projects provides valuable experience and fosters collaboration.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Identify a linguistic data science project that interests you.
- Join the project community and learn about their goals and methods.
- Contribute to the project by writing code, analyzing data, or providing documentation.
Career center
Learners who complete Big data and Language 1 will develop knowledge and skills
that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineer
NLP Engineers develop and implement computer systems that can understand and generate human language. This course may be useful for success as a NLP Engineer because it will help you develop a deep understanding of the structure of language, which will be vital in your NLP work.
Data Scientist
Data Scientist
Data Scientists use their skills in mathematics, statistics, and computer science to develop and implement data-driven solutions to business problems. This course is quite relevant, and may be helpful in your career as a Data Scientist because it will provide you with the opportunity to gain experience in collecting, analyzing, and using big data.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and implement machine learning models that can learn from data and make predictions. This course may be quite useful to your success as a Machine Learning Engineer because it will provide you with the opportunity to gain experience in collecting, analyzing, and using big data.
Information Architect
Information Architect
Information Architects design and organize websites, intranets, and other information systems in order to make them easy to use and find. This course may be quite useful in your career as an Information Architect because it will provide you with a deep understanding of the structure of language and how it can be used to convey information.
Linguistic Analyst
Linguistic Analyst
Linguistic Analysts work in many different industries, but they all use their deep understanding of language to solve problems. If you plan to be a Linguistic Analyst, this course may be helpful because it will provide you with a toolkit of skills you can use to collect and analyze big data in order to gain insights into language.
Technical Writer
Technical Writer
Technical Writers create user manuals, documentation, and other technical materials. This course may be quite useful in your career as a Technical Writer because it will enhance your ability to craft clear and concise language.
Speech Scientist
Speech Scientist
Speech Scientists study the production and perception of speech. This course may be quite useful in your career as a Speech Scientist because it will provide you with a deep understanding of the structure of spoken language.
Lexicographer
Lexicographer
Lexicographers research and compile dictionaries. This course may be quite helpful in your career as a Lexicographer because it will provide you with a deep understanding of the structure of language.
Computational Linguist
Computational Linguist
Computational Linguists use their knowledge of linguistics and computer science to develop computational models of language. While this course may not be required for this role, it can provide you with a competitive edge because it will enhance your understanding of the structure of language.
Forensic Linguist
Forensic Linguist
Forensic Linguists apply their knowledge of linguistics to legal problems. This course may be quite useful in your career as a Forensic Linguist because it will provide you with a deep understanding of the structure of language and how it can be used to convey meaning.
Translator
Translator
Translators convert written or spoken text from one language to another. This course may be somewhat useful in your career as a Translator because it will provide you with a deeper understanding of the structure of different languages.
User Experience Researcher
User Experience Researcher
User Experience Researchers study how people interact with products and services in order to improve their usability. This course may be somewhat useful in your career as a User Experience Researcher because it will provide you with a better understanding of how people use and understand language.
Language Teacher
Language Teacher
Language Teachers teach foreign languages to students. This course may be somewhat useful in your career as a Language Teacher because it will provide you with a deeper understanding of the principles of language acquisition and use.
Data Analyst
Data Analyst
Data Analysts use their skills in mathematics and statistics to collect, analyze, and interpret data. This course may be somewhat useful for your work because it will help you to build a foundation in the analysis of big data.
Front-End Web Developer
Front-End Web Developer
Front-End Web Developers are responsible for the design and implementation of the user interface of a website. This course may be somewhat useful in your career as a Front-End Web Developer because it will provide you with a deeper understanding of the principles of user experience and how to create user-friendly websites.
For more career information including salaries, visit:
OpenCourser.com/course/h72wai/big
Reading list
We've selected eight 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
Big data and Language 1.
Provides a comprehensive overview of natural language processing (NLP) techniques, with a focus on Python implementations. It covers topics such as text classification, sentiment analysis, and machine translation.
Provides a comprehensive overview of speech and language processing, with a focus on theoretical foundations and practical applications.
Provides a comprehensive overview of speech and language processing, with a focus on theoretical foundations and practical applications.
Provides a comprehensive overview of the statistical foundations of natural language processing. It covers topics such as language models, machine learning algorithms, and evaluation metrics.
Provides a comprehensive overview of speech and language processing, with a focus on theoretical foundations and practical applications. It covers topics such as speech recognition, language modeling, and machine translation.
Provides an overview of Korean natural language processing (NLP) techniques, with a focus on practical applications.
Provides a comprehensive overview of the statistical foundations of natural language processing. It covers topics such as language models, machine learning algorithms, and evaluation metrics.
Provides a comprehensive overview of Korean natural language processing (NLP) techniques, with a focus on theoretical foundations and practical applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/h72wai/big
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Effort
2-3 hours/week
Level
Introductory
Via
Coursera
Institution
Korea Advanced Institute of Science and Technology(KAIST)
Instructor
Seonmin Park
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
Nederlands
Svenska
Pусский
Türkçe
Polski
Ελληνικά
українська мова
Bahasa Indonesia
ไทย
қазақша
Good to know
Examines linguistic features of written and spoken texts, which is standard in academia
Taught by Dr. Seonmin Park, who is well-known for their work in natural language processing (NLP)
Emphasizes the use of technology to analyze language, which aligns with current trends in the digital humanities field
Introduces essential concepts and techniques for linguistic analysis, building a solid foundation for further study in the field
Requires students to conduct research on language data, providing practical experience in data analysis and interpretation
May require background knowledge in programming and statistics, which could be a potential barrier for some students
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