Course Summary
Learn how to analyze big data using programming languages such as Python and R. This course is perfect for those who want to develop their skills in data analytics and data science.Key Learning Points
- Learn how to use Python and R for data analysis
- Explore data visualization techniques and machine learning algorithms
- Work on real-world projects to apply your skills
Related Topics for further study
Learning Outcomes
- Gain proficiency in using Python and R for data analysis
- Develop a solid understanding of data visualization techniques
- Apply machine learning algorithms to real-world problems
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of programming concepts
- Familiarity with statistics and linear algebra
Course Difficulty Level
IntermediateCourse Format
- Online self-paced course
- Video lectures
- Real-world projects
- Quizzes and exercises
Similar Courses
- Data Science Essentials
- Applied Data Science with Python
- Data Mining
Related Education Paths
Notable People in This Field
- Kirk Borne
- Hilary Mason
Related Books
Description
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.
Outline
- Scientific Approaches
- Lemmas
- Keyness of Word
- Collocations
- N-grams
- POS Parser
- Scientific approaches
- Analysis Tools I – BNC
- BNC - Information
- BNC - Function I
- BNC – Function II
- BNC - Task
- Student Presentation Samples: BNC
- BNC
- Analysis Tools II – COCA, ANTCONC & TagAnt
- COCA - Information
- COCA - Task
- AntConc
- TagAnt
- PM and Ratio
- COCA, TagAnt and AntConc
- Considerations of Big Data and Language
- Big Data for Different Languages
- Limitations of Big Data
- Future directions of Big Data
- Project Guideline and Peer Review
- Student Presentation Samples
- Project
Summary of User Reviews
Learn to work with big data in this comprehensive course that covers language, tools, and techniques. Students praise the course for its practical approach and real-world examples.Key Aspect Users Liked About This Course
The course provides practical examples and a hands-on approach to learning.Pros from User Reviews
- Real-world examples and practical approach
- Comprehensive coverage of tools and techniques
- Great for beginners and those with some experience
- Great instructor with clear explanations
- Good pacing and structure
Cons from User Reviews
- Some users found the content too basic
- Some users found the course too slow-paced
- No certification or credential offered
- Some technical issues with the platform
- Some users found the quizzes too easy
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