Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
11 Hour(s) 12 Minute(s)
Language
English
Taught by
Sachin Kafle
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
4 views
Course Overview
Learn Natural Language Processing and Sentimental Analysis using "The Big Bang Theory" show script in R.
Caution before taking this course:
This course does not make you expert in R programming rather it will teach you concepts which will be more than enough to be used in machine learning and natural language processing models.
About the course:
In this practical, hands-on course you’ll learn how to program in R and how to use R for effective data analysis, visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.
Our main objective is to give you the education not just to understand the ins and outs of the R programming language, but also to learn exactly how to become a professional Data Scientist with R and land your first job.
This course covers following topics:
1. R programming concepts: variables, data structures: vector, matrix, list, data frames/ loops/ functions/ dplyr package/ apply() functions
2. Web scraping: How to scrape titles, link and store to the data structures
3. NLP technologies: Bag of Word model, Term Frequency model, Inverse Document Frequency model
4. Sentimental Analysis: Bing and NRC lexicon
5. Text mining
By the end of the course you’ll be in a journey to become Data Scientist with R and confidently apply for jobs and feel good knowing that you have the skills and knowledge to back it up.
Course Content
- 9 section(s)
- 106 lecture(s)
- Section 1 Introduction
- Section 2 Essentials: R programming
- Section 3 IMPORTANT: Data Structures in R
- Section 4 Miscellaneous
- Section 5 Building Logic in R
- Section 6 The "dplyr" package to handle data
- Section 7 Introduction to Text mining
- Section 8 Important Terminologies
- Section 9 Project: Sentimental Analysis with R
What You’ll Learn
- Use R for Data Science and Machine Learning
- Provides the entire toolbox you need to become a NLP engineer
- Learn how to pre-process data
- Apply your skills to real-life business cases
- Able to perform web scraping
- Learn text mining
- able to perform sentimental analysis on any text
Skills covered in this course
Reviews
-
JJorico Berongoy
excellent
