My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real life. After taking this course, you’ll easily use packages like caret, dplyr to work with real data in R. You will also learn to use the common social media mining and natural language processing packages to extract insights from text data.

I will even introduce you to some very important practical case studies - such as identifying important words in a text and predicting movie sentiments based on textual reviews. You will also extract tweets pertaining to trending topics and analyze their underlying sentiments and identify topics with Latent Dirichlet allocation. With this Powerful course, you’ll know it all: extracting text data from websites, extracting data from social media sites and carrying out analysis of these using visualization, stats, machine learning, and deep learning!

Start analyzing data for your own projects, whatever your skill level and Impress your potential employers with actual examples of your data science projects.

HERE IS WHAT YOU WILL GET:

Data Structures and Reading in R, including CSV, Excel, JSON, HTML data.

Web-Scraping using R

Extracting text data from Twitter and Facebook using APIs

Extract and clean data from the FourSquare app

Exploratory data analysis of textual data

Common Natural Language Processing techniques such as sentiment analysis and topic modelling

Implement machine learning techniques such as clustering, regression and classification on textual data

Network analysis

All the data and code used in the course has been made available free of charge and you can use it as you like. You will also have access to additional lectures that are added in the future for FREE.