About this Course
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100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 14 hours to complete

Suggested: 4 weeks of study, 3-6 hours/week...
Available languages

English

Subtitles: English...

Skills you will gain

Python ProgrammingStatistical AnalysisSentiment AnalysisR Programming
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 14 hours to complete

Suggested: 4 weeks of study, 3-6 hours/week...
Available languages

English

Subtitles: English...

Syllabus - What you will learn from this course

Week
1
Hours to complete
3 hours to complete

Introduction to Data Analytics

In this first unit of the course, several concepts related to social media data and data analytics are introduced. We start by first discussing two kinds of data - structured and unstructured. Then look at how structured data, the primary focus of this course, is analyzed and what one could gain by doing such analysis. Finally, we briefly cover some of the visualizations for exploring and presenting data.Make sure to go through the material for this unit in the sequence it's provided. First, watch the four short videos, then take the practice test, followed by the two quizzes. Finally, read the documents about installation and configuration of Python and R. This is very important - before proceeding to the next units, make sure you have installed necessary tools, and also learned how to install new packages/libraries for them. The course expects students to have programming experience in Python and R....
Reading
4 videos (Total 33 min), 4 readings, 2 quizzes
Video4 videos
Video-2: Structured vs. Unstructured Data10m
Video-3: Analyzing Structured Data10m
Video-4: Visualization of Data8m
Reading4 readings
Anaconda Installation20m
Python installation, configuration, and usage30m
R installation30m
R/RStudio Setup Guide (on Windows)20m
Quiz2 practice exercises
Quiz-115m
Quiz-215m
Week
2
Hours to complete
4 hours to complete

Collecting and Extracting Social Media Data

In this unit we will see how to collect data from Twitter and YouTube. The unit will start with an introduction to Python programming. Then we will use a Python script, with a little editing, to extract data from Twitter. A similar exercise will then be done with YouTube. In both the cases, we will also see how to create developer accounts and what information to obtain to use the data collection APIs. Once again, make sure to go item-by-item in the order provided. Before beginning this unit, ensure that you have all the right tools (Python, R, Anaconda) ready and configured. The lessons depend on them and also your ability to install required packages....
Reading
4 videos (Total 47 min), 6 readings, 3 quizzes
Video4 videos
Video-2: Introduction to Python Programming16m
Video-3: Using Python to Extract Data from Twitter15m
Video-4: Using Python to Extract Data from YouTube11m
Reading6 readings
Errata: please read this first1m
Python Packages Installation5m
(Optional) Introduction to Python for Econometrics, Statistics and Data Analysis30m
Script: twitter_search.pym
Twitter libraries10m
Script: youtube_search.pym
Quiz2 practice exercises
Python Programming Exercise2m
YouTube data download using Python6m
Week
3
Hours to complete
4 hours to complete

Data Analysis, Visualization, and Exploration

In this unit, we will focus on analyzing and visualizing the data from various social media services. We will first use the data collected before from YouTube to do various statistics analyses such as correlation and regression. We will then introduce R - a platform for doing statistical analysis. Using R, then we will analyze a much larger dataset obtained from Yelp. Make sure you have covered the material in the previous units before proceeding with this. That means, having all the tools (Anaconda, Python, and R) as well as various packages installed. We will also need new packages this time, so make sure you know how to install them to your Python or R. If needed, please review some basic concepts in statistics - specifically, correlation and regression - before or during working on this unit....
Reading
4 videos (Total 87 min), 8 readings, 2 quizzes
Video4 videos
Video-2: Analyzing Social Media Data Using Python26m
Video-3: Introduction to R26m
Video-4: Social Media Data Analysis with R32m
Reading8 readings
Script: twitter_process.pym
Data: iqsize.csvm
R Installation Guide10m
Installing R Packages5m
Statistical Analysis with R10m
Read this first2m
Scripts for converting json to csv2m
Data Visualization with ggplot2 (R) - Cheat Sheet10m
Quiz1 practice exercise
Statistical Analysis with Twitter Data6m
Week
4
Hours to complete
3 hours to complete

Case Studies

In the final unit of this course, we will work on two case studies - both using Twitter and focusing on unstructured data (in this case, text). The first case study will involve doing sentiment analysis with Python. The second case study will take us through basic text mining application using R. We wrap up the unit with a conclusion of what we did in this course and where to go next for further learning and exploration....
Reading
4 videos (Total 47 min), 4 readings, 2 quizzes
Video4 videos
Video-2: Sentiment Analysis with Twitter Data21m
Video-3: Text Mining of Twitter Data15m
Video-4: Conclusion6m
Reading4 readings
Script: twitter_sentiments.pym
NLTK10m
Script: text_mining_twitter.rm
An Introduction to Network Analysis with R and statnet10m
Quiz1 practice exercise
Sentiment Analysis with Twitter6m

Instructor

Avatar

Chirag Shah

Associate Professor
Information and Computer Science

About Rutgers the State University of New Jersey

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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