Intro to Cloud Computing with R in Google Cloud and Amazon Web Services

Department of Statistics, University of Missouri

Introduction to Cloud Computing with R in Google Cloud and Amazon Web Services
By Dr. Sounak Chakraborty

Introduction to Cloud Computing with R in Google Cloud and Amazon Web ServicesBy Dr. Sounak Chakraborty, Associate Professor, Department of Statistics, University of Missouri, Columbia Date: September 19, 2020 (Saturday), 9.00 am – 4 pm (attendance online only)Location: Online Short CourseThe attendance cap is set at 150. All course materials, software requirements, and installation guidelines will be provided one week before the day of the short course through e-mail to the registered participants.No refund will be issued after 09/11/2020, 4 pm (CST).Course Description:The course will provide a gentle introduction of running R software/codes in cloud computing platform using Google Cloud (GC) and Amazon Web Services (AWS) for basic statistical modeling and calculations. R is one of the world&#x27;s most popular open source statistical programming languages and is most widely used by academia and major companies. Top Tier Companies using R and developing cloud-based solutions:1.	Facebook - For behavior analysis related to status updates and profile pictures.2.	Google - For advertising effectiveness and economic forecasting.3.	Twitter - For data visualization and semantic clustering4.	Microsoft - Acquired Revolution R company and use it for a variety of purposes.5.	Uber - For statistical analysis6.	Airbnb - Scale data science.7.	IBM - Joined R Consortium Group8.	ANZ - For credit risk modelingGoogle Cloud (GC) and Amazon Web Services (AWS) include many different computational tools, ranging from storage systems and virtual servers to databases and analytical tools. For R-programmers, being familiar and experienced with these tools can be extremely beneficial in terms of efficiency, style, money-saving and more. The cloud computing resources provided by GC and AWS are either free or of very minimal cost.Course topics will include:•	What is cloud computing and what are the benefits of using a cloud computing platform over traditional desktops and expensive clusters.•	A Basic Recap/Introduction of R •	Basic introduction to running R codes in Google Cloud (GC)•	Basic introduction to running R codes in Amazon Web Services (AWS)•	Under both GC and AWS we will learn how to use R for a) reading, manipulating, and output data files; b) simple statistical analysis (descriptive statistics, t-test, ANOVA, regression and classification methods); c) generating some basic plots for visualization (scatterplots, histograms, etc)The course will be completely online and self-paced, so the participants can learn all materials at their own convenience from the comfort of their home. There will a live Q&amp;A interactive session where students can ask question to the instructor. Instructions for recommended software and other course materials will be made available before the course. All recommended software will be open source and can be downloaded free of cost.About the Course Instructor: Sounak ChakrabortyDr. Sounak Chakraborty is an Associate Professor in the Department of Statistics, University of Missouri. His research interests are Bayesian machine learning, variable selection in high dimensional problems, data mining, non-linear models for complex data sets, statistical models for multi-platform data integrations, and Markov chain Monte Carlo driven computational models. He had worked on wide ranging applications of statistical models and tools in areas as bioinformatics, medical science, sociology, ecology, business analytics, biomedical engineering, nanotechnology and nanoscience. Prof. Chakraborty is highly proficient in R, Matlab, SAS, C++, and Python, and has worked extensively in developing and implementing complex statistical models using R, Matlab, C++, and Python in various practical areas.Materials (To Be Distributed Beforehand through e-mail to all registered participants):• Download Instructions (Screenshot step-by-step guide)• Short Course Slides (PPT, PDF files)• R code files Modules (.txt or .R files)• Toy Datasets (.csv, .txt files)Topics To be Covered &amp; Tentative Schedule:Session 1: Introduction to Cloud Computing30 mins	•	Overview •	Advantages of Cloud Computing•	What is Google Cloud•	What is Amazon Web ServicesSession 2: A Recap/Introduction to R1 hr 30 mins	•	What is R•	Reading Data, Data Summaries, Descriptive Statistics •	Basic Statistical Analysis using R•	Data visualization in RSession 3: Running R in Google Cloud Platform2 hr	•	How to set up virtual machines in Google Cloud•	Submitting R codes and running statistical analysis in Google Cloud•	Parallel Computing in Google CloudSession 4: Running R in Amazon Web Services Platform2 hr	•	How to set up virtual machines in Amazon Web Services •	Submitting R codes and running statistical analysis in AWS•	Special features and parallel computing in AWS

Our {communityGuidelinesLink} describe the sort of content we prohibit on Eventbrite. If you suspect an event may be in violation, you can report it to us so we can investigate.

To report other categories of prohibited or illegal content, submit {link}

Intro to Cloud Computing with R in Google Cloud and Amazon Web Services

More events from Department of Statistics, University of Missouri

Discover more events from Department of Statistics, University of Missouri, from Science & Tech to other experiences you might love.

Still looking for the right event?

Explore all online events to browse and filter by date, category, and more.

Intro to Cloud Computing with R in Google Cloud and Amazon Web Services

More events from Department of Statistics, University of Missouri

Discover more events from Department of Statistics, University of Missouri, from Science & Tech to other experiences you might love.

You might also like...

Browse more events with different dates, prices, and formats to find your next great experience.

Still looking for the right event?

Explore all online events to browse and filter by date, category, and more.