Data Science Using R

Visualizations can surprise you - Dr. Hadley Wickham

New batch

• 9.30 pm - 11.30 pm IST Sundays for 8 weeks starting Dec 10, 2017
• Cost : Rs. 24,000 / USD 375
• In India ? : pay to paytm : +91 807 308 5989 or UPI : sirpi@kotak
• In the US ? : Whatsapp to +91 831 076 4903 to receive a paypal invoice.

Register here

• https://goo.gl/forms/fRu6MAXBibVK4Sw03

Summary

Learn R programming and visualizations using the tidyverse methods. The course is ALL HANDS ON and at the end of the course, participants will have a good handle on: data importing, data cleaning, data transformations, control structures, conditional evaluations, for loops and newer alternatives, functional programming, exploratory analysis and the many types of data visualization techniques. Participants will learn to create reproducible reports and presentations of their visualizations to impress decision makers. R Programming will be at the core of all of the above learning objectives. This course will serve as a foundation to understand data modeling, prediction, and machine learning.

References

• R for Data Science http://r4ds.had.co.nz/
• http://tidyverse.org

Data Science, jobs, career growth and strategic decision making

• If you are a college student this course will help you develop critical skills for current and future academic research or for a corporate job in entry level data science. Jobs in data science are the fastest growing in the industry.
• If you are an early career professional, this course will get you an edge over your industry peers in your domain. A professional with domain knowledge together with data science skills is valued more.
• If you are a mid career professional, this course will help you transition into a data scientist or improve your existing career by leveraging the domain knowledge you have built over the years.
• If you are at the C-level, this course will help you in strategic data-driven decision making.

Why SIRPI ?

• High profile instructors
• Live hands-on training
• Office hours for debugging
• Extra coaching by trained data scientists as needed

About the Instructor

Dr. Anand Lakshmanan, is the Founder and CEO of Bangalore based SIRPI (http://www.sirpi.co.in) which provides training, consulting, and outsourcing in areas of data science and engineering research. He has helped academic institutions and corporates deep dive into their data and make better decisions. He has designed experiments and analyzed data in areas across domains including hardware-software interfacing, electrophysiology, computational neuroscience, microstrip antenna research, mobile phone antenna design, streamlining factory processes, and quality control in hardware testing. Most recently he worked at Apple in Cupertino, California as an Antenna Design Engineer. He has published or co-published several papers and holds 7 patents. He believes that all scientists and professionals need to be data-savvy to make decisions and persuade actions. To enable that, he travels across India and around the world giving talks on data science and R programming. So far, he has trained 350 professionals on R Programming for data science. He has 17+ years experience across academia and industry.

Twitter: https://twitter.com/lan24hd

LinkedIn: https://www.linkedin.com/in/alakshmanan

Register here

• https://goo.gl/forms/fRu6MAXBibVK4Sw03

Session 1

• Why Data Science ?
• Motivation: Importance of visualization for decision making
• Demo: text vs. table vs. plot
• Installation of R and RStudio
• Hands-on coding to get started with ggplot2
• 1-variable plots, 2-variable plots and 3-variable plots
• Note on tidyverse

Session 2

• Data types : vectors, data frames, lists, factors
• Types of plots and choosing the best plot for your data
• Ordering, labeling and themes inside plots

Session 3

• Data importing : csv files, excel files, text files.
• Data wrangling : select, filter, mutate, arrange.

Session 4

• Facets: Improved multi-variable visualizations
• Visualizing and dealing with missing data
• Data reshaping and why

Session 5

• Functional programming
• purrr package and avoiding for-loops

Session 6

• Advanced graphing techniques
• Adding statistics and layers in ggplot2

Session 7

• Creating animations and gifs
• Creating reproducible reports using RMarkdown

Session 8

• Summary of course
• Project presentations