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Corporate Training

SIRPI's Corporate Onboarding training prepares fresh recruits to become effective contributors to your organization. Dr. Anand Lakshmanan, Ex-Apple Design Engineer, will be the chief trainer who will draw upon his experiences, engage with participants, and challenge them. Training methods include case studies, visualization best practices and pitfalls, cognitive biases to watch-out for, and writing effective code that is easy to debug and collaborate with. Training will be all hands on using R Programming (tidyverse methods) as the tool of practice.

  • Why Data Science?

  • Introduction to R-Programming.

  • Visualization, human perception, tidyverse, pipes.

  • Data Importing, Data

  • Transformations, Tables, Plots, Themes and Customizations

  • Data Reshaping and Data Tidying.

  • Set Operations with Data Frames.

  • Adding statistics and layers in ggplot2.

  • Facets: Improved multi-variable visualizations

  • Visualizing and dealing with missing data

  • Data Viz Do's and Dont's

Training Agenda

  • Functional Programming and Vectorized Operations.

  • Dates & times, strings, dashboards Animations.

  • Creating reproducible reports using RMarkdown Maps.

  • Adding interactivity using the 'shiny' package.

  • Introduction to modelling.

  • Visualizing model outputs the tidyverse way.

  • Linear Algebra Review.

  • Operations Research and RProgramming.

  • Introduction to Machine Learning.

Data Storytelling

There is no such thing as information overload. There are only bad designs & stories!

The aim of the workshop on Data Storytelling is to enable potential participants (project coordinators, customer-facing team leaders, managers, directors etc.) to infuse elements of liberal arts, particularly storytelling, while presenting data science insights to key stakeholders.

Key learning objectives: Data Visualization, Storytelling, Decision Support. 

To know more click here

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About the instructor

Dr. Anand Lakshmanan
Founder & CEO

Dr. Anand Lakshmanan has helped academic institutions and corporations deep dive into their data and make better decisions. He has 17+ years experience in academia and industry. He has designed experiments and analyzed data in areas across domains.

Most recently he worked at Apple in Cupertino, California as an Antenna Design Engineer for 6 years. 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.

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