GETTING STARTED WITH R AND DATA ANALYSIS

Transcription

1 GETTING STARTED WITH R AND DATA ANALYSIS [Learn R for effective data analysis]

2 LEARN PRACTICAL SKILLS REQUIRED FOR VISUALIZING, TRANSFORMING, AND ANALYZING DATA IN R One day course for people who are just starting with R as well as for data analysts who are switching to R from other statistical software, such as SAS, SPSS or Excel. R IS THE LEADING TOOL FOR STATISTICS, DATA ANALYSIS, AND MACHINE LEARNING R is an open source environment for statistical computing. R was created in 1993 by Ross Ihaka and Robert Gentleman of the University of Aukland, New Zealand. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories by John Chambers and colleagues. R provides an integrated environment for data manipulation, calculation and graphical display. Worldwide, millions of statisticians and data scientists use R for data manipulation, statistical modelling, and graphical analysis. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, and many machine learning methods) and graphical techniques, and is highly extensible. You can easily find, download and use 4000 plus methods in statistics, predictive modeling, and machine learning free of charge.

3 WHAT IS THIS COURSE ABOUT? Are you tasked with analysing data, or are you about to be? Have you been using proprietary data analysis tools and would like to explore open source? If so, you are in for a treat as we introduce you to the most popular and rapidly growing open source statistical package R. In this course you will learn how to use R for effective data analysis, how to install and configure software necessary for a statistical programming environment, learn and practice R programming language concepts, common and useful R commands. You will learn to use R for reading data, writing functions, making informative graphs, and applying basic statistical methods. As more and more business activity is digitized, new sources of information and ever-cheaper equipment combine to bring us into a new era: one in which large amounts of digital information exist on virtually any topic of interest to a business Andrew McAfee and Erik Brynjolfsson

4 WHAT WILL YOU LEARN? + Overview and introduction to R + Getting started and working with data + Basic data types and operations + Data Frames + Importing, saving, exporting, and re-using data + Common R functions for numbers, factors, text, and dates + Vector-oriented computation + Sorting, ranking, and printing + Reading and writing data with R + Reading tables and CSV files, row and column headers, delimiters. Built-in data. + Cleaning and transforming data + Programming efficiently in R + Writing R scripts and functions + Loops and conditions + Flow control, functions and classes in R, executing R scripts from GUI and command line + Visualizing data and Exploratory Data Analysis + Basic data summary functions/ summary statistics + Exploring and plotting relationships between variables + Visualizations for categorical and continuous data, scatter plots, box plots, pie charts, histograms, bar plots, dot charts, and the char object. WHO SHOULD TAKE THIS COURSE? The course is aimed at business professionals, data analysts, technologists, journalists, software developers, academics and students who already have some basic competence in using statistics but wish to begin using R for the first time.

5 PREREQUISITES Basic knowledge of statistics and programming languages. WHAT SHOULD I BRING? Along with bringing your laptop and charger, don t forget to bring loads of curiosity, scepticism, eagerness to participate and the desire to learn. COURSE INSTRUCTORS Persontyle trainers are passionate about meeting each participants learning needs. They have been chosen both for their extensive practical Data Science and Machine Learning experience and for their ability to educate and interact with natural empathy. All of our trainers have worked on a variety of data science and Machine Learning projects. They share their academic knowledge and real-world experience and each individual adds their own unique perspective to the course. Our trainers present in a style that is informal, entertaining and highly interactive. Guest Speakers Business leaders, Data Science practitioners, and academic researchers covering use cases, case studies and sharing practical experience of applying Data Science and Machine Learning in their organizations. I keep saying the sexy job in the next ten years will be statisticians. People think I'm joking, but who would've guessed that computer engineers would've been the sexy job of the 1990s? Professor Hal Varian, Chief Economist at Google

6 RETURN ON INVESTMENT (ROI) CONVINCE YOUR BOSS The advent of the data driven connected era means that analyzing massive scale, messy, noisy, and unstructured data is going to increasingly form part of everyone's work. The School of Data Science learning programs provide a unique investment opportunity that pay s for itself many times over. World-class Instructors Develop Practical Data Science Skills Real World Industry Use Cases Short Courses For Time Convenience Value For Money "For the best return on your money, pour your purse into your head." Benjamin Franklin Limited seats. We encourage you to register as soon as you can. Register Now For corporate bookings or to organize on-site training [email protected] or call now +44 (0) THE SCHOOL OF DATA SCIENCE The School of Data Science, a project of Persontyle, specializes in designing and delivering structured, relevant and practical learning experiences for all of us to understand data science in simple human terms. /school Follow us on Like us on Facebook Get in touch! [email protected]