Let us say the Department of Transportation is considering the addition of a new airport. As the incredible data scientist, you are, you have been requested to explore existing data. The results of your analysis might form the basis of a report or a machine learning mode.
In this session, you will explore a real-world dataset containing flights data from the US Department of Transportation.
What is the session about?
This is the first episode of the Four-part series - An introduction to R and Machine learning.
In this session you will learn about common data exploration and analysis tasks, as well as how to use R packages such as ggplot2, dplyr, and tidyr to turn raw data into understanding, insight, and knowledge.
Who is it aimed at? This session is aimed at anyone who would like to get started with data science in R
Why should you attend? Learn how to perform data exploration and visualization through Tidyverse R packages
Any pre-requisites? Knowledge of basic mathematics Some experience programming in R
What will we cover in the session?
Cleaning data to handle errors, missing values, and other issues.
Exploratory data analysis (EDA) to analyze and investigate data sets and summarize their main characteristics (e.g., distribution).
Speaker Bio's Carlotta Castellucio – Cloud Advocate, Microsoft Carlotta Castelluccio is a Cloud Advocate at Microsoft, focused on Data Analytics and Data Science. As a member of the Developer Relationships Academic team, she works on skilling and engaging educational communities to create and grow with Azure Cloud, by contributing to technical learning content and supporting students and educators in their learning journey with Microsoft technologies. Before joining the Cloud Advocacy team, she worked as an Azure and AI (ARTIFICIAL INTELLIGENCE) consultant in Microsoft Industry Solutions team, involved in customer-face engagements focused on Conversational AI solutions. Carlotta earned her master's degree in Computer Engineering from Politecnico di Torino and her Diplôme d'ingénieur from Télécom ParisTech, by completing an E+/EU Double Degree Program.
Eric Wanjau - Data Scientist/Researcher at the Leeds Institute for Data Analytics (LIDA)
Eric is an Early Career Researcher who continually seeks to tackle real-world challenges using applied research, data analytics and machine learning; all wrapped in unbridled empathy and enthusiasm. He is currently a Data Scientist/Researcher at the Leeds Institute for Data Analytics (LIDA) in the University of Leeds, working on the British Academy project undertaking urban transport modelling in Hanoi. He has also done research in robotics, computer vision and speech processing in Japan and Kenya, aimed at creating safe working environments and exploring human-robot interaction in board games. Eric holds a BSc. in Electrical and Electronic Engineering (2021) from Dedan Kimathi University of Technology Kenya. He plays the guitar (terribly but passionately).