Intro to Data Science and Machine Learning Bootcamp | Online
About this workshop
This one day workshop will introduce students to data exploration and machine learning techniques. Students will learn about the data science workflow and will practice exploring and visualising data using R and built in libraries. Students will also explore the differences between supervised and unsupervised learning techniques and practice creating predictive regression models.
A background in computer science, programming, and/or statistics is preferred for this workshop. It is not required but you are expected to be somewhat familiar with the command line tools and how to write simple programs.
Please bring a laptop with R and R Studio pre-installed. You can download them from the links below:
Takeaways
PART I: Data Exploration
- Understand course contents and structure
- Describe the data mining workflow and the key traits of a successful data scientist.
- Extract, format, and preprocess data using UNIX command-line tools.
- Explore and visualise data using R and ggplot2.
PART II: Intro to Machine Learning
- Explain the concepts and applications of supervised & unsupervised learning techniques.
- Describe categorical and continuous feature spaces, including examples and techniques for each.
- Discuss the purpose of machine learning and the interpretation of predictive modeling results.
Prereqs & Preparation
A background in computer science, programming, and/or statistics is preferred for this workshop. It is not required but you are expected to be somewhat familiar with the command line tools and how to write simple programs.
Please bring a laptop with R and R Studio pre-installed. You can download them from the links below:
