Python Fundamentals: Part 1

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 1 Topics:

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Git Fundamentals

Git is a powerful tool for keeping track of changes you make to the files in a project. You can use it to synchronize your work across computers, collaborate with others, and even deploy applications to the cloud. In this workshop, we'll learn the basics of understanding and using Git, including working with the popular "social coding" website, GitHub.

Are you uneasy working on the command line? Register for Programming FUN!damentals!

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Programming Fundamentals

An intro to the basics that instructors often assume you know, but that you probably never had good instruction on! After this course, you should be able to more easily start learning to program (e.g., in our R or Python Fundamentals series), follow instructions and documentation online (e.g., StackExchange), and communicate better with your collaborators who are programming. If you are just starting out and don’t know which language to learn, or what a programming language even is, this workshop is for you! No prior knowledge expected. This interactive workshop will cover:

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R Fundamentals: Part 4

R Fundamentals Part 4: Putting it all together

In the final part, we will review data importation, subsetting, and visualization. Students will then be given the majority of time to reproduce a workflow on two different datasets, ask questions, and review the solutions as a group.

 

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R Fundamentals: Part 3

R Fundamentals Part 3: Data Exploration and Analysis

Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots. You will also be introduced to coding statistical data analysis via t-tests, analyses of variance, correlation, and linear regression.

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R Fundamentals: Part 2

R Fundamentals Part 2: Subsetting and Reshaping

Students will be introduced to loading data from files and various ways to subset it with an emphasis on bracket notation. You will also learn how to use logical vectors, search for and subset missing data, and merge data frames. Terms like subset, bracket notation, and logical vectors will be defined or reintroduced in Part 2.

 

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R Fundamentals: Part 1

Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills for free at our R workshops!

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Introduction to Machine Learning in R: Part 2

Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data. To social scientists, such methods might be critical for investigating evolutionary relationships, global health patterns, voter turnout in local elections, or individual psychological diagnoses.

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Introduction to Machine Learning in R: Part 1

Machine learning often evokes images of Skynet, self-driving cars, and computerized homes. However, these ideas are less science fiction as they are tangible phenomena that are predicated on description, classification, prediction, and pattern recognition in data. To social scientists, such methods might be critical for investigating evolutionary relationships, global health patterns, voter turnout in local elections, or individual psychological diagnoses.

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Python Fundamentals: Part 4

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 4 Topics: We will applying the skills learned during previous sessions to a real world social science example.

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