Python for Data Science Bootcamp
In this bootcamp you will learn the core elements of the Python programming language. You will complement this with knowledge of some of the most popular libraries in data analysis and data visualization. No prior programming experience is required.
About this Bootcamp
In this bootcamp you will learn the most basic and essential aspects of Python programming. The topics are tailored towards data analysis; no prior programming experience is required. We will cover variables, data types and data structures, data frames, conditionals, loops, and functions. We will also cover reading and writing raw files, and the core APIs in analysis and visualization. With the basics under your belt, we will complement it with some of the most popular libraries for data analysis in Python, such as: Pandas and Numpy for data manipulation, Matplotlib for visualization, and Jupyter Notebook for analysis and reporting. These packages will facilitate workflow and enhance the basic Python functionalities; using them, one can effortlessly clean up a dataset, create elaborate plots, analyze and summarize the data, and produce presentable reports. At the end of the module, you solidify your new skills by applying the concepts you have learned to the analysis of several datasets. You will be given the opportunity to live-code during the sessions and troubleshoot your code with your classmates and the instructor. You will walk out of this bootcamp with newly-forged Python coding skills, knowledge of several of the most important data science libraries and tools, and have resources in hand for learning more.
Schedule
This content will be delivered as an intensive “module” in the Spring 2019 term. The module does not count for course credit — but is a great way to build marketable skills that you can include on your resume. The schedule will be as follows, and it is expected that students attend ALL sessions:
- Saturday, Jan 26: 10:00-1:00, 2:00-5:00
- Sunday, Feb 3: 10:00-1:00, 2:00-5:00
- Saturday, Feb 9: 10:00-1:00, 2:00-5:00
All sessions will be taught by Professor Mohammad Soltanieh-Ha.
Apply
We are accepting 40 students for this bootcamp. Please apply below.
Learn Essential R Programming!
Complement this with knowledge of some of the most popular libraries in data analysis and data visualization. Apply these skills to several in-demand applications. No prior programming experience required.
About this Bootcamp
In this bootcamp you will learn the core elements of the R programming language. With this under your belt, we will complement it with a few more advanced libraries and capabilities. We will cover variables, data types and data structures, data frames, conditionals and loops, and functions. We will also cover reading and writing CSV files, and the core APIs in analysis and visualization. You will be introduced to the most popular libraries for data analysis in R, such as dplyr, ggplot2, readr,and rmarkdown. These packages will facilitate workflow and enhance the basic R functionalities; using them, one can effortlessly clean up a dataset, create elaborate plots, analyze and summarize the data, and produce presentable reports. At the end of the module, you solidify your new skills by applying the concepts you have learned to the analysis of several datasets. You will be given the opportunity to live-code during the sessions and troubleshoot your code with your classmates and the instructor. You will walk out of this bootcamp with newly-forged R coding skills, knowledge of several of the important R libraries and tools, and have resources in hand for learning more.
Schedule
This content will be delivered as an intensive “module” in the Spring 2019 term. The module does not count for course credit — but is a great way to build marketable skills that you can include on your resume. The schedule will be as follows, and it is expected that students attend ALL sessions:
- Saturday, Feb 9: 9:30-12:30, 2:00-5:00
- Saturday, Feb 16: 9:30-12:30, 2:00-5:00
- Saturday, Feb 23: 9:30-12:30, 2:00-5:00
All sessions will be taught by Professor Brock Tibert.
Apply
We are accepting 40 students for this bootcamp. Please apply below.

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