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Dive into formal statistical thinking and computational methods in Data Science through Boston University's Research in Science and Engineering (RISE) program. This repo features materials and example code for mastering computational statistics and conducting meaningful research in the RISE Practicum.

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Boston University's RISE Data Science Practicum Track

Welcome to the official GitHub repository for the Data Science RISE Practicum Track course! This course introduces formal statistical thinking and computational methodologies to empower high school students to become skilled computational scientists. Here, you'll find many of the resources, code, and collaborative materials necessary to succeed in the course and Practicum.


Course Overview

In this course, students will:

  • Learn the principles of formal statistical thinking to gain insights into measurement, data collection, experimental design, and uncertainty quantification.
  • Analyze real-world datasets from fields like neuroscience, environmental science, physics, economics, and urban planning.
  • Develop skills in computational modeling, scientific reproducibility, and rigorous ethical practices for data-informed research.

RISE Practicum

The RISE Practicum provides students with hands-on experience in conducting computational research in one of three key areas:

  1. Computational modeling (e.g., time series forecasting).
  2. Statistical Method Benchmarking.
  3. Scientific Software Development.

The Practicum combines instructor-led morning lectures with collaborative lab work in the afternoon. Students will present their research findings at the RISE Poster Symposium at the program's conclusion.


Instructors

Meet the dedicated instructors for the RISE Data Science Practicum Track who guide students through this immersive learning experience:

  • Course Designer and Morning Lecturer: [Patrick F. Bloniasz, Computational Neuroscience PhD Candidate]

    • Expertise: [Brief description of their expertise and background]
    • Contact: [pblonias [at] bu.edu]
  • Lab Lead Lecturer: [Name, Title]

    • Expertise: [Brief description of their expertise and background]
    • Contact: [Email or other contact details]
  • Teaching Fellow: [Name, Title]

    • Expertise: [Brief description of their expertise and background]
    • Contact: [Email or other contact details]

Repository Structure

Here's what you can find in this repository:


Installation

To run the code and work through the examples, you'll need to have Python (>=3.7) installed, along with the required dependencies.

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Dive into formal statistical thinking and computational methods in Data Science through Boston University's Research in Science and Engineering (RISE) program. This repo features materials and example code for mastering computational statistics and conducting meaningful research in the RISE Practicum.

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