Science Score: 67.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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✓DOI references
Found 2 DOI reference(s) in README -
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○Scientific vocabulary similarity
Low similarity (8.8%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: C7081-2022
- License: mit
- Language: Jupyter Notebook
- Default Branch: main
- Size: 38.5 MB
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Metadata Files
README.md
C7081 Statistical Analysis for Data Science - Course Website
Harris, W. E. (2022). Statistical analysis for data science: A self-paced course for machine and statistical learning. https://c7081-2022.github.io/website/ https://github.com/C7081-2022/website 
This repository contains the course website for C7081 Statistical Analysis for Data Science (2022) at Harper Adams University.
About
C7081 is a survey of machine learning and statistical methods including supervised and unsupervised classification, regression, and tree-based methods. The course emphasizes practical applications using data stories and lab exercises, complemented by lectures and readings.
This course is part of the MSc in Data Science for Global Agriculture, Food, and Environment program at Harper Adams University, led by Ed Harris.
Prerequisites
A prerequisite for this course is basic working knowledge of R programming and introductory statistics.
Course Resources
Textbooks: - James et al. 2023 Introduction to Statistical Learning for Python - James et al. 2021 Introduction to Statistical Learning for R 2ed
Student Support: - Slack workspace (for enrolled students) - Office hours (Slack, Fridays by appointment)
Website
The course website is available at: https://c7081-2022.github.io/website/
Contact
For questions about the course content, please contact Ed Harris or use the Slack workspace for enrolled students.
About Harper Adams University
This course is offered as part of Harper Adams University's commitment to excellence in agricultural and environmental education. Learn more about the university at harper-adams.ac.uk.
License
This project is licensed under the MIT License - see the LICENSE file for details.
W. Edwin Harris C7081 Statistical Analysis for Data Science - Harper Adams University, 2022 Part of the MSc in Data Science for Global Agriculture, Food, and Environment
Citation (CITATION.cff)
cff-version: 1.0.0
message: "If you use this software, please cite it as below."
title: "Statistical analysis for data science"
abstract: "This module is a survey of machine learning and statistical methods including supervised and unsupervised classification, regression, and tree-based methods. There is an emphasis on practical applications using a series of data stories and lab exercises, along with lectures on selected topics and readings. A prerequisite is a basic working knowledge of R programming and introductory statistics."
authors:
- family-names: "Harris"
given-names: "W. E."
orcid: "https://orcid.org/0000-0002-9038-8656"
title: "R Stats Bootcamp"
version: 2022.1.0
doi: 10.5281/zenodo.15668388
date-released: 2022-08-01
url: "https://c7081-2022.github.io/website/"
license: MIT
keywords:
- R programming
- python programming
- statistics
- machine learning
- data analysis
- reproducible research
- educational materials
- self-paced learning
preferred-citation:
type: misc
authors:
- family-names: "Harris"
given-names: "W. E."
orcid: "https://orcid.org/0000-0002-9038-8656"
affiliation: "Centre for Agricultural Data Science, Harper Adams University"
title: "Statistical analysis for data science: A self-paced course for machine and statistical learning"
year: 2022 # Update to your publication year
url: "https://c7081-2022.github.io/website//"
doi: "10.5281/zenodo.15668388"
publisher: "Centre for Agricultural Data Science, Harper Adams University"
notes: "Open educational resource for learning machne and statistical learning"
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