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Quantitative Applications for Data Analysis
(Winter 2021)
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Wednesday May 29, 2024 - 05:05
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EES1137.2021.Syllabus.pdf
Syllabus for 2021 EES1137.
Erik Spence (ejspence)
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290.33
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2021-01-11 12:27
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1 Description
2 Zoom Meeting Info
3 Software Requirements
4 Lectures
4.1 Intro to Linux Shell I
4.2 Intro to Linux Shell II
4.3 Introduction to R
4.4 Vectors and data frames
4.5 Loops, conditional stateme...
4.6 Scripts
4.7 Version Control - Git
4.8 Coding Best Practices
4.9 Distributions
4.10 Hypothesis tests
4.11 Linear models
4.12 Visualization in R
4.13 Introduction to Python
4.14 Loops and functions in Python
4.15 NumPy, SciPy and Visualization
4.16 Intro to Machine Learning
4.17 Resampling
4.18 Classification II
4.19 Unsupervised learning
4.20 Feature selection
4.21 Neural networks
4.22 Ensemble methods
5 Recordings
5.1 Intro to Linux Shell I
5.2 Intro to Linux Shell II
5.3 Introduction to R
5.4 Vectors and data frames
5.5 Loops, conditionals and fu...
5.6 Scripts
5.7 Version control
5.8 Coding Best Practices
5.9 Distributions
5.10 Hypothesis tests
5.11 Linear models
5.12 Visualization in R
5.13 Introduction to Python
5.14 Loops and functions in Python
5.15 Numpy, Scipy and Visualization
5.16 Intro to Machine Learning
5.17 Resampling
5.18 Classification II
5.19 Unsupervised learning
5.20 Feature selection
5.21 Neural networks
5.22 Ensemble methods
6 Assignments
6.1 Assignment 1
6.2 Assignment 2
6.3 Assignment 3
6.4 Assignment 4
6.5 Assignment 5
6.6 Assignment 6
6.7 Assignment 7
6.8 Assignment 8
6.9 Assignment 9
6.10 Assignment 10
6.11 Assignment 11 - Makeup
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Related
Quantitative Applications for Data Analysis (Winter 2020)
Quantitative Applications for Data Analysis (Winter 2019)
Quantitative Applications for Data Analysis (Winter 2018)
Quantitative Applications for Data Analysis (Winter 2017)
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