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This course introduces Python programming as a way to have hands-on experience with Data Science. It starts with a few basic examples in Python before moving onto doing statistical processing. The course then introduces Machine Learning with techniques such as regression, classification, clustering, and density estimation, in order to solve various data problems.
This course is for beginners, but it helps to have some basic understanding of statistics (mean, median, scatter plot) and preliminary knowledge of any programming. The course also assumes that you know how to download and install various programs/apps, and you are able to edit and debug simple programs.
- Writing simple Python scripts to do basic mathematical and logical operations
- Loading structured data in a Python environment for processing
- Creating descriptive statistics and visualizations
- Finding correlations among numerical variables
- Using regression analysis to predict the value of a continuous variable
- Building classification models to organize data into pre-determined classes
- Organizing given data into meaningful clusters
- Applying basic machine learning techniques for solving various data problems