STATS 131
Python and Other Technologies for Data Analysis
Description: Lecture, three hours; discussion, one hour. Requisite: course 102A. Limited to junior/senior statistics majors and minors. Use of Python and other technologies for data analysis and data science. Focus on programming with Python and selection of its libraries--NumPy, pandas, Matplotlib, and scikit-learn--for purpose of data processing, data cleaning, data analysis, and machine learning. Other technologies covered include Jupyter notebook, Structured Query Language (SQL), and git. P/NP or letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Fall 2019 - Much of the learning is done through Data Camp, plus some in-class presentations in Jupyter notebook by Prof Chen. Lectures are recorded and posted on YouTube, so attendance is not necessary (Almost no one attended the last 2 lectures before Thanksgiving). Felt like only learned mostly from Data Camp exercises for data analysis, only the last few lectures were brand new material outside Data Camp. Not the best class to fully master Python as modeling and ML techniques were only simply or briefly discussed
Fall 2019 - Much of the learning is done through Data Camp, plus some in-class presentations in Jupyter notebook by Prof Chen. Lectures are recorded and posted on YouTube, so attendance is not necessary (Almost no one attended the last 2 lectures before Thanksgiving). Felt like only learned mostly from Data Camp exercises for data analysis, only the last few lectures were brand new material outside Data Camp. Not the best class to fully master Python as modeling and ML techniques were only simply or briefly discussed
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