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Algorithms, Part I
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Learn Git and GitHub with Data School in under an hour. This hands-on introduction covers setup, navigation, forking, committing changes, and troubleshooting.
Data School offers a hands-on introduction to faster data manipulation in R using dplyr, with 1-2 hours of material.
Learn machine learning techniques with Data School in a 4-5 hour program, covering confusion matrix, ROC curves, AUC, and Python basics.
Master Python's scikit-learn library for effective machine learning with Data School's 7-hour program. Learn model training, comparison, selection, and evaluation.
Master data analysis, manipulation, and visualization using Python's pandas library with Data School's 12-hour program. Learn through real datasets and interactive Q&A sessions.
Data School offers a quick, under 1-hour guide to web scraping in Python, teaching you to build your own dataset and export a CSV with pandas.
Master data science tasks on real-world datasets using pandas with Data School. Learn to avoid common pitfalls in a 1-2 hour workload.
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