edX
edXPython for Data Science and Deep Learning
70k studentsINTERMEDIATEEnglish
Korshub's take
Python, Data, and Real Problems
Theory withers—working code on real data is what counts. Use Python's standard toolkit (Pandas, numPy, matplotlib, scikit-learn) to solve actual problems: build regression models (linear, polynomial, multilinear), run decision trees and random forests, evaluate results honestly. Along the way, spot the traps: data bias, underfitting, overfitting—the silent errors that make models fail in production. Hands-on from the first day.
Practical focus:
- Regression models and evaluation
- Decision trees and random forests
- Libraries: Pandas, scikit-learn, matplotlib
- Bias recognition and model validation
About this course
Gain hands-on experience using Python to solve real-world data problems. ,Explore regression models, including linear, multilinear, and polynomial models. ,Use popular Python libraries such as Pandas, numPy, matplotlib, and SKLearn. ,Explore advanced data science challenges through sample data sets, decision trees, and random forests. ,Build on your Python skills run basic machine learning models, evaluating the results and recognizing data bias to avoid underfitting or overfitting data.
Price
$897
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