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Systems with Python Statistical Modeling

Track :

Programming

Lessons no : 7

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What will you learn in this course?
  • Apply Python's built-in statistics library for descriptive analysis and basic data summarization using real-world datasets
  • Utilize NumPy for efficient numerical computations and manipulation of multi-dimensional arrays in statistical modeling
  • Implement Python code to perform data cleaning, transformation, and exploratory data analysis for statistical insights
  • Develop skills to visualize data distributions and relationships using Python's statistical and numerical libraries
  • Optimize data processing workflows with Python for handling datasets of varying sizes in statistical projects
  • Troubleshoot common issues in Python statistical modeling and improve code efficiency for accurate results

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Lessons | 7


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Python's statistics is a built-in Python library for descriptive statistics. You can use it if your datasets are not too large or if you can't rely on importing other libraries. NumPy is a third-party library for numerical computing, optimized for working with single- and multi-dimensional arrays.