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Python numpy

Track :

Programming

Course Presenter :

ProgrammingKnowledge

Lessons no : 33

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What will you learn in this course?
  • Master array creation, manipulation, and mathematical operations using Python NumPy for data analysis and scientific computing
  • Implement array indexing, slicing, reshaping, and broadcasting techniques to handle large datasets efficiently in Python
  • Apply vectorization, random number generation, and statistical functions to accelerate data processing and analysis workflows
  • Integrate NumPy with Pandas and Matplotlib to enhance data visualization, statistical analysis, and machine learning projects

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Lessons | 33

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Python numpy , in this course introduces you to one of the most powerful libraries for numerical and scientific computing in Python. You’ll learn how to install NumPy, create arrays, and perform mathematical operations efficiently. The course covers array indexing, slicing, reshaping, and broadcasting, helping you manipulate large datasets with ease. You’ll explore key concepts like vectorization, random number generation, and statistical functions to speed up data analysis tasks. Through practical exercises, you’ll see how NumPy integrates with other libraries such as Pandas and Matplotlib to form the foundation of data science and machine learning workflows. By the end, you’ll have a solid understanding of how to use NumPy for fast and efficient numerical computation — an essential skill for any data analyst, programmer, or Python enthusiast. ProgrammingKnowledge