In this comprehensive Numpy Python course for data analysis, instructed by Faisal Zamir, spanning over 6+ hours of content, you’ll embark on a journey through the fundamentals of Numpy.
Chapter 01 provides a solid introduction to Numpy, covering the environment setup.
In Chapter 02, you’ll dive into creating and accessing arrays, mastering indexing and slicing techniques, exploring array dimensions, and understanding the ndarray object and its data types, along with data type conversion.
Chapter 03 delves into array attributes, various methods of array creation, and working with existing data.
Chapter 04 explores broadcasting and array iteration, allowing you to update array values efficiently.
Chapter 05 is dedicated to array manipulation operations, including joining, transposing, splitting, and other essential array operations.
In Chapter 06, you’ll explore Numpy’s binary operators, such as bitwise_and, bitwise_or, invert, left_shift, and right_shift.
Chapter 07 introduces string, mathematical, and trigonometric functions.
Chapter 08 covers arithmetic operations like addition, subtraction, multiplication, division, and more, along with statistical and counting functions.
Chapter 09 is all about sorting, including functions like sort, argsort, lexsort, searchsorted, partition, and argpartition.
Finally, in Chapter 10, you’ll learn about views and copies in Numpy. This course is your gateway to mastering Numpy for data analysis, equipping you with the essential tools and knowledge to excel in this field.
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