Introduction to NumPy

Learn one of the most in-demand Data Science packages in Python.
Rating: 3.5 out of 5 (32 ratings)
3,513 students
Introduction to NumPy
Rating: 3.5 out of 5 (32 ratings)
3,513 students
They will gain a deep understanding of the most widely used and in-demand Python packages to perform Data Science, Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Data Analysis, and Data Visualization tasks..

Requirements

  • Ability to understand and code Python programming language.
  • Knowledge of Machine Learning, Deep Learning, Computer Vision, and Natural Language Processing.
  • Familiarity with Statistics and Statistical plotting techniques.
  • Mathematical concepts used for Data Science-related tasks.
Description

This course will teach students about the NumPy packages for performing a wide array of tasks in the domain of Data Science using the Python Programming Language.

Start at the beginning and enrol in this course that teaches you everything you need to know about and work comfortably with, the NumPy package for performing numerical analysis on arrays of similar data. You will also be confident to work on an unfamiliar problem on your own as you will have the confidence to not be afraid to look deeper to find a solution.

Who this course is for:
  • Software Engineers looking to transition into Data Science.
  • Data Scientists who want to level-up their skill set.
  • Aspiring Data Scientists who want a single course to teach them all the popular Python packages.
Course content
1 section • 7 lectures • 35m total length
  • Introduction to NumPy
    01:39
  • NumPy Data Types
    03:52
  • NumPy Data Type Objects And The dtype Class
    05:06
  • Introduction to NumPy Arrays
    01:34
  • NumPy Array Creation
    01:45
  • Using Built-in Functions for Creating Arrays
    14:51
  • Creating Arrays using NumPy Numerical Ranges
    06:29

Instructor
Machine Learning Engineer
Taimur Z.
  • 3.8 Instructor Rating
  • 532 Reviews
  • 21,668 Students
  • 4 Courses

About Me: I am a Machine Learning Engineer, with over two years of experience in the field of Data Science and Machine Learning. I am a Former Teaching Assistant for the Deep Learning Master's Degree Course and the Natural Language Processing Course. I have a Bachelor's Degree in Computer Science, Nanodegrees in Deep Learning and Artificial Intelligence, and a keen interest in all things Data Science.

My Courses: I follow the agile development methodologies to design, create, and publish my courses. I follow small manageable sprints to update my courses regularly by either adding new content to existing courses or creating an entirely new course. This allows me to not only respond to and structure my courses based on direct student feedback, but also, to add the latest skill in demand as quickly as possible.