Introduction to NumPy
- 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.
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.
- 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.
- Introduction to NumPy01:39
- NumPy Data Types03:52
- NumPy Data Type Objects And The dtype Class05:06
- Introduction to NumPy Arrays01:34
- NumPy Array Creation01:45
- Using Built-in Functions for Creating Arrays14:51
- Creating Arrays using NumPy Numerical Ranges06:29
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.