NumPy for Scientific Computation with Python
Welcome to the course on NumPy for Scientific Computation with Python!
NumPy, or Numerical Python, is an open-source Python library that helps you perform simple as well as complex computations on numerical data. It is the go-to scientific computation library for beginners as well as advanced Python programmers and it is used mostly by statisticians, data scientists, and engineers.
This course aims to introduce students to NumPy and its functions and teaches all the basic fundamental concepts needed to use NumPy.
The learning objectives of the course are set out as follows:
- Learn how to install and import NumPy.
- Learn the basics of NumPy arrays.
- Learn to create NumPy arrays using built-in functions and Python data structures.
- Learn about arithmetic, statistical and transformative NumPy array operations.
- Learn how to save/load NumPy array in different file formats.
You can expect to have all of these objectives met by the time you reach the end of this course.
For this course, you need to be familiar with the Python Programming Language. If you are new to Python, you can check out our previous course on ‘Python Programming for Newbies’.
Best way to work through the course
This course is detailed and requires a good amount of attention from your end.
If you come across any problem, please check to see if your code matches exactly with the course or not. If you still are facing errors or have some doubts, please provide your question through the comment section of the specific chapter you are stuck on.
We also recommend you join our community and get connected to our vibrant network of data science aspirants. Once you are in the community, you can share your learning, form a study group or even get help building a project around NumPy.
Ready to add a fundamental skill to your Data Science toolbelt? Let’s get started.