Course Overview With this Python NumPy: Scientific Computing with Python course, you’ll begin with an introduction to NumPy and take a tour of NumPy’s features. Then you’ll move on to topics such as matrices, deviations, Eigen values, and covariance. You’ll finish with a real-world project utilizing the included resource files. Get ready to learn this fundamental scientific library for Python! Length: 1 hr Example Video Course Outline This Python NumPy: Scientific Computing with Python course provides a thorough understanding of NumPy’s features and when to use them. NumPy is mainly used in matrix computing. We’ll do a number of examples specific to matrix computing, which will allow you to see the various scenarios in which NumPy is helpful. There are a few computational computing libraries available for Python. It’s important to know when to choose one over the other. Through rigorous exercises, you’ll experience where NumPy is powerful and develop an understanding of the scenarios in which NumPy is most useful. Course goals: Express fully why NumPy should be used Ability to install NumPy Understanding of how to use NumPy Learn anytime, anywhere, at home or on the go. Length of Subscription: 12 Months Online On-Demand Access Running Time: 1 hour Platform: Windows andamp; MAC OS Level: Beginner to Intermediate Stream your training via the internet, or download to your computer and supported mobile device, including iPad™, iPhone™, iPod™ Touch and most Android devices. Need to train your Team? Contact Us for Discounts on Multiple Subscription Purchases.