What you'll learn:
- Learn to confidently work with vectors and matrices in NumPy.
- Learn basic functionality like sorting, calculating means, and finding max/min values.
- Learn to draw line plots, bar plots, and scatterplots.
- Learn to generate different types of random vectors.
- Learn to modify and reshape matrices to your advantage.
- Learn Boolean indexing and advanced slicing to extract useful information.
- Learn to do basic linear algebra in NumPy like solving linear systems, calculating inverses, and more!
- Get an understanding of how ndarrays work and utilize this to create fast code.
- Learn Fourier transforms with NumPy and use this to manipulate images and audio.
- Learn advanced linear algebra like the QR decomposition and partial least squares.
- Learn how to preserve your NumPy objects in different formats.
- Learn about neighboring libraries and that NumPy is used everywhere in Python's data science stack.
Do you want to master NumPy and unlock your potential in data science? This course is your comprehensive, hands-on introduction to the foundational library of modern Python computing!
NumPy is the absolute core building block for essential data science and machine learning libraries like Pandas, Scikit-learn, and PyTorch. By mastering it, you gain the technical edge needed for advanced topics like linear algebra, image processing, and fast numerical computations. If you want to start a career in Data Science or understand the engine behind Machine Learning in Python, this course is for you.
What You'll Master in this Hands-On Python Course:
This course will teach you everything you need to professionally use NumPy for scientific computing. We start with the basics and rapidly move into advanced techniques crucial for complex data science tasks.
Foundation: Introduction to NumPy arrays, N-dimensional arrays, and the fundamental concepts of vectors and matrices.
Data Analysis Tools: Leverage Universal Functions (ufuncs), Randomness, and Statistics to analyze and explore data efficiently in Python.
Linear Algebra for ML: Master Basic and Advanced Linear Algebra operations, which are the backbone of all Machine Learning algorithms.
Advanced Techniques: Understand Broadcasting and Advanced Indexing to write fast, memory-efficient Python code.
Real-World Scientific Computing: Apply NumPy to specialized fields like Fourier Transforms, Image Processing, and data manipulation for Simple Machine Learning models.
Data Management: Learn professional methods for Saving and Loading Data efficiently.
Why Choose Our Course? Expertise Meets Practical Application
We are Eirik and Stine, a couple passionate about creating high-quality, impactful courses. Eirik has taught both Python and NumPy at the university level, while Stine has developed curriculum used in university courses utilizing NumPy for data science.
We don't shy away from the technical depth that will make you a standout practitioner. The course is filled with:
In-Video Exercises to reinforce concepts immediately.
Large, Project-Style Assignments (in Jupyter Notebooks) on awesome topics like Audio Processing, Linear Regression (a core Machine Learning task), and Image Manipulation.
By the end of our course, you will be highly proficient with NumPy and have a rock-solid technical foundation for pursuing Data Science and Machine Learning roles in Python.
No Risk, Just Learning
You're covered by Udemy’s 30-day money-back guarantee. Preview some free lessons and see why our teaching style is perfect for you. Start your journey into Scientific Computing and Data Science today!
