Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
10 Hour(s) 47 Minute(s)
Language
English
Taught by
Ashwin Pajankar • 85,000+ Students Worldwide
Rating
Course Overview
Learn to code Scientific Python recipes and Image Processing with NumPy, SciPy, Matplotlib, and Jupyter Notebook
Become a Master in Scientific Python and acquire employers' one of the most requested skills of 21st Century! A great Scientific Python programmer earns more than $150000 per year.
This is the most comprehensive, yet straight-forward course for the Scientific Python on Udemy! Whether you have never used SciPy before, already know basics of Python, or want to learn the advanced features of NumPy with Python 3, this course is for you! In this course we will teach you NumPy, SciPy, Matplotlib, and Jupyter Notebook.
With over 100 lectures and more than 10 hours of video this comprehensive course leaves no stone unturned in teaching you Scientific Python!
This course will teach you Scientific Python in a very practical manner, with every lecture comes a full Python 3 programming video and a corresponding Jupyter notebook that has Python 3 code! Learn in whatever manner is the best for you!
We will start by helping you get Python3, NumPy, Matplotlib, Jupyter, and SciPy installed on your Windows computer and Raspberry Pi.
We cover a wide variety of topics, including:
Basics of Scientific Python Ecosystem
Basics of SciPy, NumPy, and Matplotlib
Installation of Python 3 on Windows
Setting up Raspberry Pi
Tour of Python 3 environment on Raspberry Pi
Jupyter installation and basics
Ndarrays
Array Creation Routines
Basic Visualization with Matplotlib
Ndarray Manipulation
Installation of SciPy
Image Processing with NumPy and Matplotlib
NumPy and SciPy
Scientific and Business Visualizations
K-Means clustering with SciPy
You will get lifetime access to over 100 lectures plus corresponding PDFs and the Jupyter notebooks for the lectures!
So what are you waiting for? Learn SciPy, NumPy, and Matplotlib in a way that will advance your career and increase your knowledge, all in a fun and practical way!
Course Content
- 10 section(s)
- 100 lecture(s)
- Section 1 Introduction
- Section 2 Python 3 on Windows
- Section 3 Raspberry Pi and Python
- Section 4 Python 3 Basics
- Section 5 Python Package Index and pip
- Section 6 Install NumPy and Matplotlib
- Section 7 IPython and Jupyter Basics
- Section 8 Getting Started with NumPy
- Section 9 Creation of arrays and Matplotlib
- Section 10 NumPy and Random
What You’ll Learn
- Understand and explain the Scientific Ecosystem
- Work with Ndarrays in NumPy
- Mathematical and Statistical Functions
- Image Processing with NumPy and Matplotlib
- Basic and Advanced Visualizations using Matplotlib
- SciPy, NumPy, and Matplotlib Recipes
- K-Means Clustering
Skills covered in this course
Reviews
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KKirk Hargreaves
The information presented is fine. However reading what you are typing is distracting and doesn't help comprehension. Perhaps a quick explanation of what is there would be better.
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EEmily Rodgman
There is a lot of content where it is not really relevant to using numpy, scipy, or matplotlib. It is also quite long winded. This means I am having to listen to it at 1.5 speed. For example, lesson 33 on Ndarray, Indexing and Slicing has 5 mins of irrelevant unix admin. It might be useful for someone who isn't used to unix or raspberry pi, but not a python programmer who wants to learn numpy and scipy quickly.
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TThomas Ott
very good start to this course
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WWoody12453
solid , good pace and good info
