Beginner
7h 30min
Updated 3 months ago
The Practical Guide to Python for Scientists and Engineers
Gain insights into using Python for scientific and engineering applications. Delve into real-world scenarios, learn NumPy, Matplotlib, audio processing, and more through practical, hands-on projects.
In this course, you will learn to use Python for real-world scientific/engineering applications. For each topic, there will be a real case scenario where you will build a quick solution in Python to solve the problem.
More specifically, you will cover topics such as creating a word counter, NumPy and Matplotlib, audio processing, and a lot more. Throughout each chapter, you will get hands-on experience in building solutions for complex problems that engineers and scientists face every day.
In this course, you will learn to use Python for real-world scientific/engineering applications. For each topic, there will be a...Show More
WHAT YOU'LL LEARN
The learners will use Python for real-world scientific/engineering applications.
The learners will learn how to use python libraries.
The learners will learn Multithreading in python.
The learners will learn Machine learning in python.
The learners will learn how to work around with Images and Videos in python.
The learners will use Python for real-world scientific/engineering applications.
Show more
Content
1.
Introduction
3 Lessons
Get familiar with Python's versatility, key libraries, IPython's functionality, and hands-on exercises.
2.
Create a Word Counter in Python
8 Lessons
Get started with building a Python word counter through file handling and function utilization.
3.
An Introduction to NumPy and Matplotlib
4 Lessons
Work your way through NumPy arrays and Matplotlib for efficient data visualization in Python.
4.
Python pandas
9 Lessons
Grasp the fundamentals of utilizing pandas for data analysis, including visualization, dataset management, and demographic-based insights.
5.
Audio Processing
5 Lessons
Solve problems in creating, analyzing, plotting, and cleaning sine waves with Python and FFT.
6.
Image and Video Processing
9 Lessons
Tackle image and video processing fundamentals, including image display, blurring, edge detection, and facial recognition.
7.
MultiThreading vs. Multiprocessing in Python
2 Lessons
Master the steps to distinguish between Python's multithreading and multiprocessing, optimizing performance.
8.
Machine Learning with an Amazon-like Recommendation Engine
4 Lessons
Step through creating a recommendation engine from user behavior and correlations.
9.
Conclusion
2 Lessons
Discover the logic behind applying Python for engineering, problem-solving, and future learning paths.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Course Author:
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