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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.
46 Lessons
2 Projects
7h 30min
Join 2.9 million developers at
Join 2.9 million developers at
LEARNING OBJECTIVES
- 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.
Learning Roadmap
1.
Introduction
Introduction
Get familiar with Python's versatility, key libraries, IPython's functionality, and hands-on exercises.
2.
Create a Word Counter in Python
Create a Word Counter in Python
Get started with building a Python word counter through file handling and function utilization.
3.
An Introduction to NumPy and Matplotlib
An Introduction to NumPy and Matplotlib
4 Lessons
4 Lessons
Work your way through NumPy arrays and Matplotlib for efficient data visualization in Python.
4.
Python pandas
Python pandas
9 Lessons
9 Lessons
Grasp the fundamentals of utilizing pandas for data analysis, including visualization, dataset management, and demographic-based insights.
5.
Audio Processing
Audio Processing
5 Lessons
5 Lessons
Solve problems in creating, analyzing, plotting, and cleaning sine waves with Python and FFT.
6.
Image and Video Processing
Image and Video Processing
9 Lessons
9 Lessons
Tackle image and video processing fundamentals, including image display, blurring, edge detection, and facial recognition.
7.
MultiThreading vs. Multiprocessing in Python
MultiThreading vs. Multiprocessing in Python
2 Lessons
2 Lessons
Master the steps to distinguish between Python's multithreading and multiprocessing, optimizing performance.
8.
Machine Learning with an Amazon-like Recommendation Engine
Machine Learning with an Amazon-like Recommendation Engine
4 Lessons
4 Lessons
Step through creating a recommendation engine from user behavior and correlations.
9.
Conclusion
Conclusion
2 Lessons
2 Lessons
Discover the logic behind applying Python for engineering, problem-solving, and future learning paths.
Certificate of Completion
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Developed by MAANG Engineers
ABOUT THIS COURSE
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.
ABOUT THE AUTHOR
Shantnu Tiwari
I have been programming professionally for 17+ years. Starting in embedded development, I moved to Automation using Python. I have written 5 books in Python and created many courses on it as well. My site: https://new.pythonforengineers.com/
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