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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 3 million developers at
Join 3 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

46 Lessons7 Quizzes

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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Fahim Ul HaqThe Practical Guide toPython for Scientists andEngineersFounder & CEO
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/

Learn more about Shantnu

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