HomeCoursesThe Practical Guide to Python for Scientists and Engineers

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7h 30min

Updated 2 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.

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Overview

Content

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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.

Content

46 Lessons7 Quizzes

Introduction

3 Lessons

Get familiar with Python's versatility, key libraries, IPython's functionality, and hands-on exercises.

Why Python?

What is IPython?

Exercise: IPython

Create a Word Counter in Python

8 Lessons

Get started with building a Python word counter through file handling and function utilization.

Reading and Printing a File

Counting Words from a File

Counting Number of Lines in a File

for Loop in Python

Count the Number of Exact Lines

Functions in Python

How to Call Python Files?

Quiz: Create a Word Counter

An Introduction to NumPy and Matplotlib

4 Lessons

Work your way through NumPy arrays and Matplotlib for efficient data visualization in Python.

List Comprehensions

Plotting Sin and Cos Waves

Plotting Salary vs. Names

Quiz: NumPy and Matplotlib

Python pandas

9 Lessons

Grasp the fundamentals of utilizing pandas for data analysis, including visualization, dataset management, and demographic-based insights.

Plotting with pandas

Plotting with pandas According to Age

Plotting Age of Children Compare to Adults

Movie Lens

Reading The Data and Getting Top Rated movies

Printing Top Rated Movies by Viewer Age

Getting Ratings by Gender

Comparing Ratings by Gender and Plotting Them

Quiz: Python pandas

Audio Processing

5 Lessons

Solve problems in creating, analyzing, plotting, and cleaning sine waves with Python and FFT.

Create a Sine Wave

Calculate the Frequency of a Sine Wave

Plotting a Noisy Sine Wave

Cleaning a Noisy Sine Wave

Quiz: Audio processing

Image and Video Processing

9 Lessons

Tackle image and video processing fundamentals, including image display, blurring, edge detection, and facial recognition.

Displaying an Image

Blurring and Grayscaling and Image

Edge Detection

Counting Objects

Face Detection

Working with Scale Factor

Face Detection in Video

Motion Detection

Quiz: Image and Video Processing

Image Segmentation Using scikit-image

Project

MultiThreading vs. Multiprocessing in Python

2 Lessons

Master the steps to distinguish between Python's multithreading and multiprocessing, optimizing performance.

Threads vs. Processes on Linux

Quiz: MultiThreading vs. Multiprocessing

Machine Learning with an Amazon-like Recommendation Engine

4 Lessons

Step through creating a recommendation engine from user behavior and correlations.

What is a Recommendation Engine?

Finding Correlation Between the Movie Ratings

Building the Recommendation Engine

Quiz: Build Amazon Recommendation Engine

Collaborative Filtering Recommendation System

Project

Conclusion

2 Lessons

Discover the logic behind applying Python for engineering, problem-solving, and future learning paths.

Wrap it up!

Where to Go from Here

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Shantnu Tiwari

Developed by MAANG Engineers

Every Educative lesson is designed by our in-house team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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Personalized Interview Prep

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Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

AI Prompt

Build prompt engineering skills. Practice implementing AI-informed solutions.

Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

Explain with AI

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AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

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