Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Subscribe
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
Python for Scientific Research
Rating: 4.4 out of 5(314 ratings)
44,982 students

Python for Scientific Research

Master Python for Scientific Research with Practical Examples
Created bySenior Assist Prof Azad Rasul
Last updated 12/2025
English

What you'll learn

  • Master Data Handling: Learn to creatively manipulate, import, and export data using Python.
  • Perform Statistical Analysis: Gain proficiency in descriptive statistics, correlations, ANOVA, and t-tests for research.
  • Create Professional Graphs: Develop skills in creating basic, advanced, and animated graphs with Python.
  • Apply Python in Research: Use Python to process data, perform analyses, and visualize results in scientific research.
  • Enhance Research Creativity: Unlock unlimited possibilities by applying Python creatively to your research challenges.

Course content

8 sections • 38 lectures • 4h 23m total length

  • Welcome and Course Overview4:10
  • Installing Miniconda and Python 3 on Windows1:51

    There are various ways to install and run Python along with its tools and libraries. In this learning series, we will be using "Miniconda" to install and run Python. Miniconda is a smaller version of Anaconda that comes with Python, conda, and a few pre-installed packages, including pip.

    To get started, visit the Miniconda website: https://docs.conda.io/en/latest/miniconda.html and download the appropriate version for your computer. For example, I will be downloading "Miniconda 3 Windows 64-bit" for my computer.

  • Setting Up Python Environments and Installing Packages3:53
  • Installing and Running Jupyter Notebook.3:17
  • Setting Up Your Environment

Requirements

  • No prior programming experience is required

Description

Are you looking for a powerful and versatile tool to enhance your research capabilities? This course is your gateway to mastering Python for scientific research, where you'll learn through real-world examples across various fields.

As an Assistant Professor of Remote Sensing and a Senior GBD Collaborator with over a decade of experience in Python, R programming, and Big Data, I am excited to guide you on this journey. With a Ph.D. in Geography (Remote Sensing) and over 60 peer-reviewed publications, I bring extensive expertise in data analysis, remote sensing, and climate studies to help you excel.

In this course, you'll gain hands-on experience in:

  • Data Manipulation: Learn to import, export, and manipulate data efficiently using Python.

  • Statistical Analysis: Master techniques like descriptive statistics, multi-correlation, ANOVA, and t-tests.

  • Graph Creation: Create basic, advanced, and animated graphs to visualize your research findings.

This course is designed to not only make you proficient in Python but also empower you to use your creativity in data processing and analysis. Unlike restrictive software like SPSS or Excel, Python offers unlimited possibilities, allowing you to tailor your research tools to your specific needs.

Each lecture is crafted to provide you with actionable insights that you can apply immediately in your research. By the end of the course, you’ll be able to confidently use Jupyter Notebook for scientific research and develop custom Python scripts to tackle complex research challenges.

Take the first step towards elevating your research with Python. Enroll today, and let's unlock the full potential of your research capabilities together.

Sincerely,

Assist. Prof. Azad Rasul

Who this course is for:

  • Researchers and students who are attempting to efficiently use Python programming for their scientific research.

Report abuse