Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
4 Hour(s) 24 Minute(s)
Language
English
Taught by
Senior Assist Prof Azad Rasul
Rating
Course Overview
Master Python for Scientific Research with Practical Examples
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
Course Content
- 8 section(s)
- 38 lecture(s)
- Section 1 Introduction and Setup
- Section 2 Python Programming Fundamentals
- Section 3 File Handling and Directories
- Section 4 Scientific Computing and Statistics
- Section 5 Data Visualization
- Section 6 Geospatial Analysis and AI
- Section 7 Case Studies and Applications
- Section 8 Conclusion
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.
Skills covered in this course
Reviews
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NNuzhat Tabassum
I am very much afraid of coding all the time. But it is well organized from the installation to the advanced level. It is a great help for me.
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CChandan Kashyap S
The course was indeed covered with lot of things but the pace at which it was being taught was not understandable it could have been more learner friendly but it was not
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JJesus Edmundo Diaz Trejo
Es una excelente selección de temas.
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MM H
この講座は、科学研究に役立つPythonのスキルを身につけるために非常に有益です。 実践的なアプローチ: 講義では、実際の研究シナリオに基づいたケーススタディが取り上げられており、学んだスキルを実践的に適用する機会が与えられます。 豊富なリソース: 受講中には、さまざまなデータやリソースにアクセスできるため、自分のペースで進めることができます。特に、CSVファイルやデータセットが用意されているのは助かります。 コミュニティとの連携: このコースを通じて、他の受講者や講師との交流が促進されており、質問やサポートを受けるためのQ&Aセクションがあります。これにより、わからないことをすぐに解決できます。 継続的な学習の重要性: 講師からのアドバイスとして、定期的に練習し、ビデオを見続けることが強調されており、成長のための良い指針となります。 ボトムアップの学習: 基礎から始まり、徐々に専門的なトピックに進むカリキュラムは、自分の理解を深めるのに役立ちます。 この講座は、データ分析やモデリング、可視化など、幅広い科学研究タスクを扱うための強固な基盤を提供しており、受講者の皆さんにとって非常に価値のあるリソースです。
