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Data Science for Climate Change

Learn how to use data science and big data to make crucial decisions that can help fight climate change with this online course from Luleå University of Technology.

Duration

4 weeks

Weekly study

5 hours

100% online

How it works

Unlimited subscription

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Gain a solid introduction to data science

On this four-week course, you’ll get started with data science to learn what it is, how it is used, and the societal influence it can have on big issues such as climate change.

You’ll gain a comprehensive understanding of data science including big data, data architecture, and the types of analytics you can use to make data-driven decisions.

Understand how to use visualisation

First, you’ll unpack the process of visualisation to understand how you can accurately represent the information and data you collect. With this knowledge, you’ll learn how visual aids help share your results.

Next, you’ll delve into CRISP-DM to ensure you have a structured approach to your data mining processes.

Learn how to make data-driven decisions

With an understanding of data science, you’ll hone your decision-making skills and gain confidence in making data-driven decisions.

You’ll be guided through the decision process to understand how to navigate the human and machine collaboration to make informed decisions and develop your decision-making style.

Explore climate change adaptation strategies

Finally, you’ll unpack how data science can be used to address the pressing issue of climate change.

You’ll be introduced to what climate change is, adaptation, and mitigation before exploring the many challenges that come with climate change.

Through this exploration, you’ll learn how to use data to find solutions to climate change issues and mitigate impacts.

You’ll see data science and climate change in practice to gain a solid understanding of how this can be used in real-life contexts and the career opportunities it presents.

Week 1
Getting Started with Data Science
- Course Overview
  A course overview where the learner will get to know both the subject itself, the course creators and other learners in the community.
- Data Science Overview
  This activity presents a brief introduction to Data Science.
- The Data Flood
  This activity presents and discusses the "Data Flood" that is out there in the world and how it can be understood.
- Analytics
  Analytics is a very important element of data science, therefore in this activity, we will explore analytics and introduce algorithms.
Week 2
Visualization and Analytics as a Process
- Visualization
  Presenting the analytics' outputs is a critical task, therefore we will explain it in this activity.
- CRISP-DM
  The cross industry process for data mining is how we conduct data science projects, and accordingly, we will explain it in this activity.
- Other Processes
  In this activity, we will explore other data science processes rather than the generic one.
Week 3
Data-driven Decisions
- Decision-making
  In this activity, decision-making will be discussed and explained.
- Decision-making Process
  In this activity, the phases and activities carried out towards making a decision are outlined.
- Data-driven Decisions
  Making data-driven decisions is the contemporary wat of making decisions. This activity explains what this means.
- Human-machine Collaboration
  In this activity we discuss the collaboration between human decision makers and algorithms, as well as the challenges that unfolds.
- Decision-making Styles
  In this activity, we explain and reflect on the different decision-making styles.
Week 4
Climate Change and Use Cases
- Introduction to Climate Change
  This activity introduces climate change and relates it to the UN Sustainable Development Goals (SDGs)
- Climate Change Challenges
  This activity discusses the climate change challenges and their impact.
- Data Science and Climate Change
  In this activity, we are merging data science with climate change in order to address climate change issues.
- Use Cases
  This activity provides use case examples on how data science was och could be used to address or solve climate change challenges or problems.
- Course Wrap Up
  In this activity, the course is concluded and you are given some tips for the future.