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Big Data and the Environment

Vicky Lucas, Jon Blower, Richard Lamb, Thomas Eldridge, Rebecca Emerton, Sally Stevens, and Tom August

Week 1: Introduction to big data Week 2: Data to Discovery Week 3: Big and Small Data Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more This course is aimed at professionals seeking a better understanding of environmental big data and the potential these offer to address key questions and underpin novel solutions for business. It is also relevant to anyone studying environmental topics with a general interest in big data analytics and the complexities and issues surrounding the collection, curation and application of these vast data sets. You can use the hashtag #FLenv_bigdata to talk about this course on social media.

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Reviews summary

Foundational big data for environmental insights

According to learners, this course offers a highly effective foundational overview of the intersection between Big Data and the Environment. Students frequently highlight the incredibly clear lectures, which make complex concepts accessible, and the valuable inclusion of real-world environmental case studies demonstrating practical applications. While it serves as an excellent starting point for environmental professionals or those new to the field, some learners with prior data experience or a desire for hands-on technical skills found the course to be too theoretical and lacking in deeper dives into specific tools or programming. It is generally regarded as a strong conceptual course that broadens understanding rather than teaching deep technical proficiency.

Features practical, real-world environmental applications.

"The case studies were particularly insightful, showing real-world applications of data in addressing environmental challenges."

"The environmental examples were relevant and helped illustrate the points effectively."

"The discussions around data ethics and the challenges of data collection were especially thought-provoking."

Lectures explain complex topics clearly and simply.

"The lectures were incredibly clear, and I appreciated how they broke down complex concepts into digestible pieces."

"It's well-structured and easy to follow, making big data concepts accessible."

"The quality of instruction was high, and the content was engaging."

Excellent introductory course on environmental big data.

"This course was an exceptional introduction to the intersection of big data and environmental science."

"A good foundational overview. It provided a solid conceptual understanding of big data's role in environmental analysis."

"Fantastic overview of how big data intersects with environmental challenges. It's a perfect starting point..."

May be too basic for those with prior data science experience.

"Disappointed with the lack of depth. It felt like a very surface-level discussion. For a 'big data' course, I expected at least some exposure to tools like Python or R..."

"For me, it was mostly a review of basic concepts with environmental examples. I was hoping for more advanced applications..."

"I would have liked a bit more detail on specific tools or programming aspects, but for a general introduction, it's very effective."

Emphasizes theory and concepts over hands-on application.

"While the topics were interesting, I found the course to be quite theoretical. I was hoping for more practical exercises..."

"It was mostly slides and talking. Not for those seeking technical skills."

"It is more conceptual, setting the stage, which is fine for an introductory course."

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Reading list

We've selected 49 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Big Data and the Environment.

Python for Data Analysis

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The third edition of the essential guide to data wrangling with pandas, NumPy, and Jupyter in Python. Updated for newer versions of the libraries, this book remains a core resource for anyone performing data analysis in Python. It widely used textbook and reference for its clear explanations and practical examples.

Big Data and the Environment

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Reviews summary

Foundational big data for environmental insights

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