Interested in applying machine learning and data science in the water and wastewater sector?

 We had such a terrific response to our first ever "Introduction to Machine Learning and Data Science in Water" course, that we've decided to open it up for registration for the second time. If you're in the water sector, are curious about machine learning and data science and not sure how to get started using it in your work - join our course and we'll give you the tools!

This is the second time we're doing a 10-week, cohort-based course and we plan on doing more of them in the future. So, what does our asynchronous, cohort-based course do for you?

One of the challenges with completing courses online is that it's so easy to sign up for one, get busy with life and work, fall behind and then give up on finishing the course that you signed up for. Our cohort-based and asynchronous approach helps you overcome that. The course material is online - so you get to complete it and review it when you get the time. However, we also have weekly office hours that are live - so you get to ask your questions to our experts, have them walk you through the key concepts and get you caught up with the course material if you fell behind that week. What's more, you get the accountability that comes with being part of a cohort of students - you get to work on your project with your peers and we keep you on track with meeting your goals. And once you're done, you'll be part of our online community space - where you can ask questions at any time, have discussions about data science in water and other clean technology sectors and meet other professionals in the space.

We'll close registration in a week and get started with the course - so if you're interested, sign up and work with us for the next 3 months. 

What our community are reading

Moonshots, Models, IoT and Machine Learning in Agriculture

  What do Google, Climate Corporation, early stage startups in farm robotics, and researchers trying to figure out how to feed the world sustainably have in common? They’re all grappling with one of the toughest challenges of working with natural systems - how do you work with data that is sparse, unevenly distributed and with systems that have so many connections and interactions with other systems?     Before the advent of cheap sensors that are connected to phones, easily accessible satellite data and drones that can fly over fields quickly and inexpensively -     scientists in companies and academia worked on developing plant and crop models that incorporated as many aspects of the farm and as much data as was available so that they could understand and predict what was likely to happen on the field. Understandably, the forecasts took some time to produce and as the models grew more complex, issues about how to estimate model parameters and the uncertainty a...
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Our online community space is now live!

 Our online community space is now open to anyone who has signed up for a free or paid course on our website! In addition to everyone who signed up for our cohort-based courses, we're now expanding it to all the members of our community. If you've already signed up for any of our courses, check your email for the invitation for the space. It's where we'll get together to talk about all things data science and clean technology related, discuss the latest research, network and make connections with other professionals in the sector. It's an invitation only , no bots and no trolls allowed space - so come on over! Here's where you can check out our courses and join our community !
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What’s the impact of your smartphone? Mapping the distribution and environmental impact of mines around the world

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How many different materials go into making your smartphone? According to the American Chemical Society, at least 64 different types of chemicals constitute your smartphone . Many of these materials, particularly the heavy earth metals, are extracted from the Earth through mining operations. Mining has been a part of human society for several thousand years now - from the shallow mines of earlier centuries to the more extractive ones created in the last hundred years. The challenge of mining and other extractive industries is that they are essential to many of our needs today - coal for energy, silicon for solar panels and heavy earths for electronics being among the well known ones. At the same time, they cause significant damage to local environments through the disturbance to the land caused by establishing the mine itself, to environmental impacts on water, land and ecosystems from mining operations.   So far, it’s been difficult to map the spatial extent and environmental impa...
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