Here's wishing all our readers a very happy new year! Last year, we started our journey to making data science accessible for people interested in clean technology and solving the problems facing our planet.
We had the pleasure of conducting several workshops and online webinars on different aspects of data science in clean technology. We covered a wide range of topics in our in-person workshops where we discussed data sources in different clean tech sectors, how to build effective algorithms and models including deep learning, and presented uncertainty analyses and business use cases. We also began conducting online sessions in the latter half of the year where we introduced folks to careers and tools at the intersection of data science and clean tech.
As part of our expansion plans in 2020, we're creating an online education platform that focuses on applying data science effectively in clean tech sectors. We're in beta this month and are building our content which will consist of live workshops, online courses and reports . Right now, we're offering a bundle of our existing courses and reports for freeto all our beta users (a $30 value). We'll be adding more content every month, including access to new webinars and live workshops, so stay tuned.
Our platform is hosted by Teachable, which we chose primarily for their commitment to user privacy and the glowing reviews from other students on how easy it was to use. We'd love to hear what you think about it, so please let us know!
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 associated with the resul
As the impacts of climate change on the planet become clearer, scientists and professionals in climate science are looking at the latest tools and technologies in AI and machine learning to help understand and mitigate the effects. At the same time, career opportunities in the field are growing and we’re seeing increasing numbers of students and early career professionals interested in developing and using their skills in ways that can help the planet. So, when and where can machine learning and AI be used in climate science? And what are the pitfalls? If you’re working in environmental and earth sciences, you probably already have a pretty big toolbox that has been developed over several decades! It consists of standard statistical techniques including spatial and temporal statistics, a range of physics-based or process based models, and several data collection and data integration technologies at different scales. What can machine learning add to this? Does it replace all the o
Last time we looked at how machine learning can help water utilities manage their maintenance and operations efforts - especially when dealing with hard-to-reach parts of the water system like buried water pipes. Today, let’s talk about how machine learning is being used in developing new technologies and building prototypes for decentralized, small-scale systems. Desalination has been studied and deployed at scale for several years now. As different parts of the planet face increasing water stress, desalination is being evaluated as one of several potential solutions - together with water conservation and recycled water. In the Middle East of course, large-scale desalination plants have been in operation for several decades, with Israel being one of the countries at the forefront of developing and implementing the technology. Large-scale desalination plants have the advantage of scale - you can build a single system and then connect it to your existing water network. Sufficient data a