E is for Eskwelabs Issue 050 - Food for Thought 🍳 Harvesting the Benefits of Data Skills 🌱
In our fiftieth issue, we focus on local and international issues and talk about how using data for good can be a game-changer in facing these issues head on.
We created this newsletter to keep our alums, partners, and anyone interested in learning skills for the future of work updated and connected to our ever-growing family. If you want to read our previous issues, you can check them out here.
Hi everyone, Francine here! 👋 After two years of writing E is for Eskwelabs, we made it to our 50th issue! Thank you to our early readers and to the new ones we’ve welcomed along the way. 🎉 We’re hoping to delight you with an updated newsletter format for Issue 51, but for Issue 50, we’ll stick to our original format as an ode to all the newsletters we’ve sent previously. We’re presenting Issue 50 as a “food for thought” type of issue as we literally highlight data science in action in the agriculture sector in the Philippines. Food is such a personal and universal topic and it cannot be separated from conversations about our changing climate, too. So we’ll be dedicating a section here to Earth Day 2022 as well. Lots of things to think about in this issue, let’s go! 🌱
What’s in this newsletter:
🖥️ Seeing data science in action in this local agritech startup
🧠 Learning about the K-Means algorithm
🌎 Checking out links that intertwine data and climate change
❤️ Getting your stories from how you spent Earth Day 2022
READING TIME: 5 minutes
🖥️ Seeing data science in action in this local agritech startup
A Data Science Fellowship capstone project we keep coming back to because of how relevant and advocacy-driven it is is the recommender engine done by Data Science Fellows Charity Benignos, Christopher Louie Gemida, Renzo Luis Rodelas, Andrew Justin Oconer, and Matthew Antoine Tomas.
The capstone project these Fellows did was with Mayani, an agritech startup that exists to ensure small farm-holders earn reasonable income through an online market platform. Climate change hits all aspects of our lives and one of the most affected sectors in the Philippines is agriculture. That’s why it’s crucial to support agritech startups like Mayani.
At the end of our 12-week data science program, our students are expected to design and implement a capstone project that showcases the culmination of the knowledge and skills they’ve acquired. Here’s a preview of their methodology for the Mayani recommender engine:
This blog post contains the steps they took in more detail; the tools the Fellows used like Pandas, Python 3, Scikit Learn, and more; and the impact of their solution.
You can build your own capstone project like this when you enrol in the Data Science Fellowship. Eskwelabs is a good foundation for budding data scientists. We provide you with an internationally-recognized curriculum, connections with industry practitioners, mentors who give unbeatable support, a community of lifelong friends, and career support after the program. We’ve provided Admissions details for Cohort 9 below:
Admissions corner 📝
Cohort 9 of the Data Science Fellowship starts on May 16, 2022
Sign up today: Enrol here
For those ready to dive in
Assessment exam coverage: View here
Take the 2-part assessment (Multiple choice part and essay portion)
For those who want to learn more before signing up
Comprehensive program guide: View here
🧠 Learning about the K-Means algorithm
We'd like to present a new series called “From the Notebook of Our Fellows” because readers will be guided by our very own alumni through a mix of basic and advanced data science concepts. Every time you read from one of our Fellows’ notebooks, just imagine that you have a data BFF or lifelong learning friend who’ll hold your hand at every step. 📓
The “notebook” (or blog post) we are sharing today is Basty Vergara’s. He’s a Cohort 8 Data Science Fellowship graduate. He’s written an accessible and friendly guide to the what, why, and how of the K-Means algorithm. This machine learning algorithm is actually one of the tools used in the Mayani recommender engine capstone project we shared earlier in this issue.
Written in Basty’s energetic and spunky voice, this blog post is sure to delight you and make you realize that machine learning can be beginner-friendly. We’re excited to see your confidence shine when you share this new piece of knowledge with your family and friends.
🤔 A question for our Eskweloves: How did you commemorate Earth Day 2022 last April 22?
🌎 Checking out links that intertwine data and climate change
We’ve compiled these links to give you a deeper appreciation of just how important data is in our fight against climate change. Despite the scary topics of these articles—forest fires, flooding and typhoons, heatwaves, and food scarcity, let’s approach them with a solutions-focused and hopeful mindset instead.
🌳 An Analysis of Amazonian Forest Fires (Medium) | 21 min read
🍳 Climate Change and Food Scarcity in Developing Regions: An analysis in Python (Medium) | 6 min read
🔥 Climate Change and Health: Heatwaves (Medium) | 5 min read
🌧️ Can Human Mobility Disruptions in Cities Be Seen in Near-Real-Time? (Medium) | 7 min read
That’s it for our fiftieth issue of the newsletter! Thanks for reading! 🤗 We are excited to introduce the new format of Issue 51 next time. Woo!
Have something to share? We encourage you to give us feedback and ideas (you may do so here) and if you like it, please share it with a friend!
Have a good Monday! See you again in your inbox next, next week!
💌 Cheering you on always,
Francine
Learning Community Manager at Eskwelabs