November 10, 2020 — Jamie Peterson, Senior Training & Online Learning Manager, Wolfram U
Students are spending countless hours online for classes this year, pushing educators to offer more engaging and worthwhile virtual content. We debuted Wolfram Daily Study Groups in early April with this in mind, and the results have far surpassed our expectations! Throughout this ongoing program, we’ve been able to keep students, professionals and lifelong learners engaged and connected in an enriching online community. With several Study Groups completed, and more in the works, we thought we’d share some of our successes so far.
September 24, 2020 — Jamie Peterson, Senior Training & Online Learning Manager, Wolfram U
Our second year of the Wolfram Data Science Boot Camp (and the first fully virtual edition) wrapped at the end of July. After completing final project assessments last week and issuing certificates, we can confidently say it was a success! Wolfram U mentors helped dozens of budding data scientists learn the multiparadigm approach and develop valuable skills in analysis, visualization, interface construction and more. Campers collaborated on projects of their own design, earning certifications along the way.
We’re proud of everyone who participated, and their efforts deserve some recognition! So without further ado, here’s a quick recap: how we ran the camp, what kinds of projects we saw and the lowdown on our new Level II Certification program.
September 17, 2020 — Hamza Alsamraee, Document & Media Systems
A few months before I accepted a Wolfram Research internship—around March—I was very fearful, and so was the majority of the world. We knew very little about the novel coronavirus, and the data was just not robust. In addition to the limited data we had, the scientific process necessarily takes time, so even that was not used to its full extent. In a world where not enough data can quickly become data overload, the question didn’t seem to be finding more data, but rather how can one extract useful and meaningful information from the available data?
A worldwide pandemic is definitely stressful, but a worldwide pandemic without accessible and computable information is much more so. Using Wolfram technologies in coordination with several internal teams, I created a Wolfram U course called COVID-19 Data Analysis and Visualization to try and cut through the informational fog and find some clarity. I saw this course as one that gives power to everyone to be able to look at data and gain insight. After all, data is knowledge, and knowledge is power.
September 2, 2020 — Arben Kalziqi, Education Evangelist, Education Partnerships
Schooling looks a little different in 2020. Whether it’s technical issues with the transition to online courses, decreased physical attendance or delayed and last-minute openings, we’re all feeling the pressure caused by the COVID-19 pandemic.
At Wolfram Research, we’ve been involved in education for decades and count millions of parents, teachers and students as both our customers and our friends. Because of this longstanding commitment to learning, we have content, experts and platforms at the ready to help parents and students who are looking for ways to augment their learning.
August 14, 2020 — Devendra Kapadia, Manager of Calculus & Algebra, Algorithms R&D
Linear algebra is probably the easiest and the most useful branch of modern mathematics. Indeed, topics such as matrices and linear equations are often taught in middle or high school. On the other hand, concepts and techniques from linear algebra underlie cutting-edge disciplines such as data science and quantum computation. And in the field of numerical analysis, everything is linear algebra!
Today, I am proud to announce a free interactive course, Introduction to Linear Algebra, that will help students all over the world to master this wonderful subject. The course uses the powerful functions for matrix operations in the Wolfram Language and addresses questions such as “How long would it take to solve a system of 500 linear equations?” or “How does data compression work?”
July 14, 2020 — Alec Titterton, CBM Content Development Manager, European Sales
As Conrad Wolfram writes in his new book, education in computational thinking and quantitative problem solving are largely absent from today’s mathematics curricula. With the current crisis changing education practice in many ways, what better time to try out a sample of our new curriculum? It’s a curriculum fit for learners who want to be better prepared for an AI age where computers can be used to their full potential.
It’s a beta release, a first sample manifestation of what can be deployed in a self-study mode to implement The Math(s) Fix. We’re stretching what can be done in a browser to the limit, so please be patient with refresh times. The content and intended learning outcomes are the key points to look out for; you can see how we’ve merged the learning of general “thinking” outcomes and computation outcomes with real contexts in accessible problems.
April 3, 2020 — Danielle Rommel, Director of Outreach and Communications
Remote work. Distance learning. Virtual events. These terms are becoming more commonplace as quarantines and stay-at-home orders continue and folks practice social distancing. While brainstorming how best to contribute to our customers around the world during these unusual times, we’ve generated a ton of data resources, analytics, free access to technology and much more.
However, these resources were still missing a deeper level of collaboration and interaction—the simple power of people coming together to connect, work and learn. With that in mind, here are some more group-oriented offerings to help keep you connected and in touch with one another, even in the new landscape of an almost entirely virtual world.
Today, the world around us is being captured by imaging devices ranging from cell phones and action cameras to microscopes and telescopes. With ever-increasing generation of images, image processing and automatic image analysis are used in a wide range of individual, academic and industry applications.
We are excited to announce Introduction to Image Processing, a free interactive course from Wolfram U, which makes cutting-edge image processing simple with graphical and visual examples that demonstrate how image operations work. It includes 14 video lessons, each lasting 20 minutes or fewer, and 5 short quizzes, as well as a certificate for finishing all course materials. Topics range from how to control brightness and contrast or crop and resize images, to advanced topics including segmentation, image enhancement, feature detection and using machine learning to perform modern image processing—no machine learning knowledge necessary!
January 16, 2020 — Jamie Peterson, Senior Training & Online Learning Manager, Wolfram U
Looking to fulfill your New Year’s resolution of learning new data science skills? Join Wolfram U for Wolfram Technology in Action: Data Science, a three-part web series demonstrating a range of data science applications in the Wolfram Language. These 90-minute sessions feature recorded talks from the 2019 Wolfram Technology Conference, along with live presentations by Wolfram staff scientists, application developers, software engineers and Wolfram Language users who apply the technology every day to their business operations and research.
Newcomers to Wolfram technology are welcome, as are longtime users wanting to see the latest functionality in the language.
September 17, 2019 — Brian Wood, Technical Communications & Outreach Manager
Our interactive Multiparadigm Data Science (MPDS) course has been up at Wolfram U for over a month now, and we’re pretty satisfied with the results so far. Hundreds of people have started the course—including students from our first Data Science Boot Camp, who joined us at Wolfram headquarters for a three-week training camp. Thanks to the success of the boot camp, we have also had several projects submitted for advanced MPDS certification, which will soon be available within the interactive course.
But what exactly does it mean to be a practitioner of MPDS? And how might the multiparadigm approach improve my computational projects? To find out, I decided to try this free course for myself.