The coronavirus pandemic has up ended the business world, education, and the workplace and landed us in a protracted moment of uncertainty and disruption. Companies are scrambling to manage distributed teams and coordinate work remotely, while retaining customers and finding new sources of revenue. Some must fully reinvent themselves to survive, as their traditional markets have shrunk or disappeared entirely.

Our abrupt and ongoing shift to remote work is having wide-ranging effects on design, engineering, and manufacturing industries, putting great pressure on organizations to be more agile, efficient, and flexible in a COVID-19 world.

There are more online learning resources to choose from than ever before. If you’re looking to learn emerging technologies or prepare your workforce for digital transformation an informational webinar can help you explore the content, structure, and learning outcomes of a prospective online course. Explore online courses and programs in topics like additive manufacturing, leadership, machine learning, negotiation, systems engineering, and quantum computing. Register to view any of the MIT-faculty led on-demand webinars below.

Erica LeBlanc is the Global Sales Enablement Manager for Logi Analytics, a software company that offers integrated development environments for programmers to embed dashboards, visualizations, and analytics into software applications. Although LeBlanc has over a decade of sales enablement experience, and plenty of on-the ground negotiations practice, she was looking for a quick yet comprehensive way to brush up on the latest negotiation techniques from renowned experts in the field.

In the mid-1960s, Ford Motor Company had an audacious plan: not only to enter the professional car racing circuit, but to defeat Italy’s Ferrari racing powerhouse. To achieve that goal at 24 Hours at LeMans, the most prestigious European endurance race, Ford hired two American racing legends, Carroll Shelby and Ken Miles. This story is captured in the current Oscar-nominated movie, Ford vs. Ferrari.

Former NFL Linebacker Ryan Nece is no stranger to negotiation. Whether it's with his 3-year old son ("He beats me every time," says Nece) or negotiating on behalf of his venture capital firm, Next Play Capital. Despite all of this day-to-day negotiation practice, Nece felt that he was missing formal training. So, he decided to participate in MIT xPRO's online negotiations course, Negotiating to Create Value: The Mutual Gains Approach. We sat down with Mr. Nece to discuss his online learning experience, and how athletes and executives alike can benefit from the Mutual Gains Approach (MGA).

The quantum computing revolution could empower companies and entire industries to solve previously intractable problems. As investment in quantum technology grows and tech giants vie for quantum advantage, demand for professionals with foundational quantum computing knowledge and hands-on quantum experience has never been higher.

Things are changing at Ford. The rise of “the smart car” has spurred customer demand for automation, electric vehicles, and other intelligent automotive features. To keep up with the rapid pace of change in the industry, the 116-year-old auto giant has had to make significant shifts in its portfolio of vehicles – eschewing the sedan in North America, while launching new SUVs and crossovers. New variants and features have required a more rigorous systematic approach across all engineering functions. To improve efficiency, lower variable costs, and reduce error as it launched a new portfolio of products, Ford improved its Systems Engineering (SE) approach in three key ways:

From getting beyond the quantum hype to online learning tips, here are The Curve's most popular posts from 2019:

This October, Google announced in an article published in the journal Nature that its quantum computer, which runs on a 53-qubit chip called “Sycamore,” took only 3 minutes and 20 seconds to calculate a problem that would take the world’s fastest conventional computer 10,000 years to solve. IBM disputed Google’s quantum supremacy claim, arguing that an ideal simulation of the same task can be performed on a classical system in 2.5 days and with far greater fidelity. And the debate continues.