#Education

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What is a digital vortex? Let’s talk transformation and how we got to #EducationNow from Education then.

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Cisco Engineer Alphonsine Imaniraguha Anderson shares how education played a key role in transforming her life. Now she is giving back through her own nonprofit.

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A rapid transformation is now required for the healthcare and education industries. Their recovery will serve as the engine for our communities and countries to emerge from this pandemic stronger and more inclusive than ever. Cisco will continue to prioritize investments, partnerships, and innovations to accelerate our support in these spaces.

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Teaching Global Problem Solvers: The Series (GPS: The Series) is an easy, fun way to keep students engaged in STEM. To help you get started, seasoned computer science teacher Visa Thiagarajan shares a few tips for teaching GPS: The Series online.

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Join us for Teacher Appreciation Week: a week of gratitude and inspiration as we bring teachers to the forefront.

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In our last blog we announced the Connect Your Classroom Contest and the opening of pre-registration. Sponsored by Cisco and our friends at the Center of Interactive Learning and Collaboration (CILC), the contest invites K-12 teachers in the U.S. to tell us how they’re using technology to enable collaboration in their classrooms. Since that announcement, […]

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ST Math, MIND Research Institute's flagship visual instructional program, is available at no cost to parents. Since it’s visually-based, students who speak all languages can benefit. We sat down with their CEO, Brett Woudenberg, to learn more.

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Part 3: Cisco Use Case and Designing Your Own Time Series Problem This is a continuation of the Time Series Analysis Posts. Here, I will detail a Cisco use case utilizing time series analysis and ARIMA from part 1 and part 2 of the blog series. If you have not read those yet, feel free […]

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This is a continuation of the Time Series Analysis posts. ARIMA stands for Autoregressive Integrated Moving Average. These models aim to describe the correlations in the data with each other. You can use these correlations to predict future values based on past observations and forecast errors.