David Kosbie in a classroom with students in Rwanda
David Kosbie, an associate professor of computer science at Carnegie Mellon University, and co-founder of CMU's Computer Science Academy, went to Rwanda in the summer of 2018 to teach students at the Agahozo-Shalom Youth Village school computer-science skills.
Credit: David Kosbie

Amazon donation boosts innovative computer science education program

$2 million commitment to Carnegie Mellon University’s Computer Science Academy extends opportunities to students in underserved middle and high schools.

By Douglas Gantenbein
December 08, 2020
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In the summer of 2018, David Kosbie visited a school for orphans and other young people in rural Rwanda. Kosbie — an associate professor of computer science at Carnegie Mellon University (CMU) — was there to watch the school work with curriculum from CMU’s Computer Science Academy he helped co-found as a way to reach students who lack access to computer science curriculum.

“The computer-science students would come in early and leave late,” he recalls. “On my last day there, they tried to convince me not to go to the airport to go home.”

What had the students buzzing was the chance to learn advanced computer-science and programming skills — opportunities they’d never had before. That was due to the Computer Science Academy’s online classes and teacher training, which is giving these students a chance to develop 21st century skills.

“It was just so heart-warming,” Kosbie adds. “I’ve sent some of my CMU students to that same school, and for each one it was a life-altering experience. The life stories of these students is mostly tragic, but yet the school (Agahozo-Shalom Youth Village) is one of the most joyous places I have ever been.”

David Kosbie
David Kosbie launched CMU's Computer Science Academy in 2018 with colleague Mark Stehlik.
Credit: CMU

Launched in 2018 by Kosbie and CMU colleague Mark Stehlik, CMU CS Academy is a rigorous online computer-science program that has reached more than 5,600 teachers and mentors and 61,000 students around the world, giving a boost to schools that have limited opportunities to offer students computer science or programming classes. The academy is free to schools that participate, and offers free online and in-person teacher training and support.

Amazon has now announced it will provide $2 million to support CMU CS Academy over the next three years. The donation comes from Amazon Future Engineer, Amazon’s childhood-to-career computer science education program aimed at educating and training students from underserved and underrepresented communities. 

The donation comes at a great time, says Kosbie. CMU CS Academy is growing at a rapid clip. “That $2 million will pretty much cover our current operations for three years,” he says. “It will help us with course production, and course hosting, and professional development for teachers. It also will begin to help us expand our efforts to produce CMU CS Academy in different languages.”

Most importantly, he says, it will allow CMU CS Academy to pursue its twin goals of helping students entering the world of computer science, while creating a bigger, more diverse and equitable pipeline of programmers and computer scientists. “Tech companies just can’t find enough talent,” says Kosbie. “And because of the way equity issues play out in schools, a high percentage of the best and brightest have little hope of getting into this pipeline. Amazon, of course, gets that, and is working to change that with Amazon Future Engineer.”

CMU CS Academy offers a rigorous introduction to computer science. “While we are designed to reach all students at all levels, we're CMU and we have to uphold high standards,” Kosbie says. “This is not just a gentle taste of programming where when you’re finished you know what programming is but can’t program. This is the real deal.”

Although challenging, classes also are designed to be fun, with a strong emphasis on creativity and graphics. In addition, many of the exercises are designed by CMU students — the logic being that, as recent high-schoolers themselves, they have a good sense of what is relevant to CMU CS Academy’s primary audience.

CMU CS Academy currently offers three core curricula: A basic course for middle schools, school camps, or out-of-school programs; a robust introduction to learning programming through graphics and animations for middle and high schools; and a prep course for students preparing to take advanced placement tests or to take computer science courses in college. It also offers teacher training, 24/7 support, and teacher resources.

Because classes often are taught in schools that lack great technical resources — 60 percent of participating US public schools are Title I schools that receive federal funds — they’re designed to run on rudimentary computer equipment and weaker internet connections.

Looking forward, Kosbie says that in addition to underwriting CMU CS Academy operations, Amazon’s donation will help it focus on developing methods for measuring the actual impact of its classes — whether they boost achievement, what career paths graduates take, how college acceptance rates change. “We want to be able to go to prospective donors and scientifically show them that what we’re doing works,” he says. “So far we’re hearing very promising qualitative results, but we want to back that up with sound quantitative results.”

Ultimately, Kosbie sees CMU CS Academy as a vehicle for giving young people a hand they might not otherwise receive. “We’re doing this because we know this is the right thing to do,” he says. “We have been unbelievably blessed by being skilled and experienced in a discipline that is very rewarding personally but also financially. We feel an obligation to share these opportunities with students who might not otherwise have them.

"We look forward to seeing the impact students with varying backgrounds will have on our world after building these fundamental computer science skills.”

More information about the donation is available in this Carnegie Mellon University School of Computer Science press release. To learn about the different ways you can engage with Amazon's scientific community, visit our Academic Engagements page.

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About the Author
Douglas Gantenbein
Douglas Gantenbein is a contributor to Amazon Science.
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Applied Scientist II
IN, KA, Bengaluru
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses.If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.Major responsibilities· · Use machine learning and analytical techniques to create scalable solutions for business problems· · Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes· · Design, development, evaluate and deploy innovative and highly scalable models for predictive learning· · Research and implement novel machine learning and statistical approaches· · Work closely with software engineering teams to drive real-time model implementations and new feature creations· · Work closely with business owners and operations staff to optimize various business operations· · Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation· · Mentor other scientists and engineers in the use of ML techniques
Applied Scientist, Prime Video
US, WA, Seattle
Amazon Prime Video is changing the way people watch movies, TV shows, Channels and Live Events, offering the greatest choice in what to watch on-demand or in real-time on large gamut of devices (mobile phone, PCs, Macs, gaming consoles and Fire TV etc.). We are at the forefront of the entertainment industry and growing fast - now available in more than 240 countries and territories worldwide. We work in a dynamic, and exciting environment where innovating on behalf of our customers is at the heart of everything we do.We are part of the Digital Media Engineering team in Prime Video. We are making big investments in this area and taking great strides forwards to advance the state of the art and impact streaming video industry and our customers. Our journey of leveraging Computer Vision (CV) started in 2017 to address streamer facing content defects of Content Mismatch, Frozen Frames, and Subtitle out of sync. We power multiple use-cases with our cue point automation, content matching, artwork generation, metadata generation and intro & end-credit timecodes. To move faster, we have built the Deep Video Understanding (DVU) platform to unburden app developers from hosting foundational ML/CV models that identify frames/shots/scenes/segments in video.We are building a new team for Applied Science and are looking for specialized talent to join us in our mission to build deep expertise in scene & semantic understanding, video segmentation, automatic content generation, activity detection and cross-modal learning from visual, textual and audio that has broad applicability for Prime Video. We will build sophisticated ML/CV based services that eliminate heavy lifting for digital content producers to deliver high quality inputs.As an Applied Scientist you will be the founding member of this team and will push the state of art in the computer vision and apply the same for video centric digital media. You will be responsible for new experimental solutions that combine the latest findings in cutting-edge computer vision and machine learning to build compelling demos and illustrative results. You will work closely with engineering teams to productionize proven experiments, models and solutions. You will work with a team of engineers and scientists who are passionate about using machine learning to analyze terabytes of data, build automated systems and solve problems that matter to our customers.It has never been a more exciting time for AI and Computer Vision.We are in a green-field space of computer vision which is overdue for disruption. To know more about this once-in-a-lifetime opportunity to shape the future of streaming video - please mail/chime me at – vimalb AT amazon DOT com
Economist
US, CA, San Diego
.A day in the life.About the hiring group.Job responsibilitiesEconomistThe North American Consumer Economics team uses Economics, Statistics, and Machine Learning to understand and design the complex economy of Amazon’s network of buyers and sellers. We are an interdisciplinary team, committed to use of cutting edge technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon.We are looking for an outstanding Economist who is able to provide structure around complex business problems, work with machine learning scientists to estimate and validate their models on large scale data, and who can help business and tech partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business. We are looking for creative thinkers who can combine a strong economic toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas.In this role, we expect you be able to own the development of economic models and to manage, in close collaboration with scientists and engineers, the data analysis, modeling, and experimentation that is necessary for estimating and validating your model. You will need to work with our business partners to communicate the properties of your analysis/modeling and be able to work to incorporate their feedback and requests into your project. Experience in applied economic analysis is essential, and you should be familiar with modern tools for data science and business analysis.We are particularly interested in candidates with research background in applied microeconomics, empirical IO, Marketing, Finance, applied econometrics, and market design. However, we want to talk with any experienced economist with an interest in working on an interest in working on innovative, strategic problems with significant business impact.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Sr. Applied Scientist
US, WA, Seattle
We are constantly making Alexa the best voice assistant in the world. Amazon’s Alexa cloud service and Echo devices are used every day, by people you know, in and about their homes. The Alexa Monetization team is hiring talented and experienced Sr. Applied Scientists to help building the next generation products for Alexa across multiple channels and domains. We are seeking an experienced, entrepreneurial, big thinker for a confidential new initiative within Alexa. You will be joining a team doing innovative work, making a direct impact to customers, showing measurable success, and building with the latest natural language processing systems. If you are holding out for an opportunity to:Make a huge impact as an individual· Be part of a team of smart and passionate professionals who will challenge you to grow every day· Solve difficult challenges using your expertise in coding elegant and practical solutions· Create applications at a massive scale used by millions of people· Work with machine learning systems to deliver real experiences, not just researchAnd you are experienced with…· Drive applied science (machine learning) projects end-to-end ~ from ideation, analysis, prototyping, development, metrics, and monitoring· Conduct deep analyses on massive user and contextual data sets· Propose viable modeling ideas to advance optimization or efficiency, with supporting argument, data, or, preferably, preliminary results· Design, develop, and maintain scalable, Machine Learning models with automated training, validation, monitoring and reporting· Stay familiar with the field and apply state-of-the-art Machine Learning techniques to NLP and related optimization problems· Produce peer-reviewed scientific paper in top journals and conferencesAnd you constantly look for opportunities to…· Innovate, simplify, reduce waste, and increase efficiencies· Use data to make decisions and validate assumptions· Automate processes otherwise performed by humans· Learn from others and help grow those around you...then we would love to chat!In 2021, we have the opportunity to build new products and features from the ground up and we are looking for strong, bias for action engineering leaders who are not afraid of taking bold bets and trying new things to improve customer experience for Alexa.As part of a new and growing team, you will be iterating on new features and products to help drive innovation and expansion. You will work on cross-functional and cross-domain opportunities; tackle challenging projects aim to accelerate experimentations in Alexa; and build out operating mechanisms and technology to enable novel customer experiences. You will be instrumental in setting the team culture, quality bar, engineering best practices, and norms. Mentoring and growing the team around you will be one of the primary ways you measure your own success. You will have the opportunity to contribute and develop deep expertise in the areas of distributed systems, machine learning, conversational technologies, user interfaces (including voice and natural user interfaces), data storage and data pipelines.This role is exciting for scientists who love to apply startup mindset to their day-to-day, enjoy working cross-functionally to master both business and technology knowledge, and are passionate about building engineering best practices. If you are looking for opportunity to learn, grow and lead, this is the position for you.
View from space of a connected network around planet Earth representing the Internet of Things.
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