The KTH AI Society is organizing its AI Day on Tour: an all-day event that will give 25 KTH students the opportunity to visit three industry-leading companies: Sana Labs, QuantumBlack, and Modulai. Participants will be able to witness how real professionals work and to learn more about potential future employers.
08:15 - 08:30 - We meet at Östermalmstorg 8
08:30 - 10:30 - Sana Labs
1-hour presentation followed by 1-hour mingle with breakfast.
11:00 - 14:00 - QuantumBlack
2-hour workshop on Kedro followed by 1-hour lunch. You can find more information about Kedro here.
15:00 - 17:00 - Modulai
Presentation on working on a client base with machine learning solutions. AW/Mingle including drinks will follow.
Places in the event are limited to 25, so a selection of participants will be performed by QuantumBlack based on the resume that you will have to submit with your application. By applying to the event you agree to share your information and resume with the collaborating companies. Applications end at midnight on the 4th of November!
Learning is the foundation for human progress—a chance to create better versions of ourselves and the world around us. This belief is the heart of Sana, and it informs everything we do. With breakthroughs in AI, we no longer need to use one-size-fits-all training models. Instead, we can make learning personalized, adaptive, and impactful.
QuantumBlack is an advanced analytics firm operating at the intersection of strategy, technology, and design to improve performance outcomes for organizations. In 2015 we became part of McKinsey & Company. Together we combine our advanced analytics, design, and engineering expertise with McKinsey’s industry knowledge and organizational change management experience.
Modulai’s clients range from startups to multinational companies. What they all have in common is that machine learning is or could be central to how they operate, compete and create value. Their services range from advisory projects and feasibility studies to end-to-end development and refinement of machine learning systems and products.
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