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daytum: Introductory Energy Data Science Workshop (3-Day)

From Mon 22 July 2019 to Wed 24 July 2019
8:00 AM - 6:00 PM
Ended


3-Day WORKSHOP FOCUSED ON TEACHING ENERGY INDUSTRY PROFESSIONALS THE ESSENTIAL SKILLS NEEDED TO BE EFFECTIVE DATA SCIENTISTS. WORKSHOP OVERVIEW: _“In short, software is eating the world.” – Marc Andreessen (2011)_ Our 3-day workshop focuses on the application of programming, visualizations, and data science solutions to energy industry data. We’re biased Python users. We believe that Python will be a key tool in the future of data analytics and data science (it already is!) and, as such, our 3-day workshop will be geared toward teaching students how to leverage the Python data science ecosystem (think Numpy, Pandas, Matplotlib, and Jupyter , etc.). This course is designed to be highly interactive. You will be coding Python classes and functions, dashboards, and effective visualizations, using all free open-source tools. By the end of our workshop, you will have practical experience designing tools that will optimize workflows, as well as a firm understanding of how the Python data science ecosystem can be applied to energy industry data. As a deliverable, you will have created a dynamic dashboard using the knowledge and expertise in new tools gained over the course. Note: Our program is rigorous, fast-paced, and focused on practical technical skills needed to solve data problems, automate workflows, visualize data, and leverage predictive analytics. It won’t be easy, but it will be fun. We hope to see you there! COURSE FORMAT: _Strategy _ Our 3-day workshops incorporate a just-in-time (JIT) teaching strategy. What this means is that we will show you final deliverable (think dashboards, models, visualizations, etc.) and teach you step-by-step how to build it, while exploring the Python data science ecosystem in a broader context. Major course concepts will be covered in one-hour bundles, with 15 minutes of lecture, 15 minutes of live demonstration and 30 minutes of interactive coding, coaching, and troubleshooting. Course materials will consist of web-hosted lecture materials, instructor led demonstrations, and programming examples. Everything will be delivered via a cloud-based Jupyter Lab session, so the only thing you need to bring are your laptop and your fingers! _Class Size_ We believe in tailored and focused instruction within our classrooms and have structured our courses with a 1:15 teacher to student ratio. Our goal is to give each student the attention and continuous feedback necessary to succeed. _Class Material _ daytum classes will include materials for content and reference. Students will be allowed to use class materials (e.g. video-lectures and course notes) for personal use following the completion of the course. OTHER: _Cancellation Policy _ Courses may be cancelled up to two weeks prior to the start of the class. Cancellation can be done by sending an email to contact@daytum.org. If a class is cancelled after this time, the student is responsible for the full cost of the course. _Software Requirements_ A laptop with a working web browser (try Google Chrome!) _Feedback _ Following the course, daytum may ask for feedback on instructor quality and course content. This information is kept highly confidential and is only used solely to improve the content offerings and the quality of instruction! _More Information_ Visit our website [https://daytum.org/]or our blog [https://daytum.org/blog/]to learn more about us.
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25/07/2019 Last update

University of Houston, Student Center South
4455 University Dr, Houston, TX, United States

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