[Virtual workshop] - Energy Data Science Using Python (5 half days)

daytumis a data science education platform that focuses on the energy industry.daytum’smission is to help createunicorns: energy industry specialists with a deep knowledge of statistics, coding, and data analytics and data science.daytumoffers a range ofeducational coursesandenterprise solutionsthat teach energy industry professionals the Python data science ecosystem, advanced statistics, machine learning, and software engineering. Attendees will learn these skills by building their own models and dashboards using tangible energy industry datasets.

daytum

Join us from 1-5 pm for a 5-day workshop for energy professionals. Learn the essential skills needed to be effective data scientists.

<h1>Virtual Workshop Overview: </h1>“Information is the oil of the 21st century, and analytics is the combustion engine” – Peter SondergaardOur 5 half-day Virtual 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 5 half-day workshop will be geared toward teaching students how to leverage the Python data science ecosystem (think Numpy, Pandas, Matplotlib, 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 (SEE DASHBOARD BELOW). 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!

<h2>Course Format:</h2>Strategy After registration you will be sent a Zoom link, Prerequisites, and access to our online classroom 1 week before the course.Our 5 half-day Virtual 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. 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 are your laptop and your fingers! Class SizeWe 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.Prerequisites - to be completed before class1) DOMAIN - Oil and gas industry experience and familiarity with basic Petroleum Engineering / Geology concepts (e.g. understanding what Production, Porosity, and Permeability is)2) CODING - Basic Python proficiency OR Completion of datacamp’s “<a href="https://www.datacamp.com/courses/introduction-to-data-science-in-python" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Introduction to Data Science in Python</a>” course3) GIT/GITHUB - Familiarity with Git and Github OR just watch this <a href="https://www.youtube.com/watch?v=5OLUolv4DaM" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">video</a>!

<h2>Other: </h2>Cancellation Policy Cancellation can be done by sending an email to contact@daytum.io.Event Cancellation by daytumdaytum reserves the right to cancel an event due to low enrollment, inclement weather or other circumstances which would make the event non-viable. If daytum cancels an event, registrants will be offered a full refund. Should circumstances arise that result in the postponement of an event, registrants will have the option to either receive a full refund or transfer registration to the same event at the new, future date.Registration Cancellation by ParticipantUnless specifically stated on registration materials, the deadline to receive a refund for an individual ticket is one week before the event.Software RequirementsA 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!Ordering as a GroupFor online group orders from the same company, be sure to contact us at contact@daytum.io for discounted rate.

Our {communityGuidelinesLink} describe the sort of content we prohibit on Eventbrite. If you suspect an event may be in violation, you can report it to us so we can investigate.

To report other categories of prohibited or illegal content, submit {link}

[Virtual workshop] - Energy Data Science Using Python (5 half days)

More events from daytum

Discover more events from daytum, from Science & Tech to other experiences you might love.

Still looking for the right event?

Explore all online events to browse and filter by date, category, and more.

[Virtual workshop] - Energy Data Science Using Python (5 half days)

More events from daytum

Discover more events from daytum, from Science & Tech to other experiences you might love.

You might also like...

Browse more events with different dates, prices, and formats to find your next great experience.

Still looking for the right event?

Explore all online events to browse and filter by date, category, and more.