Introducing Enthought Academy, The Premier Python Training Program for Scientific Organizations

Introducing Enthought Academy, The Premier Python Training Program for Scientific Organizations

Enthought’s training equips students with the digital skills to solve their most complex science and engineering challenges

Austin, TX – October 4, 2022Enthought, a company powering digital transformation for science, today announced the launch of Enthought Academy (“Academy”), the most effective Scientific Python curriculum for R&D professionals. Informed by more than 20 years of training and consulting experience, Enthought Academy empowers scientists and engineers with the core skills needed to leverage technology to accelerate their research. Academy instructors are scientists and engineers themselves and have deep knowledge and understanding of the strategies and technologies covered in each track, and extensive practical experience applying Python to solve complex challenges across a range of science-based industries.

According to the World Economic Forum, 50% of all employees will need reskilling by 2025, as adoption of technology increases. To fill this growing skills gap within science-based businesses, Enthought—who has trained over 10,000 scientists and engineers and co-created the SciPy package and conference—launched the Academy to broaden access to the fundamental digital skills required to establish continuous value creation. 

“We are thrilled to announce the launch of Enthought Academy,” said Eric Olsen, Director of Training Solutions at Enthought. “Many other training programs are one-size-fits-all solutions, offering a large, difficult to navigate, catalog of classes taught with pre-recorded training videos. And while easily accessible, we know these rarely work. At Enthought, we understand our students’ time is precious and have designed our program to maximize impact with the ‘Monday Morning Difference.’ With hands-on learning, expert scientist instructors and domain-relevant exercises, Enthought Academy ensures students return to work ready to deliver actionable solutions from day one.” 

Corporate groups or individual learners have the option to enroll in the following four learning tracks, each of which begins with a Python Foundations course and culminates in a certificate:

  • Machine Learning Track: automate decision-making and make predictions for both “big data” and the real world of “small” R&D data. 
  • Data Analysis Track: compile data, make sense of it and communicate important conclusions with prose, code and visualizations.
  • Tool Maker Track: develop, share and maintain software tools to save time, leverage experts’ knowledge and multiply their impact.
  • Manager Track: develop a shared language, separate myth from reality, establish best practices to maintain and scale digital tools and infrastructure.

“People are at the core of digital transformation efforts, not technology,” said Alexandre Chabot-Leclerc, Vice President of Digital Transformation Solutions at Enthought. “Enthought Academy encapsulates everything we’ve learned over the last 20 years about the skills and mindset shifts required to fundamentally change the way R&D organizations operate and achieve ROI.”

To learn more about Enthought Academy and how to enroll, please visit https://www.enthought.com/academy/

 

About Enthought

Enthought, Inc. powers digital transformation for science. Enthought’s technology and deep scientific expertise enable faster discovery and continuous innovation, building a digitally enabled workforce and arming them with analytics-ready scientific data to be catalysts of value creation in science and business. Enthought specializes in transforming organizations in the electronic, semiconductor, materials design, manufacturing, pharmaceutical, biotechnology, energy and consumer goods markets. Enthought is headquartered in Austin, Texas, with additional offices in Houston, Texas; Cambridge, United Kingdom; Zürich, Switzerland; and Tokyo, Japan. For more information visit enthought.com, or follow on LinkedIn and Twitter.  

 

PAN Communications

Lauren Force, (617) 502-4366

Enthought@pancomm.com 

Share this article:

Related Content

Digital Transformation in Practice

There is much more to digital transformation than technology, and a holistic strategy is crucial for the journey.

Read More

Leveraging AI for More Efficient Research in BioPharma

In the rapidly-evolving landscape of drug discovery and development, traditional approaches to R&D in biopharma are no longer sufficient. Artificial intelligence (AI) continues to be a...

Read More

Utilizing LLMs Today in Industrial Materials and Chemical R&D

Leveraging large language models (LLMs) in materials science and chemical R&D isn't just a speculative venture for some AI future. There are two primary use...

Read More

Top 10 AI Concepts Every Scientific R&D Leader Should Know

R&D leaders and scientists need a working understanding of key AI concepts so they can more effectively develop future-forward data strategies and lead the charge...

Read More

Why A Data Fabric is Essential for Modern R&D

Scattered and siloed data is one of the top challenges slowing down scientific discovery and innovation today. What every R&D organization needs is a data...

Read More

Jupyter AI Magics Are Not ✨Magic✨

It doesn’t take ✨magic✨ to integrate ChatGPT into your Jupyter workflow. Integrating ChatGPT into your Jupyter workflow doesn’t have to be magic. New tools are…

Read More

Top 5 Takeaways from the American Chemical Society (ACS) 2023 Fall Meeting: R&D Data, Generative AI and More

By Mike Heiber, Ph.D., Materials Informatics Manager Enthought, Materials Science Solutions The American Chemical Society (ACS) is a premier scientific organization with members all over…

Read More

Real Scientists Make Their Own Tools

There’s a long history of scientists who built new tools to enable their discoveries. Tycho Brahe built a quadrant that allowed him to observe the…

Read More

How IT Contributes to Successful Science

With the increasing importance of AI and machine learning in science and engineering, it is critical that the leadership of R&D and IT groups at...

Read More

From Data to Discovery: Exploring the Potential of Generative Models in Materials Informatics Solutions

Generative models can be used in many more areas than just language generation, with one particularly promising area: molecule generation for chemical product development.

Read More