What: A guided walkthrough and Q&A about Enthought’s technical training course Python for Scientists & Engineers with Enthought’s VP of Training Solutions, Dr. Michael Connell
Who Should Attend: individuals, team leaders, and learning & development coordinators who are looking to better understand the options to increase professional capabilities in Python for scientific and engineering applications
“Writing software is not my job…I just have to do it every day.”
-21st Century Scientist or Engineer
Many scientists, engineers, and analysts today find themselves writing a lot of software in their day-to-day work even though that’s not their primary job and they were never formally trained for it. Of course, there is a lot more to writing software for scientific and analytic computing than just knowing which keyword to use and where to put the semicolon.
Software for science, engineering, and analysis has to solve the technical problem it was created to solve, of course, but it also has to be efficient, readable, maintainable, extensible, and usable by other people — including the original author six months later!
It has to be designed to prevent bugs and — because all reasonably complex software contains bugs — it should be designed so as to make the inevitable bugs quickly apparent, easy to diagnose, and easy to fix. In addition, such software often has to interface with legacy code libraries written in other languages like C or C++, and it may benefit from a graphical user interface to substantially streamline repeatable workflows and make the tools available to colleagues and other stakeholders who may not be comfortable working directly with the code for whatever reason.
Enthought’s Python for Scientists and Engineers is designed to accelerate the development of skill and confidence in addressing these kinds of technical challenges using some of Python’s core capabilities and tools, including:
- The standard Python language
- Core tools for science, engineering, and analysis, including NumPy (the fast array programming package), Matplotlib (for data visualization), and Pandas (for data analysis); and
- Tools for crafting well-organized and robust code, debugging, profiling performance, interfacing with other languages like C and C++, and adding graphical user interfaces (GUIs) to your applications.
In this webinar, we give you the key information and insight you need to evaluate whether Enthought’s Python for Scientists and Engineers course is the right solution to take your technical skills to the next level, including:
- Who will benefit most from the course
- A guided tour through the course topics
- What skills you’ll take away from the course, how the instructional design supports that
- What the experience is like, and why it is different from other training alternatives (with a sneak peek at actual course materials)
- What previous course attendees say about the course