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 Watch: 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
Presenter: Dr. Michael Connell, VP, Enthought Training Solutions
Ed.D, Education, Harvard University
M.S., Electrical Engineering and Computer Science, MIT
Python for Scientists & Engineers Training: The Quick Start Approach to Turbocharging Your Work
If you are tired of running repeatable processes manually and want to (semi-) automate them to increase your throughput and decrease pilot error, or you want to spend less time debugging code and more time writing clean code in the first place, or you are simply tired of using a multitude of tools and languages for different parts of a task and want to replace them with one comprehensive language, then Enthought’s Python for Scientists and Engineers is definitely for you!
This class has been particularly appealing to people who have been using other tools like MATLAB or even Excel for their computational work and want to start applying their skills using the Python toolset. And it’s no wonder — Python has been identified as the most popular coding language for five years in a row for good reason.
One reason for its broad popularity is its efficiency and ease-of-use. Many people consider Python more fun to work in than other languages (and we agree!). Another reason for its popularity among scientists, engineers, and analysts in particular is Python’s support for rapid application development and extensive (and growing) open source library of powerful tools for preparing, visualizing, analyzing, and modeling data as well as simulation.
Python is also an extraordinarily comprehensive toolset – it supports everything from interactive analysis to automation to software engineering to web app development within a single language and plays very well with other languages like C/C++ or FORTRAN so you can continue leveraging your existing code libraries written in those other languages.
Many organizations are moving to Python so they can consolidate all of their technical work streams under a single comprehensive toolset. In the first part of this class we’ll give you the fundamentals you need to switch from another language to Python and then we cover the core tools that will enable you to do in Python what you were doing with other tools, only faster and better!
|Upcoming Open Python for Scientists & Engineers Sessions:
Albuquerque, NM, Sept 11-15, 2017
Washington, DC, Sept 25-29, 2017
Los Alamos, NM, Oct 2-6, 2017
Cambridge, UK, Oct 16-20, 2017
San Diego, CA, Oct 30-Nov 3, 2017
Albuquerque, NM, Nov 13-17, 2017
Los Alamos, NM, Dec 4-8, 2017
Austin, TX, Dec 11-15, 2017
Have a group interested in training? We specialize in group and corporate training. Contact us or call 512.536.1057.
|Download Enthought’s Machine Learning with Python’s Scikit-Learn Cheat Sheets
|Additional Webinars in the Training Series:
Python for Data Science: A Tour of Enthought’s Professional Technical Training Course
Python for Professionals: The Complete Guide to Enthought’s Technical Training Courses
An Exclusive Peek “Under the Hood” of Enthought Training and the Pandas Mastery Workshop
|Download Enthought’s Pandas Cheat Sheets