Why Python?
Python is an uniquely flexible language – it can be used for everything from software engineering (writing applications) to web app development, system administration to “scientific computing” — which includes scientific analysis, engineering, modeling, data analysis, data science, and the like.
Unlike some “generalist” providers who teach generic Python to the lowest common denominator across all these roles, Enthought specializes in Python training for professionals in scientific and analytic fields. In fact, that’s our DNA, as we are first and foremost scientists, engineers, and data scientists ourselves, who just happen to use Python to drive our daily data wrangling, modeling, machine learning, numerical analysis, simulation, and more.
If you’re a professional using Python, you’ve probably had the thought, “how can I be better, smarter, and faster in using Python to get my work done?” That’s where Enthought comes in – we know that you don’t just want to learn generic Python syntax, but instead you want to learn the key tools that fit the work you do, you want hard-won expert insights and tips without having to discover them yourself through trial and error, and you want to be able to immediately apply what you learn to your work.
Bottom line: you want results and you want the best value for your invested time and money. These are some of the guiding principles in our approach to training.
What: Presentation and Q&A with Dr. Michael Connell, COO & Chief Digital Transformation Officer
Who Should Watch: Anyone who wants to develop proficiency in Python for scientific, engineering, analytic, quantitative, or data science applications, including team leaders considering Python training for a group, learning and development coordinators supporting technical teams, or individuals who want to develop their Python skills for professional applications
View the Python for Professionals Webinar Recording here
In this webinar, we’ll give you the information you need to decide whether Enthought’s Python training is the right solution for your or your team’s unique situation, helping answer questions such as:
- What kinds of Python training does Enthought offer? Who is it designed for?
- Who will benefit most from Enthought’s training (current skill levels, roles, job functions)?
- What are the key things that make Enthought’s training different from other providers and resources?
- What are the differences between Enthought’s training courses and who is each one best for?
- What specific skills will I have after taking an Enthought training course?
- Will I enjoy the curriculum, the way the information is presented, and the instructor?
- Why do people choose to train with Enthought? Who has Enthought worked with and what is their feedback?
We’ll also provide a guided tour and insights about our our five primary course offerings to help you understand the fit for you or your team:
- Python Foundations
- Python for Scientists and Engineers
- Python for Data Science
- Python for Data Analysis
- Pandas Mastery Workshop
View the Python for Professionals Webinar Recording here
Presenter: Dr. Michael Connell, COO & Chief Digital Transformation Officer
Ed.D, Education, Harvard University
M.S., Electrical Engineering and Computer Science, MIT
About Enthought’s Python Training
Enthought’s Python training is designed to accelerate the development of skill and confidence for people using Python in their work. In addition to the Python language, we develop proficiency in the core tools used by all scientists, engineers, analysts, and data scientists, such as NumPy (fast array computing), Matplotlib (data visualization and plotting), and Pandas (data wrangling and analysis), as well as tools and techniques that are more specialized for different technical roles.
Our courses are created by our Python experts and instructors based on their extensive experience in using Python and its many technical packages to solve real-world problems across domains ranging from geophysics to biotechnology to aeronautical engineering to marketing analysis and everything in between. The courses have also been refined based on lessons learned over more than a decade of teaching thousands of people to use Python effectively in their everyday work.
About Enthought’s Python Instructors
More than “trainers,” our instructors are professional peers, which means you won’t just go through a checklist of programming or computer science topics, you’ll learn from a Python expert who can guide you through the ins and outs of applying specific concepts to scientific and analytic problems.
Related Content
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…
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…
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...
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.
7 Pro-Tips for Scientists: Using LLMs to Write Code
Scientists gain superpowers when they learn to program. Programming makes answering whole classes of questions easy and new classes of questions become possible to answer….
The Importance of Large Language Models in Science Even If You Don’t Work With Language
OpenAI's ChatGPT, Google's Bard, and other similar Large Language Models (LLMs) have made dramatic strides in their ability to interact with people using natural language....
4 Reasons to Learn Xarray and Awkward Array—for NumPy and Pandas Users
You know it. We know it. NumPy is cool. Pandas is cool. We can bend them to our will, but sometimes they’re not the right tools…
Making the Most of Small Data in Scientific R&D
For many traditional innovation-driven organizations, scientific data is generated to answer specific immediate research questions and then archived to protect IP, with little attention paid...
7 Lesser-Known Command Line Tools That Ship with Python
Like most people, I mostly interact with Python using the default REPL or with IPython. Yet, I often reach for one of the Python tools…
ChatGPT on Software Engineering
Recently, I’ve been working on a new course offering in Enthought Academy titled Software Engineering for Scientists and Engineers course. I’ve focused on distilling the…