Category Archives: Webinars

Webinar: An Exclusive Peek “Under the Hood” of Enthought Training and the Pandas Mastery Workshop


Enthought’s Pandas Mastery Workshop is designed to accelerate the development of skill and confidence with Python’s Pandas data analysis package — in just three days, you’ll look like an old pro! This course was created ground up by our training experts based on insights from the science of human learning, as well as what we’ve learned from over a decade of extensive practical experience of teaching thousands of scientists, engineers, and analysts to use Python effectively in their everyday work.

In this webinar, we’ll give you the key information and insight you need to evaluate whether the Pandas Mastery Workshop is the right solution to advance your data analysis skills in Python, 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 workshop attendees say about the course

Date and Registration Info:
January 26, 2017, 11-11:45 AM CT
Register (if you can’t attend, register and we’ll be happy to send you a recording of the session)


michael_connell-enthought-vp-trainingPresenter: Dr. Michael Connell, VP, Enthought Training Solutions

Ed.D, Education, Harvard University
M.S., Electrical Engineering and Computer Science, MIT

Why Focus on Pandas:

Python has been identified as the most popular coding language for five years in a row. One reason for its popularity, especially among data analysts, data scientists, engineers, and scientists across diverse industries, is its extensive library of powerful tools for data manipulation, analysis, and modeling. For anyone working with tabular data (perhaps currently using a tool like Excel, R, or SAS), Pandas is the go-to tool in Python that not only makes the bulk of your work easier and more intuitive, but also provides seamless access to more specialized packages like statsmodels (statistics), scikit-learn (machine learning), and matplotlib (data visualization). Anyone looking for an entry point into the general scientific and analytic Python ecosystem should start with Pandas!

Who Should Attend: 

Whether you’re a training or learning development coordinator who wants to learn more about our training options and approach, a member of a technical team considering group training, or an individual looking for engaging and effective Pandas training, this webinar will help you quickly evaluate how the Pandas Mastery Workshop can meet your needs.

Additional Resources

Upcoming Open Pandas Mastery Workshop Sessions:

London, UK, Feb 22-24
Chicago, IL, Mar 8-10
Albuquerque, NM, Apr 3-5
Washington, DC May 10-12
Los Alamos, NM, May 22-24
New York City, NY, Jun 7-9

Learn More

Have a group interested in training? We specialize in group and corporate training. Contact us or call 512.536.1057.

Download Enthought’s Pandas Cheat Sheets

Webinar: Solving Enterprise Python Deployment Headaches with the New Enthought Deployment Server

See a recording of the webinar:

Built on 15 years of experience of Python packaging and deployment for Fortune 500 companies, the NEW Enthought Deployment Server provides enterprise-grade tools groups and organizations using Python need, including:

  1. Secure, onsite access to a private copy of the proven 450+ package Enthought Python Distribution
  2. Centralized management and control of packages and Python installations
  3. Private repositories for sharing and deployment of proprietary Python packages
  4. Support for the software development workflow with Continuous Integration and development, testing, and production repositories

In this webinar, Enthought’s product team demonstrates the key features of the Enthought Deployment Server and how it can take the pain out of Python deployment and management at your organization.

Who Should Watch this Webinar:

If you answer “yes” to any of the questions below, then you (or someone at your organization) should watch this webinar:

  1. Are you using Python in a high-security environment (firewalled or air gapped)?
  2. Are you concerned about how to manage open source software licenses or compliance management?
  3. Do you need multiple Python environment configurations or do you need to have consistent standardized environments across a group of users?
  4. Are you producing or sharing internal Python packages and spending a lot of effort on distribution?
  5. Do you have a “guru” (or are you the guru?) who spends a lot of time managing Python package builds and / or distribution?

In this webinar, we demonstrate how the Enthought Deployment Server can help your organization address these situations and more.

Webinar: Introducing the NEW Python Integration Toolkit for LabVIEW

See a recording of the webinar:

LabVIEW is a software platform made by National Instruments, used widely in industries such as semiconductors, telecommunications, aerospace, manufacturing, electronics, and automotive for test and measurement applications. In August 2016, Enthought released the Python Integration Toolkit for LabVIEW, which is a “bridge” between the LabVIEW and Python environments.

In this webinar, we’ll demonstrate:

  1. How the new Python Integration Toolkit for LabVIEW from Enthought seamlessly brings the power of the Python ecosystem of scientific and engineering tools to LabVIEW
  2. Examples of how you can extend LabVIEW with Python, including using Python for signal and image processing, cloud computing, web dashboards, machine learning, and more

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Webinar: Fast Forward Through the “Dirty Work” of Data Analysis: New Python Data Import and Manipulation Tool Makes Short Work of Data Munging Drudgery

Python Import & Manipulation Tool Intro Webinar

Whether you are a data scientist, quantitative analyst, or an engineer, or if you are evaluating consumer purchase behavior, stock portfolios, or design simulation results, your data analysis workflow probably looks a lot like this:

Acquire > Wrangle > Analyze and Model > Share and Refine > Publish

The problem is that often 50 to 80 percent of time is spent wading through the tedium of the first two stepsacquiring and wrangling data – before even getting to the real work of analysis and insight. (See The New York Times, For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights)


Enthought Canopy Data Import Tool

Try the Data Import Tool with your own data. Download here.

In this webinar we’ll demonstrate how the new Canopy Data Import Tool can significantly reduce the time you spend on data analysis “dirty work,” by helping you:

  • Load various data file types and URLs containing embedded tables into Pandas DataFrames
  • Perform common data munging tasks that improve raw data
  • Handle complicated and/or messy data
  • Extend the work done with the tool to other data files

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Webinar: Work Better, Smarter, and Faster in Python with Enthought Training on Demand

Join Us For a Webinar

Enthought Training on Demand Webinar

We’ll demonstrate how Enthought Training on Demand can help both new Python users and experienced Python developers be better, smarter, and faster at the scientific and analytic computing tasks that directly impact their daily productivity and drive results.

View a recording of the Work Better, Smarter, and Faster in Python with Enthought Training on Demand webinar here.

What You’ll Learn

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Advanced Cython Recorded Webinar: Typed Memoryviews

Author: Kurt SmithWebinar_screenshot

Typed memoryviews are a new Cython feature for accessing memory buffers, such as NumPy arrays, without any Python overhead. This makes them very useful for manipulating blocks of memory in Cython directly without calling into the Python-C API.  Typed memoryviews have a clean declaration syntax and have a NumPy-like look and feel, supporting slicing, striding and indexing.

I go into more detail and provide some specific examples on how to use typed memoryviews in this webinar: “Advanced Cython: Using the new Typed Memoryviews”.

If you would like to watch the recorded webinar, you can find a link below (the different formats will play directly in different browsers so check to see which one works for you, and you won’t have to download the whole recording ahead of time):

“Why We Built Enthought Canopy, An Inside Look” Recorded Webinar

We posted a recording of a 30 minute webinar that we did on the 20th that covers what Canopy is and why we developed it. There’s a few minutes of Brett Murphy(Product Manager at Enthought) discussing the “why” with some slides, and then Jason McCampbell (Development Manager for Canopy) gets into the interesting part with a 15+ minute demo of some of the key capabilities and workflows in Canopy. If you would like to watch the recorded webinar, you can find it here (the different formats will play directly in different browsers so check them and you won’t have to download the whole recording first):

Summed up in one line: Canopy provides the minimal set of tools for non-programmers to access, analyze and visualize data in an open-source Python environment.

The challenge in the past for scientists, engineers and analysts who wanted to use Python had been pulling together a working, integrated Python environment for scientific computing. Finding compatible versions of the dozens of Python packages, compiling them and integrating it all was very time consuming. That’s why we released the Enthought Python Distribution (EPD) many years back. It provided a single install of all the major packages you needed to do scientific and analytic computing with Python.

But the primary interface for a user of EPD was the command line. For a scientist or analyst used to an environment like MATLAB or one of the R IDEs, the command line is a little unapproachable and makes Python challenging to adopt. This is why we developed Canopy.

Enthought Canopy is both a Python distribution (like EPD) and an analysis environment. The analysis environment includes an integrated editor and IPython prompt to faciliate script development & testing and data analysis & plotting. The graphical package manager becomes the main interface to the Python ecosystem with its package search, install and update capabilities. And the documentation browser makes online documentation for Canopy, Python and the popular Python packages available on the desktop.

Check out the Canopy demo in the recorded webinar (link above). We hope it’s helpful.