Category Archives: Austin

TGIF: SciPy 2012 Recap Video

As we wait for the SciPy talk videos to make their way onto the web, we’d like to share a short film recapping SciPy 2012.

The latest iteration of the SciPy conference was another great example of the scientific python community coming together to share “the latest and greatest.” Most organizations want to change the world in some way or another. At Enthought, we attempt to do this by building tools that help our customers – in both academia and industry – concentrate on solving their actual problems rather than wrestling with technology. We believe Python’s ability to operate smoothly in different contexts (e.g., desktop, web, array-based and distributed computing, etc.) makes it a highly productive and pragmatic tool with which to build solutions.

The SciPy community is changing the world by continually pushing technical computing forward in a pragmatic way. One just has to look at the content and tools presented at SciPy historically to know that this community has been been up to its neck in “data science” for some time. One could also argue, however, that SciPy is one of the best kept secrets in technical computing. As the recent focus on MapReduce solutions illustrates, the world is in the grips of “big computation.” It will only get tougher in the foreseeable future. At the same time, “big data” is a relative term. “Big” for a bioinformatician is different than for a macro hedge fund analyst, and these differences can often be measured in orders of magnitude. And when it comes to solutions, rarely does one size fit all.

In contrast, SciPy addresses a broad array of problems. SciPy 2012 offered High Performance Computing and Visualization tracks, with tutorials on machine learning, plotting, parallel computing, and time series analysis. Sometimes all these topics could be found in a single talk (see VisIt). The community also demonstrated some open-mindedness by inviting Jeff Bezanson, one of the authors of Julia, to share his experience building a language specifically designed for technical computing. It turns out there is a fair amount of overlap between what the SciPy community and the Julia team are planning. With LLVM IR increasingly being viewed as a common target, there is real excitement about what the future holds for language development and interaction.

This is all to say that SciPy has a lot to offer the world. Stay tuned for a bigger and better SciPy next year!

Scipy 2012

No Mas

Scipy 2012 is wrapping up today tomorrow as bands of sprinters come together to hack away on their projects of interest. Many thanks to the sponsors and volunteers that made this year’s Scipy another success. The Scipy conference has always been highly technical. Although “data science” and “big data” have become buzzwords recently, Scipy has been exploring these themes for many years. Projects featuring machine learning, high performance computing, and visualization were in full attendance at this year’s Scipy. Stay tuned for links to talk videos (care of Next Day Video)!

Intro to Scientific Computing in Python, June 15-19, Austin TX

Enthought is offering “Introduction to Scientific Computing in Python” at our offices in Austin, Texas from June 15th to June 19th. This course is intended for scientists and engineers who want to learn to use Python for day-to-day computational tasks.

  • Day 1: Introduction to the Python Language
  • Day 2: Array Calculations with NumPy
  • Day 3: Numeric Algorithms with SciPy
  • Day 4: Interfacing Python with Other Languages
  • Day 5: Interactive 2D Visualization with Chaco

The cost for the course is $2500. Please see the course description on the Enthought website for details.

Space is still available in our course on Python for Science, Engineering, and Financial Analysis, May 18th to 21st, in New York City

Intro to Scientific Computing in Python, Feb. 16-20, Austin TX

Enthought is offering “Introduction to Scientific Computing in Python” at our offices in Austin, Texas from February 16th to February 20th. This course is intended for scientists and engineers who want to learn to use Python for day-to-day computational tasks.

  • Day 1: Introduction to the Python Language
  • Day 2: Array Calculations with NumPy
  • Day 3: Numeric Algorithms with SciPy
  • Day 4: Interfacing Python with Other Languages
  • Day 5: Interactive 2D Visualization with Chaco

The cost for the course is $2500. Please see the course description on the Enthought website for details.

Python for Scientific Computing – Training Course

Enthought

Enthought is offering an open training course for Scientific Computing with Python at its Austin, TX offices. Space is limited. We’ll accept the first 15 people who register.

Date: June 23-27, 2008
Location: Austin, Texas, at Enthought’s offices
Cost: 3 days: $1500; 5 days: $2500. You can attend either the first three days of the course or the entire five days.
Registration: Contact Leah Jones at 1-512-536-1057 to register via credit card, or email info@enthought.com with any questions.

Please see the training web page for the full syllabus and more details.