Continuum Analytics

Python Training Classes

Continuum Analytics, in partnership with Dabeaz LLC, offers several Python training courses to meet your programming needs. All of our courses, taught by Python experts, embody the philosophy that the best way to learn is with hands-on experience to real world problems. These courses are available to individuals online, at numerous sites, or as an in-house course at your place of business. Please check the corresponding course page to find the next class being taught, or contact us to schedule a private session.

  • Practical Python Programming
    A 3-day class on the Python programming language and standard library with a focus on applying Python to problems in scripting, data analysis, and systems programming. This course assumes no prior experience with Python, but does assume participants know how to program in another programming language. It is especially well-suited for programmers who want to know what Python is all about without extra fluff.

  • Python for Finance
    Geared toward quantitative analysts and technology staff, Python for Finance provides a strong foundation which will enable you to work and prototype much more rapidly. This course covers open source Python tools relevant to solving your day-to-day financial programming problems. Specific topics addressed include: array computation and mathematics with NumPy; statistical computation with SciPy; working with tabular data in Pandas to generate summary statistics and rolling window calculations; and using libraries for numerical optimization.

  • Python for Science
    Python for Science is Continuum’s training course geared specifically toward scientists and engineers. The course provides a strong foundation of best practices for doing array-oriented computing with Python and will help you understand the vast number of tools available to you for doing technical computing with Python. This course covers open source Python tools relevant to solving your day-to-day scientific and engineering programming problems. Specific topics examined include: array computation and mathematics with NumPy; statistics, linear algebra, optimization, interpolation, and advanced computation with SciPy; and working with tabular data in Pandas to generate summary statistics and rolling window calculations.

  • Custom Python Courses
    Continuum will work with you to develop then deliver training specific to your organizational needs. These courses can be delivered at your location or in our training facility in Austin, TX.

Additional course offerings are available through our partner, David Beazley.

Course Information


Schedule a Course

To attend a course, please check the corresponding course page to find the next class being taught, or contact us to schedule a private session. Classes are typically scheduled at least 8 weeks in advance and can be held worldwide.

Virtual Courses

Virtual courses are taught via an interactive, online meeting program. These courses are open to enrollment from the public and are limited to 25 students. Courses run from 9am CT to 5pm CT with a one-hour lunch break. Class time is split between instruction and hands-on programming exercises, with the instructor on-hand to answer questions at any time.

Course manuals (in .pdf format) and meeting login information will be sent the week before your course start date. Students are expected to have a working Python installation before the start of class and are encouraged to use a Mac or PC to access the class. Linux offers only limited virtual meeting functionality. Anaconda is Continuum’s free Python distribution and can be downloaded here.

Open Courses

Open courses are limited to 25 students and are open to enrollment from the public. Courses run from 9am to 5pm local time with a one-hour lunch break. Class time is split between instruction and hands-on programming exercises, with the instructor on-hand to answer questions at any time.

The course can be taught on Windows, Linux, or Mac OS X. Students are expected to have a working Python installation before the start of class. (Anaconda is Continuum’s free Python distribution and can be downloaded here.) Course manuals are provided at the start of the class.

On-Site Courses

On-site courses are recommended for 12 students, but can accommodate up to 25, and are typically conducted at the client’s place of business. Class time is split between instruction and hands-on programming exercises, with the instructor on-hand to answer questions at any time. Course topics can be customized to the client’s needs if arranged in advance. (Additional curriculum development rates may apply.)

Clients provide the instruction space, video projector, and computers where students can work on the programming exercises. The course can be taught on Windows, Linux, or Mac OS X. Students are expected to have a working Python installation on their computers before the start of class. (Anaconda is Continuum’s free Python distribution and can be downloaded here.) Course manuals are provided at the start of the class.

Organizations who purchase classroom training sessions are eligible to receive 25% off any virtual class for employees a period of one year after the classroom training date. Contact training@continuum.io for more details.

Prerequisites

Although no prior experience with Python is required for our Practical Python Programming courses, the course assumes that students have prior experience with some other programming language such as C++, Java, or Perl. This is not an introductory programming class for absolute beginners. Participants should already be familiar with the basic concepts of programming such as variables, statements, control-flow, functions, arrays, data structures, and common programming problems (e.g., searching, sorting, etc.).

In addition, it is assumed that students already know how to work with files, folders, editors, command shells, environment settings, internet connections, and other essential aspects of using a computer for software development.

Students in the Python for Science and Python for Finance classes should be familiar with the topics covered in Practical Python Programming.

More Information

Questions? Need customized training? Contact us at training@continuum.io or call 512-222-5440.

Refund Policy

100% --- within 24 hours of registration
100% --- 28 days or more before course
90% --- 21 - 27 days or more before course
80% --- 14 - 20 days or more before course
70% --- 7 - 13 days or more before course
50% --- 1 - 6 days before course
0%   --- once the event has started