This 3-day intensive Python training class provides practical, hands-on experience and foundational working knowledge of Python for data analysis, science, engineering, and other technical applications. Whether you are new to Python or a long-time enthusiast, you'll benefit from this focused series of topics and best practices taught by experts who create Python software for notable companies in finance, oil and gas, scientific research, aerospace, biotechnology, marketing analysis and more.
The Python Foundations Core Class will get you up to speed quickly on how to optimize your use of the Python standard language and key Python packages for data exploration, modeling, and analysis. You’ll leave with:
The class will give you the initial building blocks to effectively use Python in your daily work, while setting the foundation for additional skill building in areas of specific interest.
Duration and Format: 3 days intensive live classroom training (with heavy emphasis on hands-on exercises) + 30-day free access to additional self-paced online training with Enthought Training on Demand. Live classes are limited to a maximum of 15 students to allow for dedicated interaction with the instructor.
We kick off the class by exploring the functionality of the IPython Shell, an enhanced interactive science-centric console. Next we review the Jupyter Notebook, a cell-based environment that renders scripts, plots, and rich media in a web-like interface, making it ideal for sharing and publishing analysis with peers. You'll leave with a mastery of these tools that will accelerate your productivity and facilitate collaboration.
Next we move into an introduction to Python’s core language features that form part of your universal toolkit for tasks ranging from initial data exploration to extensible application development. We'll introduce Python's built-in data structures, including how and where each might be used and what trade-offs are present, and we’ll cover Python’s looping and control flow constructs. Along the way we’ll provide insight into Python’s design choices that will help you understand why Python works the way it does.
There are a number of "must-have" packages for scientific computing and data analysis with Python. We'll review three of these in this class that will give you the underpinnings you need to be able to expand your knowledge into additional packages that fit your area of specialization. If you are coming from a background in MATLAB®* or R, you'll find these libraries essential.
Chief among these packages is NumPy, a tool for rapidly manipulating and processing large data sets. Whether you are a scientist writing short scripts to analyze and plot your analytical results or an analyst writing large-scale quantitative finance applications for Wall Street, NumPy should be part of your toolbox. We give you a jump start with the basics in the classroom, then provide you additional curated lectures to extend your understanding.
Once you've crunched your data, you'll want to visualize it, which is where matplotlib comes in. Matplotlib is a versatile 2D plotting library that allows you to generate plots, histograms, power spectra, bar charts, error charts, scatter plots, and more with just a few lines of code.
Finally, we do a deep dive into the Python Data Analysis Library (Pandas), a powerful package for working with multi-dimensional datasets. Pandas' powerful data aggregation and reorganization capabilities, including support for labeling data along each dimension, missing values, and time series manipulations, have made Python an indispensable tool for data exploration and analysis.
SciPy: Python's Scientific Computing Ecosystem
This course provides an introduction to performing scientific computations in Python using high-level packages like SciPy, NumPy, and SymPy.
Object-Oriented Programming in Python
This course covers object-oriented programming (OOP) in Python, with a focus on what you need to know for scientific applications. With an example-driven approach and lots of exercises, we cover OOP from the ground up to enable you to create your own custom data types (classes).
Interfacing Python with Other Languages
This course will show you how to interface Python with code written in other languages, allowing you to complement the strengths of Python with the speed and performance of C, C++, and FORTRAN.
This course covers a number of useful Python tools and concepts that aren't necessary for getting started with the language, but are really valuable as your skills and needs progress.
* MATLAB is a registered trademark of The MathWorks, Inc.
For inquiries or to register call 512.536.1057
Discounts available for 3+ attendees; corporate training options are also available. Contact us or call 512.536.1057 for more information.
A 20% discount is available for academics at a degree-granting institution. Contact us at 512.536.1057 to register.
Programming experience in some language (such as C, VB, R, FORTRAN, or MATLAB®) is expected. Knowledge of calculus, statistics, signal and image processing, and optimization are all valuable but not required. Please contact us here or at (512) 536-1057 with any questions.
Participants will receive 30 days of Enthought Training on Demand Python Foundations Series access as part of the course
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