Details
Python has a fantastic array of modules that are useful to both scientists and engineers. Easily enabling data processing, modelling, linear algebra and much more. Tools that allow immediate data visualization are particularly helpful.
In this course you will learn how to:
- Perform complex maths in Python
- Solve mathematical equations symbolically using python
- Use numerical methods to find solutions to mathematical problems
- Perform simulations
Delivery Methods
| Delivery Method | Duration | ||
|---|---|---|---|
| 2 Days | Get a Quote | ||
| 2 Days | Get a Quote |
Discounts Available
Save up to 10% by booking and paying 10 business days before the course.
Brochure:
Audience
Scientists, Engineers, data scientists.
Pre-Requisites
Python programming
Course Outline / Curriculum
Symbolic Math (symy)
Symbols
isympy
Numeric types
Differentiation and Integration
Ordinary differential equations
Series expansions and plotting
Linear equations and matrix inversion
Non linear equations
Output: LATEX interface and pretty-printing
Numerical Python (numpy)
Introduction
Arrays (Matrices)
Convert from array to list or tuple
Standard Linear Algebra operations
Numpy for Matlab users
Visualising Data
Matplotlib 2D plotting
Matplotlib and Pylab
pyplot, numpy
Fine tuning your plot
Plotting more than one curve
Histograms
Visualising matrix data
3D Plots
Visual Python
Basics, rotating and zooming
Setting the frame rate for animations
Tracking trajectories
Connecting objects (Cylinders, springs, 3d vision)
Visualising higher dimensional data
Numerical Methods (scipy)
Overview
Numerical integration
Solving ordinary differential equations
Finding roots using the bisection and fsolve method
Fast Fourier Transforms
Interpolation and curve fitting
Simulations (simpy)
Schedule Dates and Booking
There are currently no scheduled dates.