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Python has a fantastic array of modules that are useful to data scientists. Easily enabling data processing, modelling, linear algebra and much more. Python has rich data visualization capabilities, fast numerical methods, statistical and data analysis tools and machine learning libraries.

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
  • Analyze data
  • Create amazing visualizations
  • Interact with Power BI
  • Introduce machine learning

Base Cost


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  I will book and pay 10 business days before the course (less $55.00)


If you are currently resident in South Africa you will need to pay VAT at 15%.


2 Days


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Information may change without notice.

Delivery Method

Instructor Led classroom based training. Scheduled classes are normally held in Woodmead - near to Sandton in Johannesburg, Gauteng, South Africa. Stationary and textbook included. Refreshments, including 2 tea breaks and a cooked meal for lunch are provided. Contact hours are between 9am to 4pm.


Would be data scientists, scientists, engineers, data analysts.


Introduction to programming using Python or equivalent knowledge.  See

Course Outline / Curriculum

Symbolic Math (symy)



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)


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


Visualising matrix data

3D Plots



Numerical Methods (scipy)


Numerical integration

Solving ordinary differential equations

Finding roots using the bisection and fsolve method

Fast Fourier Transforms

Interpolation and curve fitting, including Linear regression

Intro to Machine Learning

Predictive models

Supervised Learning, Naive Bayes, Decision Trees, Random Forests.

Unsupervised Learning



Schedule Dates and Booking

To apply for a booking, click on the relevant "Book Now" button below.
Note: places are only fully secured once payment has been made.

Start Date Branch Duration  
Mon 23 Mar 2020 Woodmead 2 Days
Mon 29 Jun 2020 Woodmead 2 Days
Mon 28 Sep 2020 Woodmead 2 Days