This is a course for data analysts, quants, statisticians, software developers, and other technical staff interested in learning to use Python for analysing and visualising data and performing powerful predictive analytics.
Some familiarity with programming concepts (in any language) is assumed.
By the end of the course, you will have all the knowledge you need to start using Python competently for processing, analysing, modelling, and visualising various kinds of data, with a focus on time series. You will have had experience with using Python for various scripting, data-manipulation and plotting tasks with data in a variety of formats, including CSV, Excel spreadsheets, SQL databases, JSON, and API endpoints. You will have applied powerful tools for optimisation, regression, classification, and clustering, in useful practical settings on a variety of data sets. You will understand the elegance and power of the Python language and its powerful ecosystem of packages for data analytics, and you will be well-placed to continue learning more as you use it day-to-day.
Day 1 covers how to use Python for basic scripting and automation tasks, including tips and tricks for making this easy. The syllabus is as follows:
The Pandas package is an amazingly productive tool for working with and analysing data in Python. Day 2 gives a thorough introduction to analysing data with Pandas and visualising it easily:
Day 3 demonstrates more advanced features of Pandas for working with data, including time-series data. It then describes Monte Carlo simulation methods and walks you through using powerful Bayesian methods of inference and modelling for different kinds of data in Python:
Day 4 introduces a more automated approach to modelling real-world data with several powerful machine learning algorithms using scikit-learn. The datasets are selected from a range of industries: financial, geospatial, medical, and social sciences. The syllabus is:
We will supply you with printed course notes and a USB stick containing a complete Python environment based on VirtualBox. This saves time in the course and allows us to focus on using Python rather than installing it. The USB stick also contains kitchen-sink Python installers for multiple platforms, solutions to the programming exercises, several written tutorials, and reference documentation on Python and the third-party packages covered in the course.
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