- familiarity with basic programming concepts (variables, loops, conditionals, etc.)
We want our workshops to be accessible to everyone who wants to learn the principles of data science. After receiving a lot of incredible feedback for the first event, we have decided to organise a supplementary scientific Python workshop. During a two hour event you will be working in small groups and learn the essentials of Numpy, Pandas, Matplotlib and Scipy. If you are just getting started with the scientific Python stack, this is the perfect learning opportunity! Attending this workshop will equip you with the skills necessary to follow our future machine learning oriented events easily.
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Introuduction to Numpy
- array creation
- indexing and shapes
- mathematical operations and broadcasting
- basic linear algebra
- data types
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Introduction to Matplotlib
- plotting data
- titles, legends and labels
- subplots and the object-oriented interface
- displaying images
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Optimization with Scipy
- linear regression with Scipy
- Numpy and Matplotlib tutorial from Stanford
- The official documentation for Numpy, Scipy and Matplotlib
- Numpy exercises to practice the concepts covered in this workshop
- Quantopian's introduction to Numpy (more finance-oriented)
- A tutorial on indexing, slicing and reshaping Numpy arrays
- Scipy cookbook for examples of more advanced Scipy applications
- Seaborn for more advanced visualizations with Matplotlib