Course overview
In this course, we cover Python packages that are commonly used for data analysis. These packages include handling CSV files, Numpy (‘Numerical Python’), SciPy (used for scientific and technical computing) and Pandas (data analysis library).
Campus locations
What you'll learn
- You would learn to code and execute simple data analysis programs in Python
- Learn to use powerful extensions available in Python
- You would learn to manipulate large and varied datasets by getting hands-on, practical experience working on real-life data problems on anonymised datasets
- You would gain a working knowledge of a few of the most commonly used Python modules, used by data scientists
Study method
- In-class
- Blended
- Online
Locations
- England
- London
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Duration study load
- 2 Days
Course features
- Python data course certificate on completion (assessment based)
- Python data course notes
- Practical python data course exercises, Python data course homework/python data course revision work
- To assist after the course, 1 free session for questions online python data course via Skype or Teamviewer
- Max group size on this python data course is 4
Who's it for?
The course is useful for professionals who anyone who use data as part of their work and who need to draw analysis from the data. It is best to have an understanding of programming already.
Subjects
What are ‘modules’ and how can they be useful for data analysis tasks.
Reading and writing CSV files into a Python program: The CSV module.
Identifying and fixing errors in datasets.
Pandas: Indexing, Iteration, Functions, aggregation, merge/join. Comparison with SQL.
The Python NumPy Module: Working with arrays, array manipulation, string, math, arithmetic and statistical functions.
Introduction and overview of SciPy.
About PCWorkshops
PCWorkshops mission is to be an integral partner to companies who up-skill and cross-skill their software and data staff.
We are based in London, Milton Keynes, Southend-On-Sea, Birmingham, Portsmouth and Manchester.
Our clients are in a variety of industries, e.g. e-commerce companies,
finance companies, insurance companies, software and technology companies and more.
