About the course:
Our instructor-led Python Data Analysis training course covers an introduction to the core concepts of the Python language, ultimately focusing on Big Data Analytics including how to best manipulate and visualise your data with Python's excellent library support.
This data analytics course is intended for Data Scientists, Data Analysts and Business Intelligence professionals who want to understand how to use Python tools to improve data handling capabilities; it's also suitable for Python developers who are looking to move into Data Science.
Practical exercises and interactive walkthroughs are used throughout, so attendees have the opportunity to apply the proposed concepts on real Data Science applications, from exploratory data analysis to predictive analytics.
You can save money if you purchase this course in conjunction with our Machine Learning with Python course - see the Python Data Science combined training course for details and to book.
By the end of this course, you will have learnt about:
- Anaconda, conda and Jupyter
- Python data analytics tools: NumPy and Pandas
- Data cleaning and preparation
- Data Analysis
- Data Visualisation
Who should attend
Analysts, Data Scientists, and software developers who want to get a practical introduction to Data Science and Machine Learning with Python.
Prerequisites
Delegates should ideally have some prior experience programming and / or of using statistical analysis techniques. Any experience with Python would be beneficial but we will give you "just enough" Python pointers to be able to create real-world workable solutions to data analysis challenges.
Live, instructor-led online and on-site training
We appreciate that you need flexibility to fit in with new working situations - whether you're an individual, part of a distributed team, or simply have projects and deadlines to meet.
Our remote training can take place online in a virtual classroom, with content split into modules to accommodate your scheduling challenges and meet your learning goals. Get in touch today to find out how we can help design a cost-effective, flexible training solution.
As soon as it's safe, we'll return to also offering the on-site custom training courses and programmes upon which we've built our reputation.
Environment Set-up
- The Anaconda distribution as Python Data Science platform
- Overview on Python virtual environment set-up
- Running code in Jupyter notebook
Data Analysis with Python:
Python core concepts
- Core data types in Python
- Control flow statements
- Defining and using custom functions
- The Python standard library
- Working with data:
- Iteration and list comprehensions
- Accessing raw data on file (CSV, JSON, ...)
- Working with dates and times
- Basics of Object-Oriented Programming in Python
Python Data Science libraries
Numpy:
- Working with NumPy arrays
- Essential operations with NumPy arrays
- Stats and linear algebra with NumPy
pandas:
- Working with table-like data in pandas
- Essential operations with Series and DataFrame object
- Loading data from file into DataFrame objects
- Summary statistics over DataFrame objects
- Data aggregation queries (groupby() method)
- Exploratory analysis of new datasets
- Data visualisation over DataFrames
- Join/merge operations with DataFrames
- Working with text data in DataFrames
- Working with Time Series data
Databases:
- Working with relational databases in Python
- Overview on SQLAlchemy for database interaction
- Integration of pandas and SQL