You will be able to write a complex several hundred line program that works as intended (and is also readable!). Writing a program of this length is good practice for ensuring that you can split programs into multiple files using constructs such as modules, classes and functions. You’ll leave with a substantive project that can be demonstrated to potential future or current employers.
We firmly believe in classroom-based study versus online learning, because it ensures your teacher is always on-hand to help you with the challenges you encounter.
Furthermore, we teach through projects selected by you, allowing you to choose the direction of your learning at a pace that suits you.
Our teachers are Data Scientists and Python programmers.
They come with years of commercial experience –
Priyesh is a Step Function Python teacher and works full-time as a Data Scientist at Collinson Group. Priyesh has a Nuclear Engineering Doctorate form Imperial College, where he also worked as a Post-Doc developing Python based modelling tools.
Priyesh was a student on the Step Function Data Science Professional course in the summer of 2017.
“The teacher was very knowledgeable with the potential to take students far. I enjoyed the exercises and projects, which gave a tangible feeling of what one can do with Python in the real world.”
IOANA COMSA – February 2018 Course
“I just wanted to say I really enjoyed the classes… especially the machine learning component which is my real interest! The evening classes really suited my schedule.”
HAMILTON HINDS – April 2018 Python and Machine Learning Course
How to use the basic python constructs: lists, dictionaries, functions and objects, while adhering to pythonic principals and good software design guidelines.
We focus on learning these concepts more thoroughly than other introductory python courses by working through multiple exercises.
Covering Boolean values and expressions, operators, conditional statements and loops. All learning is reinforced through exercises.
Exception handling, raising errors and user-defined errors.
Master the core libraries of Python starting from scratch, e.g. datetime, csv, json, unittest.
Learn how to read from and write to csv files, facilitating automation of manual processes in the workplace.
Solid foundation in software management principles, how to design, manage and run software projects.
Including version control systems like Github, development environments in MacOS and windows and ipython.
We also introduce concepts related to using Amazon Web Services as a coding environment, which is an effective introduction to the principles of cloud computing.
Using 3rd party data services is a crucial skill not covered by most introductory python courses, yet it’s something you are expected to understand from day one in most python related roles.
We provide a hands-on demonstration and tutorial on using important API services such as Google Maps and IBM Watson.
You my choose to extend the 3 week course by 1 week to incorporate our Introduction to Machine Learning module:
Please note that the details of this Introduction to Python Course syllabus are accurate at the time of printing. There may be some variation in the final syllabus that is taught.
Step Function, January 2019