Highlights
Python Training:
Click here for Python for Data Analysts training course
- Python History & content overview
- Gain an introduction to Python from its origins
- Learn about Python techniques and features
- Apply Basic Data types to integers, floating points, and strings
- Learn how to use Python aggregated types to manage large data sets
- Gain an understanding of Flow Control for code layout and clarity
- Discover how to make decisions with the IF statement
- Use Python functions for parameters and variables
- Acquire knowledge of functional programming
- Modularise code to write and use larger Python programs
- Master how to improve your code robustness by handling exceptions
- Take advantage of file handling to manipulate text and binary files
- Implement Agile and test-driven development methods to write clean and readable Python code
- Apply powerful text processing with regular expressions
- Gain an overview of Object-Oriented Programming with classes
- Acquire knowledge of classes to help with dynamic typing and code re-usability
Course Details
Python Training & Features
- Ease and economy of development
- Scalability
- Extensibility
- Adoption by major users
- Intro to Python core concept in initial Training session
Introduction to Python
- Python history
- Interactive and scripted execution
- Dynamic typing examples and uses
Basic Data Types
- Arithmetic on integers and longs
- Overflow-free arithmetic
- Using floating point for fractional values
- Using Decimal for precise decimal calculations
- Strings: indexing, slicing and formatting
Python aggregated types
- Lists and tuples: accessing information by position
- Modifying and appending to lists by index or slice
- Operations on lists: comparison and sorting
- List comprehensions for more compact code
- Managing large data sets with generators
Python Training for Flow Control
- Making decisions with the if statement
- Python code layout and clarity
- Iterating with the for and while constructs
- Writing your own iterators and generators
Python Functions Training
- Parameters: positional, named and, default arguments
- Variable-length argument lists
- Functional programming: functions as arguments and return values
- Using lambda functions to simplify code
Larger Programs and Modularisation
- Writing Python modules to modularise code
- Using the import statement to use Python modules
- Customising the import search path
- Grouping modules into packages
Improving code robustness by handling exceptions
- The importance of avoiding unhandled errors
- Using the try/except/else and finally construct
- Raising exceptions
- Using custom exceptions for a better user experience
File handling
- Opening files for read and/or write
- Managing file handles correctly
- Reading and writing text and binary files
- Performing random access
Agile and Test Driven development
- Improving code quality and delivery with unit testing
- Th Python unit testing libraries
- Using unittest, PyTest, Doctest
- Using umbrella test classes to integrate different testing approaches
Powerful text processing with regular expressions in Python
- Expressing powerful abstract text patterns with metacharacters
- Using capturing to extract patterns from text
- Substituting text patterns with fixed or dynamic replacement patterns
Object oriented programming with classes
- Understanding the power of OOP using abstract data types
- Defining abstract data types using classes
- Writing class member and static functions
- Understanding the class and object structure
- Exploiting Python’s dynamic class and object behaviour
More on classes in Python Training
- Using inheritance for code reusability
- Further enhancing reusability through polymorphism
- Using Python dynamic typing to change types at run time
- More on Python Training
Pre-Course technical chat and analysis for all Python Training courses
Who should attend
Whether you're a total beginner looking to learn your first programming language, or an experienced coder trying to expand your skills, Python is versatile enough to help. This includes Quants, Data Scientists, Data Analysts, Mathematicians, System Testers and Shell Scripters.
With Python's usefulness for data science, ML, web apps, and more, our course can get you up to speed or enhance your abilities, no matter your industry.
Feedback
4.8 out of 5 average
"The instructor genuinely cared about our learning. We felt supported from start to finish and left with knowledge that truly mattered to our work" Brian Leek, Data Analyst, May 2023