Target Audience for 55285A: Advanced Python

The 55285A: Advanced Python course is designed for experienced Python developers looking to deepen their knowledge in advanced programming, data handling, and software design.

Target audience for the course includes:

• Software Developers and Programmers with Python experience
• Data Scientists and Analysts looking to enhance data manipulation skills
• Database Administrators interested in Python for automation and data processing
• Data Engineers who want to improve their data pipeline scripting abilities
• Backend Developers aiming to refine their coding and debugging practices
• DevOps Engineers who use Python for scripting and automation tasks
• IT Professionals needing advanced Python skills for system optimization
• Software Architects designing complex systems with Python
• Quality Assurance Engineers focused on test automation in Python
• Technical Leads and Managers overseeing Python projects
• Academic Researchers utilizing Python for complex data analysis

Learning Objectives - What you will Learn in this 55285A: Advanced Python?

1. Introduction: The Advanced Python 55285A course deepens your understanding of complex Python features, enhancing your programming, data handling, and software development skills to an expert level.

2. Learning Objectives and Outcomes:

• Master the use of lambda functions for creating anonymous, inline functions to simplify code readability and maintenance.
• Employ advanced list comprehensions for more efficient data processing and manipulation within lists.
• Utilize the Collections Module to implement specialized container datatypes, optimizing data organization and retrieval.
• Implement mapping and filtering to transform and filter data collections without the need for explicit loops.
• Understand the distinction between mutable and immutable objects in Python and their implications for data stability and performance.
• Learn advanced sorting techniques, including custom sorting logic, to effectively organize complex data structures.
• Apply sequence unpacking in function calls to improve code clarity and parameter management.
• Manage and manipulate data using Python's SQLite database integration for robust and scalable data-driven applications.
• Develop testing and debugging strategies using the unittest module, ensuring code reliability and performance optimization.
• Design and manage classes and objects, including inheritance, abstract classes, and decorators, to create well-structured, reusable, and scalable code bases.