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Course Outline

1. Installation & Environment

  • Introduction to Python 3 (differences from Python 2)
  • Python 3.14 new features
  • Installing Python, PIP, UV
  • Installing libraries
  • Compilation vs Interpretation

2. Basic Syntax

  • PEP conventions
  • Data types: bool, int, float, complex, str
  • Variables and scope
  • f-strings and t-strings (3.14)
  • Conditional structures (if, match case)
  • Loops: for, while, break/continue
  • Writing and documenting functions

3. Data Structures

  • list, dict, set
  • tuple, frozenset
  • range
  • Lambda expressions
  • Generators

4. File Manipulation

  • txt, csv, json
  • Serialization / Deserialization
  • Accessing relational databases

5. Organization & Best Practices

  • Error handling
  • Module structuring
  • PEP best practices

6. Using the Standard Library

  • Command-line arguments
  • re module (regex)
  • sys, os, os.path modules

7. Object-Oriented Programming

  • Key concepts: classes, objects, encapsulation
  • APHE (Abstraction, Polymorphism, Inheritance, Encapsulation)
  • UML and diagrams
  • SOLID principles
  • Introduction to Design Patterns
  • Professional best practices

8. Quality Assurance (QA)

  • Static analysis: Pylint
  • Logging and message levels
  • Step-by-step debugging
  • Unit testing: unittest, pytest
  • Test automation and aggregation
  • Code coverage
  • Profiling

9. Final Project

  • Capstone project integrating all concepts
  • Clean and modular architecture
  • Automated tests
  • Presentation and code review

Requirements

  • Understanding of algorithms:  loops, conditions, data structures.
  • Experience with another programming language (Java, C++, JavaScript, etc.) to facilitate learning.

Target Audience

  • Developers and Software Engineers
  • Technicians
  • Data Scientists, Analysts, and Researchers
  • Technical Project Managers, Software Architects
 35 Hours

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