Python for Computer Science Exam: Solving Tasks 24 and 25

Preparing for advanced computer science exam problems requires a solid grasp of key algorithms and clean code practices. This course guides you through solving complex string processing and number theory problems using Python. You will start with core terminology, standard library functions, and mathematical fundamentals before moving on to step-by-step logic and practical code examples. What you'll learn: Understand key concepts of string parsing, pattern matching, and substring search; Master divisor search algorithms, prime factorization, and numerical filters; Apply clean Python idioms, built-in functions, and type hints for readable code; Identify and avoid common logical edge cases and performance bottlenecks; Practice writing efficient loops and condition checks for optimized execution. The content begins with foundational theory and standard problem-solving strategies, followed by practical written walk-throughs of typical exam patterns. Designed for students and beginners looking to strengthen their Python skills for exam preparation, no prior advanced algorithmic knowledge is required. Read through the lessons to build your problem-solving confidence and master these key exam tasks.