Computer Programming
11792 learners
Maximized Efficiency in Problem Solving Techniques in Python
This comprehensive course incorporates unique problem-solving approaches and analyzing techniques that extend beyond core programming. Topics include optimizing brute force methods, dealing with combinatorial problems, and utilizing heaps and sorted lists effectively.
Python
See path
5 lessons
15 practices
3 hours
Badge for General Programming and Algorithms,
General Programming and Algorithms
Lessons and practices
Lesson 1: Estimating Algorithm Processing Time and Optimizing Brute-Force Solutions by Picking Optimal Variable for Brute Force
Finding a Pair with Target Sum Using Hashmap Optimization
Player Score Lookup Through ID Queries
Finding Pair Sums in Two Arrays
Lesson 2: Optimizing Range Query Solutions with Precalculation Techniques
Maximal Cumulative Sum in Array for Given Queries
Finding the Length of a Substring After Removing Certain Characters
Finding Divisors of the Closest Perfect Square
Lesson 3: Combinatorial Pair Analysis in Large Datasets
Counting Distinct Pairs with Absolute Difference More Than 10
Counting Pairs with Equal Values in an Array
Three-Letter Combination Count from String
Lesson 4: Efficient Median Calculation for Array Prefixes Using Heaps
Implementing Heap Operations on a Set of Numbers
Heap Manipulation for Data Querying
Finding the floor(k/3)-th Smallest Number in Each Prefix
Lesson 5: Efficient Set Operations with Sorted Data Structures
Finding Smallest Absolute Distance Between Added Numbers
Managing Operations on A Sorted List
Interval Management with SortedLists in Python
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