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.
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
Interested in this course? Learn and practice with Cosmo!
Practice is how you turn knowledge into actual skills.