Build a strong foundation in algorithmic concepts, covering algorithms, asymptotic analysis, sorting, searching, and divide and conquer techniques.

Computer Science Bootcamp

Algorithms are step-by-step instructions or guidelines for solving specific problems or accomplishing specific tasks. Analyzing algorithms is important to understand their efficiency, scalability, and overall performance, thus enabling us to decide on their implementation and optimization. This module introduces us to algorithmic paradigms, asymptotic analysis, lists, sorting and searching algorithms, and techniques such as divide and conquer. We’ll start by discovering techniques like brute force, greedy algorithms, divide and conquer, and dynamic programming. Then, we’ll learn to analyze algorithms using asymptotic notations, focusing on Big O and solving challenges like removing even integers, merging sorted lists, and finding minimum values. By the end of this module, we will have gained expertise in sorting and searching algorithms, like selection sort, merge sort, and binary search, and applied the divide and conquer technique to solve challenges, like finding peak elements and missing numbers.

Fundamental Algorithms in Python

Here’s a quick summary of what we learned from the “Fundamental Algorithms in Python” module.

Algorithmic Paradigms

Asymptotic Analysis

Introduction to Lists

Sorting and Searching

Divide and Conquer

Conclusion

Final Remarks

Summary