Algorithmic Thinking (Part 2)

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Algorithmic Thinking (Part 2)

Coursera · Beginner ·⚡ Algorithms & Data Structures ·3mo ago

Key Takeaways

Develops algorithmic thinking for computational problem-solving

Original Description

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems. In part 2 of this course, we will study advanced algorithmic techniques such as divide-and-conquer and dynamic programming. As the central part of the course, students will implement several algorithms in Python that incorporate these techniques and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms. Once students have completed this class, they will have both the mathematical and programming skills to analyze, design, and program solutions to a wide range of computational problems. While this class will use Python as its vehicle of choice to practice Algorithmic Thinking, the concepts that you will learn in this class transcend any particular programming language.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
KMP Algorithm (Knuth-Morris-Pratt): The Smart Way to Perform String Matching in O(N)
Learn the KMP algorithm for efficient string matching in O(N) time complexity and improve your coding skills
Dev.to · Jaspreet singh
📰
Every Backtracking Problem Is the Same Three Lines. I Just Couldn't See the Tree.
Master backtracking problems with a simple three-line approach to improve problem-solving skills in coding interviews and challenges
Dev.to · Alex Mateo
📰
DSA From Zero to Hero #3: Sliding Window (Fixed Size) Explained With a Java Example
Learn to solve subarray problems efficiently using the sliding window technique, a crucial skill for software engineers and data scientists
Medium · Programming
📰
Two Pointers & Sliding Window: Turn O(n²) Into O(n)
Learn to optimize algorithms from O(n²) to O(n) using Two Pointers and Sliding Window techniques
Medium · Programming
Up next
Stump Grinder Carbide Wheel Grinds Hardwood To Chips
Innoforge Studio
Watch →