Mastering Algorithms and Data Structures in Python

Overview

This path will teach you some of the key foundational skills in computer programming often required in technical interviews. It will focus on understanding how to choose optimal algorithms and data structures for different problems, how to apply them, and how to explain their reasoning.

Syllabus

Course 1: Hashing, Dictionaries, and Sets in Python
Course 2: Sorting and Searching Algorithms in Python
Course 3: Linked Lists, Stacks, and Queues in Python
Course 4: Understanding and Using Trees in Python
Course 5: Mastering Graphs in Python

Courses

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3 hours
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Dive into Hashing, Dictionaries, and Sets in Python with this focused course, covering implementation, real-world applications, and algorithmic problem-solving. Gain practical experience to confidently tackle data analysis and management challenges.
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4 hours
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This is an in-depth course designed to instill foundational and advanced knowledge of sorting and searching algorithms. The course navigates through various types and functionality of these algorithms, their complexity analysis, and practical application in solving complex coding problems.
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3 hours
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This course dives into the understanding and application of basic data structures including Linked Lists, Stacks, and Queues. It sheds light on the inner workings of these structures, their implementation, time, and space complexity, along with their effectiveness in solving interview-focused algorithmic coding challenges.
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3 hours
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This course is designed to provide a deep understanding of trees in Python with a specific focus on binary trees, binary search trees, and heaps. The course covers the BFS and DFS in non-binary trees to elaborate on the different traversal methods. It extensively draws attention to the use of tree data structures in solving complex interview problems.
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3 hours
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This course is designed to demonstrate the representation of a graph using adjacency graphs and adjacency matrices in Python. A core part of the course is dedicated to implementing and utilizing BFS and DFS algorithms in graphs. Explore the comprehensive use of graph data structures in solving intricate interview-based algorithmic problems.