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Advanced Coding Interview Preparation with Python

Software Engineering

5 courses

87 practices

18 hours

This rigorous learning path extends your Python programming proficiency from intermediate to advanced level. It's dedicated to refine your knowledge and application of sophisticated algorithms, complex data structures and efficient implementation strategies.

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Verified skills you'll gain

INTERMEDIATE

Debugging and Troubleshooting

ADVANCED

General Programming and Algorithms

Tools you'll use

Python

Course 1

Multidimensional Arrays and Their Traversal in Python

5 lessons

25 practices

Brush up on your knowledge of multidimensional arrays and their traversal techniques. This course will equip you with the skills to manipulate multidimensional arrays, transposing rows and columns, and iterating over nested elements.

Course 2

Revision of Python HashMaps and Their Use in Practice

4 lessons

20 practices

Enhance your comprehension and use of hashmap data structures while focusing on its application in counting and aggregation tasks. This exploration will deepen your understanding of their efficient data access and manipulation capabilities.

Course 3

Master Splitting Advanced Tasks into Smaller Pieces with Python

4 lessons

12 practices

Learn how to break down complex tasks into manageable sub-tasks. This course will help you master the skills necessary to effectively structure, divide, and implement each part of advanced coding problems. You'll also focus on merging sub-task solutions into a cohesive whole.

Course 4

Master Dictionaries, Two Pointers, and More Algorithms in Python

5 lessons

15 practices

Delve into the essentials of optimal programming algorithms involving HashMaps, HashSets, and two-pointer techniques. Enhance your skills in data structure optimization and streamline problem-solving methods.

Course 5

Maximized Efficiency in Problem Solving Techniques in Python

5 lessons

15 practices

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.

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