Algorithms for Data Science | Data Science Algorithms Course

Explore a wide range of algorithms and data structures relevant to data science, including Count-Min Sketch, Bloom Filters, and DGIM Algorithm. Gain a solid foundation in the algorithmic aspects of data science.

Introduction

This course covers various algorithms and data structures that are useful for data science applications. It includes topics such as Count-Min Sketch, Bloom Filters, Hashing, Frequency Moments, and DGIM Algorithm.

Highlights

• Covers a wide range of algorithms and data structures relevant to data science
• Provides in-depth understanding of the theoretical foundations and practical applications of the covered topics
• Includes video recordings and slides for each lecture
• Offers useful references and additional resources for further learning

Recommendation

This course is recommended for students and professionals interested in data science, algorithms, and the application of advanced data structures. It provides a solid foundation in the algorithmic aspects of data science and equips learners with the necessary tools and techniques to tackle real-world data challenges.