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Explore the fundamentals of Python for data science in this 33-minute lecture by CTO and data strategist Boyan Angelov. Gain insights into essential tools and libraries used in data science and engineering, covering topics such as data processing, feature engineering, visualization, modeling, and evaluation. Learn through a real-world case study to understand end-to-end data science and engineering processes. Discover key concepts including data product requirements, system design, and product development. Participate in hands-on exercises and access additional resources to further your learning. This lecture is part of a comprehensive series by Data Science Dojo, aimed at making data science accessible to everyone.
Syllabus
Introduction
What is a Data Product
Data Product Requirements
Closing the Loop
Natural Language Tool Kit Demo
Basic System Design
Product Development
Exercise I
Exercise II
Resources
Closing Remarks
Taught by
Data Science Dojo