July 2019
Intermediate
50m
English
Closed Captioning available in English
Overview
In this comprehensive video course, you will learn the essentials of linear algebra required for data science, focusing on Python implementations. Gain a deep understanding of operations with scalars, vectors, and matrices, and learn to use vectorization to improve computational efficiency.
What I will be able to do after this course
- Demystify foundational concepts such as scalars, vectors, and matrices in linear algebra.
- Perform common linear algebra operations efficiently using Python programming.
- Understand and interpret linear algebra concepts from a geometrical perspective.
- Identify and correct syntax errors often encountered when implementing linear algebra code in Python.
- Leverage linear algebra techniques to optimize your data science workflows and machine learning model performance.
Course Instructor(s)
The course is instructed by a data science professional with extensive experience in Python programming and mathematical applications to computational problems. With hands-on examples and a step-by-step teaching style, they'll equip you with the skills crucial for modern data analysis.
Who is it for?
This course is tailored for aspiring data scientists, analysts, and engineers who are beginning their journey in data science or enhancing their mathematical foundations. A basic understanding of Python programming is recommended, and a passion for exploring mathematical data processes is ideal. By the end, learners will optimize their analysis using linear algebra.
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