Modern linear algebra using Python instead of a textbook
This course provides an introduction to modern linear algebra using Python instead of a textbook. It covers topics such as matrices in Python using sympy, matrix arithmetic, LU decomposition, inverse of a matrix, and null space of a matrix. It also includes a tutorial on ordinary least squares. Students will gain a comprehensive understanding of linear algebra and its applications in Python. ▼
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Course Feature
Cost:
Free
Provider:
Youtube
Certificate:
Paid Certification
Language:
English
Start Date:
On-Demand
Course Overview
❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [February 21st, 2023]
Linear algebra using sympy.
Matrices in python using sympy.
Matrix arithmetic using sympy.
LU decomposition of a matrix using sympy.
Inverse of a matrix.
Null space of a matrix using sympy.
Ordinary Least Squares Tutorial using Python.
Gram Schmidt process for QR decomposition using Python.
Basics of the Jacobian and its use in a neural network using Python.
(Please note that we obtained the following content based on information that users may want to know, such as skills, applicable scenarios, future development, etc., combined with AI tools, and have been manually reviewed)
This course provides an introduction to modern linear algebra using Python instead of a textbook. Learners will gain an understanding of matrices in Python, matrix arithmetic, LU decomposition, inverse of a matrix, null space, ordinary least squares, QR decomposition, Jacobian and its use in a neural network.
Possible Development Paths include furthering their knowledge in linear algebra, mathematics, computer science, and data science. Learners can also apply their knowledge to develop algorithms, build machine learning models, and create data visualizations.
Learning Suggestions for learners include studying linear algebra, calculus, and statistics. Learners should also become familiar with Python programming and libraries such as NumPy, SciPy, and Matplotlib. Additionally, learners should practice coding and problem solving to gain a better understanding of the concepts.
[Applications]
Students who have completed this course can apply their knowledge of linear algebra using Python to a variety of tasks. They can use Python to solve linear equations, calculate matrix arithmetic, decompose matrices, calculate the inverse of a matrix, and calculate the null space of a matrix. They can also use Python to perform the Ordinary Least Squares Tutorial, the Gram Schmidt process for QR decomposition, and the basics of the Jacobian and its use in a neural network.
[Career Paths]
1. Data Scientist: Data Scientists use linear algebra to analyze large datasets and uncover patterns and trends. They use Python to develop algorithms and models to interpret data and make predictions. With the increasing availability of data, the demand for Data Scientists is growing rapidly.
2. Machine Learning Engineer: Machine Learning Engineers use linear algebra to develop algorithms and models that can learn from data and make predictions. They use Python to develop and optimize machine learning models and algorithms. As machine learning becomes more widely used, the demand for Machine Learning Engineers is expected to grow.
3. Artificial Intelligence Engineer: Artificial Intelligence Engineers use linear algebra to develop algorithms and models that can learn from data and make decisions. They use Python to develop and optimize AI models and algorithms. As AI becomes more widely used, the demand for Artificial Intelligence Engineers is expected to grow.
4. Quantitative Analyst: Quantitative Analysts use linear algebra to develop algorithms and models that can analyze financial data and make predictions. They use Python to develop and optimize quantitative models and algorithms. As financial markets become more complex, the demand for Quantitative Analysts is expected to grow.
Course Provider
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