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Updated in [March 06th, 2023]

From simulating complex phenomenon on supercomputers to storing the coordinates needed in modern 3D printing, data is a huge and growing part of our world. A major tool to manipulate and study this data is linear algebra. This course is part 1 of a 2-part course. In this part, we'll learn basics of matrix algebra with an emphasis on application. This class has a focus on computer graphics while also containing examples in data mining. We'll learn to make an image transparent, fade from one image to another, and rotate a 3D wireframe model. We'll also mine data; for example, we will find similar movies that one might enjoy seeing. In the topic of sports ranking, we'll be ready to participate in March Madness and submit our own mathematically generated brackets to compete against millions of others. The lectures are developed to encourage you to explore and create your own ideas either through your own programming but also with online tools developed for the course. Come to this course ready to investigate your own ideas.

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Unlock the Exciting World of Learning! Here's What Awaits You: This course provides an introduction to linear algebra and its applications. Learners will gain an understanding of the basics of matrix algebra and how it can be used to manipulate and study data. Through the course, learners will explore computer graphics, data mining, and sports ranking. They will also learn how to make an image transparent, fade from one image to another, and rotate a 3D wireframe model. Additionally, learners will be able to participate in March Madness and submit their own mathematically generated brackets to compete against millions of others. This course encourages learners to explore and create their own ideas through programming and online tools.

[Applications]
Upon completion of this course, students will have a better understanding of the applications of linear algebra. They will be able to use matrix algebra to manipulate and study data, as well as create images and mine data. Students will also be able to use their knowledge to participate in March Madness and submit their own mathematically generated brackets. Additionally, students will be able to explore and create their own ideas through programming or online tools.

[Career Paths]
1. Data Scientist: Data Scientists use linear algebra to analyze and interpret large datasets. They use linear algebra to identify patterns and trends in data, and to develop predictive models. As data becomes increasingly important in the modern world, the demand for Data Scientists is growing rapidly.

2. Computer Graphics Engineer: Computer Graphics Engineers use linear algebra to create and manipulate 3D models and images. They use linear algebra to create realistic images, to animate objects, and to create virtual reality experiences. As the demand for more realistic and immersive experiences increases, the demand for Computer Graphics Engineers is expected to grow.

3. Machine Learning Engineer: Machine Learning Engineers use linear algebra to develop algorithms that can learn from data. They use linear algebra to create models that can identify patterns and make predictions. As machine learning becomes increasingly important in the modern world, the demand for Machine Learning Engineers is expected to grow.

4. Data Analyst: Data Analysts use linear algebra to analyze and interpret large datasets. They use linear algebra to identify patterns and trends in data, and to develop predictive models. As data becomes increasingly important in the modern world, the demand for Data Analysts is expected to grow.

[Education Paths]
1. Bachelor's Degree in Mathematics: A Bachelor's Degree in Mathematics is a great way to gain a comprehensive understanding of linear algebra and its applications. This degree will provide students with the skills and knowledge to apply linear algebra to a variety of fields, such as computer science, engineering, and finance. Students will learn the fundamentals of linear algebra, including matrix operations, vector spaces, and linear transformations. They will also learn how to use linear algebra to solve real-world problems. As technology continues to advance, the demand for mathematicians with a strong understanding of linear algebra is expected to increase.

2. Master's Degree in Computer Science: A Master's Degree in Computer Science is a great way to gain a deeper understanding of linear algebra and its applications in computer science. This degree will provide students with the skills and knowledge to apply linear algebra to a variety of computer science topics, such as machine learning, artificial intelligence, and computer graphics. Students will learn the fundamentals of linear algebra, including matrix operations, vector spaces, and linear transformations. They will also learn how to use linear algebra to solve real-world problems in computer science. As technology continues to advance, the demand for computer scientists with a strong understanding of linear algebra is expected to increase.

3. Master's Degree in Data Science: A Master's Degree in Data Science is a great way to gain a comprehensive understanding of linear algebra and its applications in data science. This degree will provide students with the skills and knowledge to apply linear algebra to a variety of data science topics, such as data mining, predictive analytics, and data visualization. Students will learn the fundamentals of linear algebra, including matrix operations, vector spaces, and linear transformations. They will also learn how to use linear algebra to solve real-world problems in data science. As data continues to grow in importance, the demand for data scientists with a strong understanding of linear algebra is expected to increase.

4. Doctoral Degree in Applied Mathematics: A Doctoral Degree in Applied Mathematics is a great way to gain a comprehensive understanding of linear algebra and its applications in applied mathematics. This degree will provide students with the skills and knowledge to apply linear algebra to a variety of applied mathematics topics, such as numerical analysis, optimization, and dynamical systems. Students will learn the fundamentals of linear algebra, including matrix operations, vector spaces, and linear transformations. They will also learn how to use linear algebra to solve real-world problems in applied mathematics. As technology continues to advance, the demand for applied mathematicians with a strong understanding of linear algebra is expected to increase.