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超過 22 小時的超詳細線性代數課程，帶你一步步學會線性代數的重要觀念和公式，趕快收藏起來.
這門詳盡的線性代數課程將引領您深入瞭解多個主題，包括機器學習中的主成分分析（Principal Component Analysis, PCA）、Python 實作的圖像分析、馬可夫鏈、SVD分解、LU分解、QR分解、特徵值和特徵向量、施特拉森演算法、可逆矩陣的判斷以及Gershgorin圓定理。
線性代數為電腦科學、資訊工程等領域的必修課程，其應用之廣泛，包含機器學習、深度學習、預測模型、電腦圖形處理以及加密系統等等。這堂線性代數課程內容包含基本的線性方程組的基本運算、向量空間、線性獨立、矩陣的可逆性、行列式、線性轉換、還有特徵矩陣以及特徵值的尋找，一步一步帶你認識所有重要的觀念、證明、運算過程與題目解答。不論你的數學基礎為何，都可以有系統性的認識線性代數中的重要理論、公式與計算原理。所有課程中所提到的公式與定理皆有證明過程與對應例子，讓學習有紮實基礎！
另外，課程也包含線性代數在電腦科學中的應用，包含密碼學的加密與解密演算法、圖形與向量處理、2D旋轉壓縮移動矩陣、3D旋轉矩陣、主成分分析 (PCA) 等等。這堂課程也包含章節的練習題，讓你能夠衡量學習成效與得到充分練習的機會。
你應該要註冊這堂課的理由:
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超過 22 小時的超詳細線性代數課程，帶你一步步學會線性代數的重要觀念和公式，趕快收藏起來.
這門詳盡的線性代數課程將引領您深入瞭解多個主題，包括機器學習中的主成分分析（Principal Component Analysis, PCA）、Python 實作的圖像分析、馬可夫鏈、SVD分解、LU分解、QR分解、特徵值和特徵向量、施特拉森演算法、可逆矩陣的判斷以及Gershgorin圓定理。
線性代數為電腦科學、資訊工程等領域的必修課程，其應用之廣泛，包含機器學習、深度學習、預測模型、電腦圖形處理以及加密系統等等。這堂線性代數課程內容包含基本的線性方程組的基本運算、向量空間、線性獨立、矩陣的可逆性、行列式、線性轉換、還有特徵矩陣以及特徵值的尋找，一步一步帶你認識所有重要的觀念、證明、運算過程與題目解答。不論你的數學基礎為何，都可以有系統性的認識線性代數中的重要理論、公式與計算原理。所有課程中所提到的公式與定理皆有證明過程與對應例子，讓學習有紮實基礎！
另外，課程也包含線性代數在電腦科學中的應用，包含密碼學的加密與解密演算法、圖形與向量處理、2D旋轉壓縮移動矩陣、3D旋轉矩陣、主成分分析 (PCA) 等等。這堂課程也包含章節的練習題，讓你能夠衡量學習成效與得到充分練習的機會。
你應該要註冊這堂課的理由:
Read more
超過 22 小時的超詳細線性代數課程，帶你一步步學會線性代數的重要觀念和公式，趕快收藏起來.
這門詳盡的線性代數課程將引領您深入瞭解多個主題，包括機器學習中的主成分分析（Principal Component Analysis, PCA）、Python 實作的圖像分析、馬可夫鏈、SVD分解、LU分解、QR分解、特徵值和特徵向量、施特拉森演算法、可逆矩陣的判斷以及Gershgorin圓定理。
線性代數為電腦科學、資訊工程等領域的必修課程，其應用之廣泛，包含機器學習、深度學習、預測模型、電腦圖形處理以及加密系統等等。這堂線性代數課程內容包含基本的線性方程組的基本運算、向量空間、線性獨立、矩陣的可逆性、行列式、線性轉換、還有特徵矩陣以及特徵值的尋找，一步一步帶你認識所有重要的觀念、證明、運算過程與題目解答。不論你的數學基礎為何，都可以有系統性的認識線性代數中的重要理論、公式與計算原理。所有課程中所提到的公式與定理皆有證明過程與對應例子，讓學習有紮實基礎！
另外，課程也包含線性代數在電腦科學中的應用，包含密碼學的加密與解密演算法、圖形與向量處理、2D旋轉壓縮移動矩陣、3D旋轉矩陣、主成分分析 (PCA) 等等。這堂課程也包含章節的練習題，讓你能夠衡量學習成效與得到充分練習的機會。
你應該要註冊這堂課的理由:
課程教材適合所有程度的人，不論你的數學基礎為何，此課程由簡入深學習所有必要資訊與觀念.
課程涵蓋其他線性代數的補充與電腦科學應用。
學會用Geogebra軟體來輔助了解空間與矩陣運算。
Register for this course and see more details by visiting:
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What's inside
Syllabus
Chapter 0 - Course Preparation
Learning Tips
Course Resources
Chapter 1 - Linear Equations
Read more
Syllabus
Chapter 0 - Course Preparation
Learning Tips
Course Resources
Chapter 1 - Linear Equations
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
這門課程其中一個主題是廣泛應用的線性代數在電腦圖形處理中。
這門課程涵蓋了深入線性代數多個領域的主題，包含機器學習中的主成分分析（Principal Component Analysis, PCA）、Python 實作的圖像分析、馬可夫鏈、SVD分解、QR分解、特徵值和特徵向量、施特拉森演算法等內容。
課程包含章節的練習題，幫助衡量學習進度並得到充足的練習機會。
這門課程包含線性代數在電腦科學中的應用，包含密碼學的加密與解密演算法、圖形與向量處理、2D旋轉與壓縮移動矩陣等內容。
這門課程由淺入深，學習所有重要的線性代數觀念、證明、運算過程與題目解答。
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Reviews summary
線性代數應用導向詳解
根據課程描述，學習者會發現這門線性代數課程提供了超過22小時的超詳細內容，旨在一步步引導學生掌握重要觀念與公式。課程不僅涵蓋了紮實的理論基礎，所有公式與定理皆有證明過程與對應例子，還深度結合了電腦科學與資訊工程的廣泛應用，特別是機器學習中的主成分分析（PCA）和圖像分析。它強調適用於所有數學基礎的學生，並提供練習題與輔助工具如Geogebra，幫助學生衡量學習成效並視覺化抽象概念。
提供練習題和Geogebra軟體輔助，幫助鞏固學習效果。
"章節練習題讓我能即時衡量學習成效，並得到充分的練習機會。"
"Geogebra軟體的使用讓我能視覺化向量和矩陣運算，對理解空間概念很有幫助。"
"透過練習題，我能及時複習所學知識，加深印象。"
所有公式和定理都附有證明過程與對應例子，基礎穩固。
"課程中的每個公式和定理都有清晰的證明過程，幫助我建立紮實的數學基礎。"
"我能夠透過豐富的例子來理解抽象的數學概念，這讓學習變得容易許多。"
"講師在證明部分做得很好，不只教計算，也解釋了背後的原理。"
無論數學基礎如何，課程都能提供系統性的學習體驗。
"課程由簡入深，即使像我這樣數學基礎不強的人也能逐步理解。"
"我發現課程對所有必要資訊和觀念都做了詳細講解，讓學習過程非常順暢。"
"我很欣賞課程宣稱適合所有程度，且內容確實能幫助我從零開始學習線性代數。"
課程內容廣泛且深入，涵蓋線性代數核心與進階主題。
"這門課程涵蓋了線性代數的每一個重要主題，從基礎到高階，應有盡有。"
"我發現課程對每個觀念和公式都提供了超詳細的解釋，讓我能夠一步步掌握。"
"課程時長超過22小時，顯示了其內容的豐富性和深度，非常適合系統學習。"
將線性代數與電腦科學應用緊密結合，極具實用價值。
"課程將線性代數與機器學習、圖像分析等應用結合，讓我能將理論應用於實際。"
"我學習了主成分分析 (PCA)、密碼學與圖形處理，這些在資訊工程領域非常有用。"
"除了基礎理論，課程還展示了其在電腦科學中的廣泛應用，拓展了我的視野。"
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in 線性代數 (Linear Algebra) with these
activities:
尋找一位線性代數專家作為指導者
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找到一位優秀的指導者將提供額外的支持和指導，幫助你更深入地探索線性代數。
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詢問教授或助教推薦信
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參加相關活動或工作坊，認識潛在的指導者
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尋找一位線性代數專家作為指導者
Show steps
找到一位優秀的指導者將提供額外的支持和指導，幫助你更深入地探索線性代數。
Show steps
Show steps
Show steps
- 詢問教授或助教推薦信
- 參加相關活動或工作坊，認識潛在的指導者
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Career center
Learners who complete 線性代數 (Linear Algebra) will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists combine programming skills with statistical and mathematical knowledge to extract insights from data. They work with a variety of data sources and tools to identify trends, patterns, and relationships. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of data science. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy data science models.
Computer Scientist
Computer Scientist
Computer Scientists design, develop, and analyze computer systems and software. They work with a variety of programming languages and technologies to create solutions for a wide range of problems. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of computer science. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy computer science models.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. They work with a variety of machine learning algorithms and techniques to build models that can learn from data and make predictions. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of machine learning. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy machine learning models.
Mathematician
Mathematician
Mathematicians study the properties of numbers, shapes, and patterns. They develop new mathematical theories and techniques to solve problems in a variety of fields. This course will help you build a strong foundation in linear algebra, which is essential for understanding many areas of mathematics. By understanding the concepts in linear algebra, you will be better equipped to pursue a career in mathematics.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They work with a variety of data sources and tools to identify trends, patterns, and relationships. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of statistics. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy statistical models.
Risk Manager
Risk Manager
Risk Managers use mathematical and statistical models to assess risk and uncertainty. They work with a variety of data sources and tools to develop and implement risk management strategies. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of risk management. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy risk management models.
Engineer
Engineer
Engineers design, build, and maintain structures and systems. They work with a variety of materials and technologies to create solutions for a wide range of problems. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of engineering. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy engineering models.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. They work with a variety of data sources and tools to identify trends, patterns, and relationships. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of quantitative finance. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy quantitative finance models.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. They work with a variety of data sources and tools to develop and implement risk management strategies. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of actuarial science. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy actuarial models.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to optimize business processes. They work with a variety of data sources and tools to identify inefficiencies and develop solutions. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of operations research. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy operations research models.
Financial Analyst
Financial Analyst
Financial Analysts use mathematical and statistical models to analyze financial data and make investment decisions. They work with a variety of data sources and tools to identify trends, patterns, and relationships. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of financial analysis. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy financial analysis models.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to extract meaningful insights. Their work helps businesses make informed decisions about products, marketing, and operations. This course will build a strong foundation in linear algebra, which is essential for understanding data structures, algorithms, and statistical models. By understanding the concepts in linear algebra, you will be better equipped to analyze large datasets and draw meaningful conclusions.
Economist
Economist
Economists study how people make decisions in the face of scarcity. They develop models to explain economic phenomena and make predictions about the future. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of economics. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy economic models.
Physicist
Physicist
Physicists study the laws of nature. They develop models to explain the behavior of matter and energy. This course will help you build a strong foundation in linear algebra, which is essential for understanding the mathematical foundations of physics. By understanding the concepts in linear algebra, you will be better equipped to develop and deploy physics models.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with a variety of programming languages and technologies to create solutions for a wide range of problems. This course will help you build a strong foundation in linear algebra, which is essential for understanding computer graphics, image processing, and machine learning algorithms. By understanding the concepts in linear algebra, you will be better equipped to develop robust and efficient software applications.
For more career information including salaries, visit:
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Reading list
We've selected 17 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
線性代數 (Linear Algebra).
Save
Classic textbook on linear algebra that is known for its mathematical rigor. It good choice for students who want to learn the subject in a deep and thorough way.
Save
Textbook on linear algebra and matrix theory. It is suitable for students with a strong mathematical background who are looking for a rigorous treatment of the subject.
This textbook on matrix analysis and applied linear algebra that is suitable for students with a strong mathematical background. It provides a comprehensive treatment of the material, including topics such as matrix theory, eigenvalues and eigenvectors, and numerical linear algebra.
Provides an in-depth treatment of linear algebra, including many proofs and examples. It good choice for students who want to learn more about the theoretical side of linear algebra.
This classic textbook on linear algebra that provides a comprehensive introduction to the subject. It is suitable for students with a strong mathematical background who are looking for a rigorous treatment of the material.
This textbook on linear algebra that is suitable for students with a variety of mathematical backgrounds. It provides a comprehensive treatment of the material, including topics such as linear programming and applications to engineering and economics.
這本書以嚴謹的數學語言介紹了線性代數的抽象概念，適合於有較強數學基礎的讀者，可作為線性代數的進階讀物。
This popular textbook on linear algebra that is known for its clear and concise explanations. It is suitable for students with a variety of mathematical backgrounds.
This textbook on linear algebra that is suitable for students with a variety of mathematical backgrounds. It provides a modern treatment of the material, including topics such as linear programming and applications to computer science.
This textbook on linear algebra that is suitable for students with a variety of mathematical backgrounds. It provides a comprehensive treatment of the material, including topics such as linear programming and applications to computer science.
Provides a modern treatment of linear algebra, including many applications to computer science and other fields. It good choice for students who want to learn more about the practical side of linear algebra.
這本教科書以清晰簡潔的語言介紹了線性代數的基本概念，特別適合用於自學或作為本科線性代數課程的補充讀物。
這本教科書深入探討了線性代數的理論和應用，特別適合於工程、科學和經濟學等領域的學生使用。
Collection of problems and solutions in linear algebra. It good choice for students who want to practice their skills in solving linear algebra problems.
這本書從應用的角度出發，介紹了線性代數在各個領域的應用，適合於工程、科學和經濟學等領域的讀者。
Provides a clear and concise introduction to the basics of linear algebra. It good choice for students who are new to the subject.
Good choice for students who are new to linear algebra and want to learn the basics in a fun and easy-to-understand way.
For more information about how these books relate to this course, visit:
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