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    • Linear Algebra

    Linear Algebra Courses Online

    Study linear algebra for mathematical and engineering applications. Learn about matrices, vectors, and linear transformations.

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    Explore the Linear Algebra Course Catalog

    • Status: Free
      Free
      T

      The Hong Kong University of Science and Technology

      Python and Statistics for Financial Analysis

      Skills you'll gain: Statistical Inference, Statistical Methods, Pandas (Python Package), Probability & Statistics, Risk Analysis, Financial Trading, Financial Data, Data Manipulation, Statistical Analysis, Regression Analysis, Financial Analysis, Jupyter, Financial Modeling

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.5K reviews

      Intermediate · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Algebra: Elementary to Advanced - Functions & Applications

      Skills you'll gain: Mathematical Modeling, Graphing, Algebra, Mathematical Theory & Analysis, Applied Mathematics, Arithmetic

      4.8
      Rating, 4.8 out of 5 stars
      ·
      184 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      K

      Koç University

      Doğrusal Cebir I: Uzaylar ve İşlemciler / Linear Algebra I: Spaces and Operators

      Skills you'll gain: Linear Algebra, Applied Mathematics, Algebra, Engineering Calculations, General Mathematics, Calculus, Mathematics and Mathematical Modeling, Advanced Mathematics, Differential Equations, Mathematical Modeling, Mathematical Theory & Analysis, Geometry

      4.1
      Rating, 4.1 out of 5 stars
      ·
      43 reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Toronto

      Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Control Systems, Embedded Software, Automation, Deep Learning, Software Architecture, Simulations, Safety Assurance, Artificial Neural Networks, Global Positioning Systems, Hardware Architecture, Systems Architecture, Artificial Intelligence, Estimation, Algorithms, Machine Learning Methods, Predictive Modeling, Scenario Testing, Spatial Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: New AI skills
      New AI skills
      G

      Google

      Google UX Design

      Skills you'll gain: Storyboarding, Wireframing, Responsive Web Design, User Experience Design, Design Thinking, User Research, UI/UX Research, Information Architecture, Figma (Design Software), Usability Testing, User Story, Web Design, Design Reviews, Usability, Presentations, User Experience, Design Research, Ideation, User Centered Design, Mockups

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      90K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • K

      Kennesaw State University

      Six Sigma Yellow Belt

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Lean Methodologies, Data Collection, Process Improvement, Quality Improvement, Process Optimization, Lean Six Sigma, Correlation Analysis, Statistical Hypothesis Testing, Kaizen Methodology, Process Analysis, Probability Distribution, Regression Analysis, Process Capability, Business Process, Statistical Process Controls, Quality Management, Team Management, Continuous Improvement Process

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.9K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Natural Language Processing

      Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Algorithms, Keras (Neural Network Library), Linear Algebra, Data Cleansing, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Alberta

      Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Simulations, Solution Architecture, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Supervised Learning, Algorithms, Performance Testing, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      Data Analysis with Python

      Skills you'll gain: Data Wrangling, Data Cleansing, Data Analysis, Data Manipulation, Data Import/Export, Exploratory Data Analysis, Data Science, Statistical Analysis, Descriptive Statistics, Regression Analysis, Predictive Modeling, Pandas (Python Package), Scikit Learn (Machine Learning Library), Machine Learning Methods, Data Pipelines, NumPy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      19K reviews

      Intermediate · Course · 1 - 3 Months

    • D

      Duke University

      Introduction to Logic and Critical Thinking

      Skills you'll gain: Deductive Reasoning, Logical Reasoning, Computational Logic, Probability, Sampling (Statistics), Persuasive Communication, Research, Writing, Statistics, Scientific Methods, Oral Expression, Correlation Analysis, Interpersonal Communications, Interactive Learning, Learning Strategies, Instructional Strategies

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Amsterdam

      Methods and Statistics in Social Sciences

      Skills you'll gain: Qualitative Research, Scientific Methods, Descriptive Statistics, Statistical Analysis, Statistical Hypothesis Testing, Research, Sampling (Statistics), Probability Distribution, Correlation Analysis, Research Design, Research Reports, Science and Research, Interviewing Skills, Data Analysis, Probability, Data Collection, Social Sciences, Statistical Methods, Probability & Statistics, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.6K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of London

      International Business Essentials

      Skills you'll gain: Financial Statements, Business Planning, Sampling (Statistics), Leadership and Management, Descriptive Statistics, Team Management, Team Building, Organizational Structure, Data Presentation, Professional Networking, Communication, Organizational Change, Business Mathematics, Business Strategy, Professionalism, Resource Allocation, Competitive Analysis, Linear Algebra, Mathematical Modeling, Business Strategies

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    Linear Algebra learners also search

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    1…567…55

    In summary, here are 10 of our most popular linear algebra courses

    • Python and Statistics for Financial Analysis: The Hong Kong University of Science and Technology
    • Algebra: Elementary to Advanced - Functions & Applications: Johns Hopkins University
    • DoÄŸrusal Cebir I: Uzaylar ve İşlemciler / Linear Algebra I: Spaces and Operators: Koç University
    • Self-Driving Cars: University of Toronto
    • Google UX Design: Google
    • Six Sigma Yellow Belt: Kennesaw State University
    • Natural Language Processing: DeepLearning.AI
    • Reinforcement Learning: University of Alberta
    • Data Analysis with Python: IBM
    • Introduction to Logic and Critical Thinking: Duke University

    Skills you can learn in Machine Learning

    Python Programming (33)
    Tensorflow (32)
    Deep Learning (30)
    Artificial Neural Network (24)
    Big Data (18)
    Statistical Classification (17)
    Reinforcement Learning (13)
    Algebra (10)
    Bayesian (10)
    Linear Algebra (10)
    Linear Regression (9)
    Numpy (9)

    Frequently Asked Questions about Linear Algebra

    Linear algebra courses on Coursera cover a wide array of fundamental and advanced topics, enabling learners to:

    • Understand vectors and matrices and their applications in various fields
    • Learn methods for solving systems of linear equations
    • Explore eigenvalues and eigenvectors and their significance in transformations
    • Apply linear algebra concepts to computer graphics, data analysis, and more
    • Discover how linear algebra supports machine learning and artificial intelligence algorithms‎

    No prior experience in advanced mathematics is required to start with the introductory linear algebra courses available on Coursera. These courses are designed to accommodate learners at different proficiency levels:

    • Beginners can start with basic concepts of vectors and matrix operations.
    • Intermediate learners can delve into more complex subjects such as linear transformations and space.
    • Advanced learners can tackle topics like abstract vector spaces and computational linear algebra.‎

    Coursera offers various credentials through its linear algebra courses, designed to cater to both novices and professionals:

    • Course certificates that validate your knowledge of linear algebra fundamentals
    • Professional certificates that demonstrate your specialized skills in mathematics
    • Specializations with focused expertise in advanced linear algebra topics‎

    Looking to enhance your team's linear algebra skills? Coursera provides tailored enterprise solutions for teams ranging of 5-125 employees. Our offerings include advanced analytics, customized learning paths, and collaborative tools. To explore our linear algebra training options and make a purchase, please visit our Coursera for Teams page.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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