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Dennis Davenport
and
MOUSSA DOUMBIA
This course is the first of a series that is designed for beginners who want to learn how to apply basic data science concepts to real-world problems. You might be a student who is considering pursuing a career in data science and wanting to learn more, or you might be a business professional who wants to apply some data science principles to your work. Or, you might simply be a curious, lifelong learner intrigued by the powerful tools that data science and math provides. Regardless of your motivation, we’ll provide you with the support and information you need to get started.
Read more
This course is the first of a series that is designed for beginners who want to learn how to apply basic data science concepts to real-world problems. You might be a student who is considering pursuing a career in data science and wanting to learn more, or you might be a business professional who wants to apply some data science principles to your work. Or, you might simply be a curious, lifelong learner intrigued by the powerful tools that data science and math provides. Regardless of your motivation, we’ll provide you with the support and information you need to get started.
Read more
This course is the first of a series that is designed for beginners who want to learn how to apply basic data science concepts to real-world problems. You might be a student who is considering pursuing a career in data science and wanting to learn more, or you might be a business professional who wants to apply some data science principles to your work. Or, you might simply be a curious, lifelong learner intrigued by the powerful tools that data science and math provides. Regardless of your motivation, we’ll provide you with the support and information you need to get started.
In this course, we'll cover the fundamentals of linear algebra, including systems of linear equations, matrix operations, and vector equations. Whether you’ve learned some of these concepts before and are looking for a refresher or you’re brand new to the ideas we’ll cover, you’ll find the materials to support you. Let's get started!
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What's inside
Syllabus
Introduction to Matrices and Linear Algebra
In module 1, you'll learn how to explain fundamental concepts of linear algebra and how to use Python, one of the most powerful programming languages, to model different data. We will cover the following learning objectives.
Read more
Syllabus
Introduction to Matrices and Linear Algebra
In module 1, you'll learn how to explain fundamental concepts of linear algebra and how to use Python, one of the most powerful programming languages, to model different data. We will cover the following learning objectives.
Read more
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Designed to help beginners apply basic data science concepts to real-world problems through the use of Python and linear algebra
Instructors include Dennis Davenport and MOUSSA DOUMBIA, both experts in their respective fields
Covers a wide range of topics relevant to data science, including linear algebra, matrix operations, and vector equations
Introduces learners to relevant software tools, such as Python, NumPy, SymPy, and Jupyter Notebook
Emphasizes hands-on learning through software installation, best practices, and data modeling activities
Provides real-world applications of vector equations to help learners understand their practical significance
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Reviews summary
Foundational linear algebra with practical python
According to students, this course is a largely positive introduction to linear algebra, especially for those with minimal math background or seeking to apply concepts with Python. Many found the instructor's explanations clear and engaging, making complex topics understandable. The hands-on coding and practical applications, particularly with NumPy and SymPy, are frequently highlighted as a major strength. While some absolute beginners found the pace occasionally challenging and a few learners desired more advanced challenges or deeper theoretical dives, the course generally provides a solid foundational understanding suitable for aspiring data scientists and business professionals.
Emphasizes concrete examples for practical understanding.
"I particularly appreciated the practical applications of vector equations in the final module."
"Real-world examples were particularly useful."
"I learned how to use practical tools and strategies that I could apply immediately to my work, especially as a professional."
Instructor delivers clear and engaging explanations.
"The instructor made complex topics understandable through clear explanations and hands-on examples."
"The instructor was engaging, and the pacing was just right for someone new to both subjects."
"The instructor's explanations were patient and thorough. I highly recommend it."
Presents complex concepts accessibly for new learners.
"This course provided an excellent introduction to linear algebra for someone with minimal math background."
"Excellent course for true beginners! I had no prior experience with linear algebra or Python, and this course gently guided me through."
"The instructor made complex topics understandable through clear explanations and hands-on examples."
Seamlessly applies linear algebra concepts using Python.
"The Python integration was seamless and practical. Highly recommend for beginners in data science."
"Fantastic course for anyone looking to bridge the gap between theoretical linear algebra and its application in Python."
"The practical applications with Python were incredibly insightful. The content is accessible and well-organized for me."
Some found the pace fast, others desired more depth.
"Some parts felt a bit rushed, especially for absolute beginners..."
"I struggled with this course. While the Python examples were clear, the linear algebra explanations often felt too fast or assumed prior knowledge I didn't have."
"The course is okay. It covers the basics, but I felt it lacked depth in certain areas. I needed external resources for deeper understanding."
"This course was too basic for me, even for an introduction. I was hoping for more challenging problems and a deeper dive into theoretical aspects."
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 Introduction to Linear Algebra and Python with these
activities:
Review Calculus Concepts
Show steps
Review key concepts from calculus, which provide a foundation for understanding linear algebra.
Browse courses on
Calculus
Show steps
-
Review the concepts of limits, derivatives, and integrals
-
Solve practice problems to reinforce your understanding
Read 'Linear Algebra and Its Applications'
Show steps
Review the foundational concepts of linear algebra by reading a comprehensive textbook before starting the course.
View
Linear Algebra and Its Applications, Global...
on Amazon
Show steps
-
Read the assigned chapters on matrix operations, vector equations, and linear transformations
-
Solve the practice problems at the end of each chapter
Practice Basic Matrix Operations
Show steps
Practice basic matrix operations to refresh your understanding of matrix algebra before starting the course.
Browse courses on
Matrix Operations
Show steps
-
Review matrix addition and subtraction
-
Practice multiplying matrices
-
Try solving systems of linear equations using matrices
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow Tutorials on Matrix Decompositions
Show steps
Follow online tutorials to supplement your understanding of matrix decompositions, which are covered later in the course.
Browse courses on
Matrix Decompositions
Show steps
-
Find reputable tutorials on matrix decompositions
-
Watch the tutorials and take notes
-
Try the practice exercises provided in the tutorials
Solve Vector Equation Practice Problems
Show steps
Solve practice problems on vector equations to reinforce the concepts covered in the course.
Show steps
-
Find the solutions to systems of vector equations
-
Apply vector equations to model real-world problems
Attend a Linear Algebra Workshop
Show steps
Attend a workshop led by an expert in linear algebra to gain hands-on experience and clarify your understanding of the subject.
Browse courses on
Linear Algebra
Show steps
-
Research and find a suitable workshop
-
Register for the workshop and attend all sessions
-
Participate actively in discussions and exercises
Visualize Matrix Transformations
Show steps
Create visual representations of matrix transformations to enhance your understanding of their effects on data.
Show steps
-
Choose a matrix transformation to visualize
-
Use a programming language or software to create a visual representation
-
Analyze the visualization to understand the effects of the transformation
Mentor a Junior Student in Linear Algebra
Show steps
Enhance your understanding by mentoring a junior student in linear algebra, helping them to grasp the concepts and solve problems.
Browse courses on
Linear Algebra
Show steps
-
Identify a junior student who needs assistance
-
Meet regularly to review concepts and solve problems together
-
Provide feedback and encouragement to help the student progress
Review Calculus Concepts
Show steps
Review key concepts from calculus, which provide a foundation for understanding linear algebra.
Browse courses on
Calculus
Show steps
Show steps
Show steps
- Review the concepts of limits, derivatives, and integrals
- Solve practice problems to reinforce your understanding
Read 'Linear Algebra and Its Applications'
Show steps
Review the foundational concepts of linear algebra by reading a comprehensive textbook before starting the course.
View
Linear Algebra and Its Applications, Global...
on Amazon
Show steps
Show steps
Show steps
- Read the assigned chapters on matrix operations, vector equations, and linear transformations
- Solve the practice problems at the end of each chapter
Practice Basic Matrix Operations
Show steps
Practice basic matrix operations to refresh your understanding of matrix algebra before starting the course.
Browse courses on
Matrix Operations
Show steps
Show steps
Show steps
- Review matrix addition and subtraction
- Practice multiplying matrices
- Try solving systems of linear equations using matrices
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow Tutorials on Matrix Decompositions
Show steps
Follow online tutorials to supplement your understanding of matrix decompositions, which are covered later in the course.
Browse courses on
Matrix Decompositions
Show steps
Show steps
Show steps
- Find reputable tutorials on matrix decompositions
- Watch the tutorials and take notes
- Try the practice exercises provided in the tutorials
Solve Vector Equation Practice Problems
Show steps
Solve practice problems on vector equations to reinforce the concepts covered in the course.
Show steps
Show steps
Show steps
- Find the solutions to systems of vector equations
- Apply vector equations to model real-world problems
Attend a Linear Algebra Workshop
Show steps
Attend a workshop led by an expert in linear algebra to gain hands-on experience and clarify your understanding of the subject.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Research and find a suitable workshop
- Register for the workshop and attend all sessions
- Participate actively in discussions and exercises
Visualize Matrix Transformations
Show steps
Create visual representations of matrix transformations to enhance your understanding of their effects on data.
Show steps
Show steps
Show steps
- Choose a matrix transformation to visualize
- Use a programming language or software to create a visual representation
- Analyze the visualization to understand the effects of the transformation
Mentor a Junior Student in Linear Algebra
Show steps
Enhance your understanding by mentoring a junior student in linear algebra, helping them to grasp the concepts and solve problems.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Identify a junior student who needs assistance
- Meet regularly to review concepts and solve problems together
- Provide feedback and encouragement to help the student progress
Career center
Learners who complete Introduction to Linear Algebra and Python will develop knowledge and skills
that may be useful to these careers:
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make predictions about future market trends. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Quantitative Analysts. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Data Scientist
Data Scientist
Data Scientists use scientific methods to extract knowledge and insights from data. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Data Scientists. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Machine Learning Engineers. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Software Engineers. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to provide insights that can be used to make better decisions. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Data Analysts. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Financial Analyst
Financial Analyst
Financial Analysts evaluate and recommend investments. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Financial Analysts. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve business problems. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Operations Research Analysts. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Actuary
Actuary
Actuaries analyze and assess financial risks. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Actuaries. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Statisticians. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Market Researcher
Market Researcher
Market Researchers conduct research to understand market trends and consumer behavior. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Market Researchers. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Business Analyst
Business Analyst
Business Analysts analyze business processes and identify opportunities for improvement. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Business Analysts. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Management Consultant
Management Consultant
Management Consultants advise businesses on how to improve their operations. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Management Consultants. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Financial Advisor
Financial Advisor
Financial Advisors provide financial advice to individuals and businesses. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Financial Advisors. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Risk Manager
Risk Manager
Risk Managers identify, assess, and mitigate risks. This course can be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, both of which are essential skills for Risk Managers. Particularly, the module on using linear algebra concepts in Python can be helpful for understanding how to use these tools in a practical setting.
Teacher
Teacher
Teachers plan, prepare, and deliver instruction to students. This course may be useful in building a foundation for this job role, as it provides an introduction to linear algebra and Python, which can be helpful for understanding the mathematical concepts taught in schools.
For more career information including salaries, visit:
OpenCourser.com/course/wrn33i/introduction
Reading list
We've selected 11 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
Introduction to Linear Algebra and Python.
Provides a comprehensive introduction to Python for data analysis, covering topics such as data manipulation, data visualization, and machine learning. It valuable resource for anyone who wants to use Python for data science.
Provides a comprehensive introduction to linear algebra, covering a wide range of topics including matrix operations, vector spaces, and systems of linear equations. It classic textbook that is used in many university courses on linear algebra.
Provides a comprehensive introduction to deep learning using Python, covering a wide range of topics from the basics to advanced concepts. It valuable resource for anyone who wants to learn about deep learning or improve their understanding of the field.
Save
Provides a comprehensive introduction to deep learning, covering a wide range of topics from the basics to advanced concepts. It valuable resource for anyone who wants to learn about deep learning or improve their understanding of the field.
Provides a practical introduction to machine learning using Python, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone who wants to learn how to use machine learning for real-world problems.
Provides an introduction to linear algebra from an applied perspective, with a focus on applications in engineering and computer science. It covers topics such as matrix decompositions, eigenvalues and eigenvectors, and linear programming.
Provides a clear and concise introduction to linear algebra, with a focus on applications in the social sciences, business, and engineering. It covers topics such as matrix operations, vector spaces, and systems of linear equations.
Save
Provides a comprehensive introduction to algebraic geometry, covering a wide range of topics from the basics to advanced concepts. It valuable resource for anyone who wants to learn about algebraic geometry or improve their understanding of the field.
Provides a comprehensive introduction to homological algebra, covering a wide range of topics from the basics to advanced concepts. It valuable resource for anyone who wants to learn about homological algebra or improve their understanding of the field.
Provides a comprehensive introduction to category theory, covering a wide range of topics from the basics to advanced concepts. It valuable resource for anyone who wants to learn about category theory or improve their understanding of the field.
Provides a rigorous and abstract treatment of linear algebra, suitable for advanced undergraduate or graduate students. It covers topics such as vector spaces, linear transformations, and inner product spaces.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/wrn33i/introduction
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Effort
12 hours to complete
Level
Introductory
Via
Coursera
Institution
Howard University
Instructors
Dennis Davenport
MOUSSA DOUMBIA
Language
English
Transcripts
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This course belongs to a
collection
called
Linear Algebra for Data Science Using Python. It's comprised of four courses:
- Fundamental Linear Algebra Concepts with Python
- Introduction to Linear Algebra and Python (viewing)
- Capstone: Data Science Problem in Linear Algebra Framework
- Building Regression Models with Linear Algebra
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