This course is part of the Linear Algebra for Data Science Using Python Specialization

Moussa Doumbia +1 more instructor

1,934 already enrolled

Offered By

Linear Algebra for Data Science Using Python SpecializationHoward University

About this Course

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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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Course 1 of 4 in the

Linear Algebra for Data Science Using Python Specialization

Beginner Level

Approx. 12 hours to complete

English

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Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 4 in the

Linear Algebra for Data Science Using Python Specialization

Beginner Level

Approx. 12 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Moussa Doumbia

Department of Mathematics

2,085 Learners

4 Courses

Dennis Davenport

Graduate Director and Associate Professor

Department of Mathematics

2,085 Learners

4 Courses

Offered by

Howard University

Founded in 1867, Howard University is a private, research university that is comprised of 14 schools and colleges. Students pursue more than 140 programs of study leading to undergraduate, graduate and professional degrees. The University operates with a commitment to Excellence in Truth and Service and has produced one Schwarzman Scholar, three Marshall Scholars, four Rhodes Scholars, 12 Truman Scholars, 25 Pickering Fellows and more than 165 Fulbright recipients. Howard also produces more on-campus African American Ph.D. recipients than any other university in the United States. For more information on Howard University, visit www.howard.edu.

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Syllabus - What you will learn from this course

Week1

Week 1

5 hours to complete

Introduction to Matrices and Linear Algebra

5 hours to complete

15 videos (Total 85 min), 6 readings, 3 quizzes

15 videos

Introduction to Linear Algebra for Data Science Using Python (Specialization)3mIntroduction to Linear Algebra and Python2mIntroduction to Instructors3mInstalling the Version Control System Git Bash5mInstalling Git Bash for a Mac4mInstalling Jupyter Notebook via Anaconda4mOpening a Jupyter Notebook8mHow to Document Your Code7mIntroduction to Matrices5mIntroduction to Matrices in Python Using NumPy6mIntroduction to Matrices in Python Using SymPy6mHow Is Linear Algebra Used to Solve Problems?3mUsing Graphs in Python to Model Data8mDoing More with Graphs in Python to Model Data: Part 18mDoing More with Graphs in Python to Model Data: Part 2 (Data Visualizations)5m

6 readings

Course 1 Welcome30mNote About Git Bash for Mac1mReminder - Start with Git Bash5mBest Practices for Learning Programming10mPython Resources30mGet to Know NumPy and SymPy10m

3 practice exercises

Getting Started with Linear Algebra and Python30mModeling Data in Python30mFundamental Concepts in Linear Algebra & Common Data Science Applications of Linear Algebra30m

Week2

Week 2

3 hours to complete

Using Linear Algebra Concepts in Python

3 hours to complete

7 videos (Total 46 min), 1 reading, 3 quizzes

7 videos

Introduction to Linear Algebra Functions in Python6mUsing Matrices in Python5mSolving Linear Equations Using Python6mMatrix Addition5mMatrix Multiplication8mA Practical Example of Matrix Multiplication2mUsing Matrix Algebra in Python10m

1 reading

Supplemental Reading on Using Python to Solve Linear Equations30m

3 practice exercises

Using Linear Algebra30mMatrix Algebra by Hand and in Python30mMatrix Addition, Multiplication, and Scalar Multiplication by Hand and in Python30m

Week3

Week 3

2 hours to complete

Vector Equations and Systems of Linear Equations

2 hours to complete

7 videos (Total 47 min)

7 videos

Systems of Linear Equations4mRow Echelon Form and Augmented Matrices8mElementary Row Operations and Row Equivalent Matrices4mGaussian Elimination (row reduction)8mVector Equations4mSolving Vector Equations7mPractical Applications of a Linear Function Model8m

3 practice exercises

Vector Equations and Systems of Linear Equations30mUsing Vector Equations30mVector Equations, Systems of Linear Equations, and Modeling Data30m

Week4

Week 4

2 hours to complete

Real-World Applications of Vector Equations

Welcome to the final module of this course! Over the past 3 modules, you have been introduced to and gained knowledge on the following topics:- Version control - Git Bash, Jupyter Notebook via Anaconda, NumPy and SymPy, and other software tools, Modeling data, Matrix algebra and, Vector equations. In the final module of the course, you'll apply what you've learned to concrete, real-world examples. You'll practice using vector equations to study data sets and provide peer reviews. We will cover the following learning objectives.

2 hours to complete

4 videos (Total 24 min), 1 reading, 2 quizzes

About the Linear Algebra for Data Science Using Python Specialization

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What will I get if I subscribe to this Specialization?
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Introduction to Linear Algebra and Python

About this Course