Course Summary
This course teaches students the math skills necessary for data science, including linear algebra, calculus, probability, and statistics.Key Learning Points
- Emphasis on practical applications of math skills in data science
- Hands-on exercises and projects to reinforce concepts
- Suitable for beginners with no prior math background
Job Positions & Salaries of people who have taken this course might have
- USA: $60,000 - $110,000
- India: ₹300,000 - ₹1,200,000
- Spain: €30,000 - €50,000
- USA: $60,000 - $110,000
- India: ₹300,000 - ₹1,200,000
- Spain: €30,000 - €50,000
- USA: $90,000 - $150,000
- India: ₹600,000 - ₹2,000,000
- Spain: €40,000 - €70,000
- USA: $60,000 - $110,000
- India: ₹300,000 - ₹1,200,000
- Spain: €30,000 - €50,000
- USA: $90,000 - $150,000
- India: ₹600,000 - ₹2,000,000
- Spain: €40,000 - €70,000
- USA: $120,000 - $170,000
- India: ₹800,000 - ₹3,000,000
- Spain: €50,000 - €90,000
Related Topics for further study
Learning Outcomes
- Understanding of linear algebra and its applications in data science
- Ability to perform calculus operations for data analysis
- Knowledge of probability and statistics for data modeling
Prerequisites or good to have knowledge before taking this course
- Basic understanding of algebra
- Familiarity with programming concepts
Course Difficulty Level
BeginnerCourse Format
- Online
- Self-paced
Similar Courses
- Data Science Essentials
- Applied Data Science with Python
Related Education Paths
Related Books
Description
Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time.
Outline
- Welcome to Data Science Math Skills
- Welcome to Data Science Math Skills
- Course Information
- Weekly feedback surveys
- Building Blocks for Problem Solving
- Sets - Basics and Vocabulary
- Sets - Medical Testing Example
- Sets - Venn Diagrams
- Numbers - The Real Number Line
- Numbers - Less-than and Greater-than
- Numbers - Algebra With Inequalities
- Numbers - Intervals and Interval Notation
- Sigma Notation - Introduction to Summation
- Sigma Notation - Simplification Rules
- Sigma Notation - Mean and Variance
- A note about the video lectures in this lesson
- A note about the video lectures in this lesson
- A note about the video lectures in this lesson
- Feedback
- Practice quiz on Sets
- Practice quiz on the Number Line, including Inequalities
- Practice quiz on Simplification Rules and Sigma Notation
- Graded quiz on Sets, Number Line, Inequalities, Simplification, and Sigma Notation
- Functions and Graphs
- Cartesian Plane - Plotting Points
- Cartesian Plane - Distance Formula
- Cartesian Plane - Point-Slope Formula for Lines
- Cartesian Plane: Slope-Intercept Formula for Lines
- Functions - Mapping from Sets to Sets
- Functions - Graphing in the Cartesian Plane
- Functions - Increasing and Decreasing Functions
- Functions - Composition and Inverse
- A note about the video lectures in this lesson
- A note about the video lectures in this lesson
- Feedback
- Practice quiz on the Cartesian Plane
- Practice quiz on Types of Functions
- Graded quiz on Cartesian Plane and Types of Function
- Measuring Rates of Change
- Tangent Lines - Slope of a Graph at a Point
- Tangent Lines - The Derivative Function
- Using Integer Exponents
- Simplification Rules for Algebra using Exponents
- How Logarithms and Exponents are Related
- The Change of Base Formula
- The Rate of Growth of Continuous Processes
- A note about the video lectures in this lesson
- A note about the video lectures in this lesson
- Feedback
- Practice quiz onTangent Lines to Functions
- Practice quiz on Exponents and Logarithms
- Graded quiz on Tangent Lines to Functions, Exponents and Logarithms
- Introduction to Probability Theory
- Probability Definitions and Notation
- Joint Probabilities
- Permutations and Combinations
- Using Factorial and “M choose N”
- The Sum Rule, Conditional Probability, and the Product Rule
- Bayes’ Theorem (Part 1)
- Bayes’ Theorem (Part 2)
- The Binomial Theorem and Bayes Theorem
- A note about the video lectures in this lesson
- A note about the video lectures in this lesson
- A note about the video lectures in this lesson
- Feedback
- Practice quiz on Probability Concepts
- Practice quiz on Problem Solving
- Practice quiz on Bayes Theorem and the Binomial Theorem
- Probability (basic and Intermediate) Graded Quiz
Summary of User Reviews
The Data Science Math Skills course is highly recommended by users, with many praising its comprehensive coverage of math concepts essential in data science.Key Aspect Users Liked About This Course
comprehensive coverage of math concepts essential in data sciencePros from User Reviews
- In-depth coverage of math concepts
- Engaging and interactive course materials
- Challenging exercises that help students learn
- Excellent instructor who is knowledgeable and helpful
Cons from User Reviews
- The course can be challenging for those without a strong math background
- Some users found the pace too fast
- Some users felt that the course could benefit from more examples and real-world applications
Daniel Egger
4.5 Raiting
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