Sci: Mathematics

Sort options

Calculus through Data & Modeling: Limits & Derivatives (Coursera)

Jan 31st 2022
Calculus through Data & Modeling: Limits & Derivatives (Coursera)
Course Auditing
Categories
Effort
Languages
This first course on concepts of single variable calculus will introduce the notions of limits of a function to define the derivative of a function. In mathematics, the derivative measures the sensitivity to change of the function. For example, the derivative of the position of a moving object with [...]
No votes yet

Calculus through Data & Modeling: Applying Differentiation (Coursera)

Jan 31st 2022
Calculus through Data & Modeling: Applying Differentiation (Coursera)
Course Auditing
Categories
Effort
Languages
As rates of change, derivatives give us information about the shape of a graph. In this course, we will apply the derivative to find linear approximations for single-variable and multi-variable functions. This gives us a straightforward way to estimate functions that may be complicated or difficult to evaluate. We [...]
No votes yet

Precalculus: Mathematical Modeling (Coursera)

Jan 31st 2022
Precalculus: Mathematical Modeling (Coursera)
Course Auditing
Categories
Effort
Languages
This course helps to build the foundational material to use mathematics as a tool to model, understand, and interpret the world around us. This is done through studying functions, their properties, and applications to data analysis. Concepts of precalculus provide the set of tools for the beginning [...]
No votes yet

Precalculus: Periodic Functions (Coursera)

Jan 31st 2022
Precalculus: Periodic Functions (Coursera)
Course Auditing
Categories
Effort
Languages
This course helps to build the foundational material to use mathematics as a tool to model, understand, and interpret the world around us. This is done through studying functions, their properties, and applications to data analysis. Concepts of precalculus provide the set of tools for the beginning [...]
No votes yet

Precalculus: Relations and Functions (Coursera)

This course helps to build the foundational material to use mathematics as a tool to model, understand, and interpret the world around us. This is done through studying functions, their properties, and applications to data analysis. Concepts of precalculus provide the set of tools for the beginning [...]
No votes yet

First Steps in Linear Algebra for Machine Learning (Coursera)

The main goal of the course is to explain the main concepts of linear algebra that are used in data analysis and machine learning. Another goal is to improve the student’s practical skills of using linear algebra methods in machine learning and data analysis. You will learn the fundamentals [...]
No votes yet

Calculus and Optimization for Machine Learning (Coursera)

Hi! Our course aims to provide necessary background in Calculus sufficient for up-following Data Science courses. Course starts with a basic introduction to concepts concerning functional mappings. Later students are assumed to study limits (in case of sequences, single- and multivariate functions), differentiability (once again starting from single variable [...]
No votes yet

Discrete Math and Analyzing Social Graphs (Coursera)

The main goal of this course is to introduce topics in Discrete Mathematics relevant to Data Analysis. We will start with a brief introduction to combinatorics, the branch of mathematics that studies how to count. Basics of this topic are critical for anyone working in Data Analysis or Computer [...]
No votes yet

Probability Theory, Statistics and Exploratory Data Analysis (Coursera)

Exploration of Data Science requires certain background in probability and statistics. This course introduces you to the necessary sections of probability theory and statistics, guiding you from the very basics all way up to the level required for jump starting your ascent in Data Science.
No votes yet

Mathematics for Machine Learning: Multivariate Calculus (Coursera)

This course offers a brief introduction to the multivariate calculus required to build many common machine learning techniques. We start at the very beginning with a refresher on the “rise over run” formulation of a slope, before converting this to the formal definition of the gradient of a function. [...]
No votes yet