Adjunct mathematics instructor education requirements

1. Mathematical Biostatistics Boot Camp 1

This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required...

2. Mathematics for Engineers

This specialization was developed for engineering students to self-study engineering mathematics. We expect students to already be familiar with single variable calculus and computer programming. Through this specialization, students will learn matrix algebra, differential equations, vector calculus, numerical methods, and MATLAB programming. This will provide them with the tools to effectively apply mathematics to engineering problems and be well-equipped to pursue a degree in engineering. To...

3. Master Pre Calculus and Trigonometry

4.4

(510)

Get prepared for Calculus and fully grasp all things Precalculus and Trigonometry with over 9 hours of lectures...

4. Mathematical Foundations of Machine Learning

4.5

(5,125)

Essential Linear Algebra and Calculus Hands-On in Num Py, Tensor Flow, and Py Torch...

5. Mathematics for Machine Learning

For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science. This specialization aims to bridge that gap, getting you up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine...

6. SQL Mathematical Functions

Welcome to this project-based course, SQL Mathematical Functions. In this project, you will learn how to use SQL Mathematical Functions to manipulate tables in a database. By the end of this 2-hour-long project, you will be able to use different Mathematical Functions to retrieve the desired result from a database. In this project, you will learn how to use SQL Mathematical Functions like CEIL(), FLOOR(), RANDOM(), SETSEED(), ROUND(), TRUNC(), SQRT(), CBRT(), and POWER() to manipulate data in...

7. Mathematical Foundation For Machine Learning and AI

4.6

(1,262)

Learn the core mathematical concepts for machine learning and learn to implement them in R and python...

8. College Algebra, Pre-Calculus, & Trigonometry Explained

4.7

(466)

Master College Level Algebra with our Step by Step Video Tutorials. Over 4500 Practice Questions! Ace your Algebra Exam!...

9. Mathematics for Machine Learning: PCA

This intermediate-level course introduces the mathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique. We'll cover some basic statistics of data sets, such as mean values and variances, we'll compute distances and angles between vectors using inner products and derive orthogonal projections of data onto lower-dimensional subspaces. Using all these tools, we'll then derive PCA as a method that minimizes the average squared...

10. Mathematics for Machine Learning and Data Science

Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. This beginner-friendly Specialization is where you’ll master the fundamental mathematics toolkit of machine learning.\n\nMany machine learning engineers and data scientists need help with mathematics, and even experienced practitioners can feel held back by a lack of math skills. This Specialization uses innovative pedagogy in mathematics to help you learn...

11. Discrete Mathematics

4.6

(2,937)

Master Discrete Math for Computer Science and Mathematics Students...

12. Mathematics for Computer Games Development using Unity

4.5

(1,590)

A Beginner's Guide to Essential Mathematics, Data Structures and Algorithms used in Game Programming applied in Unity...

13. Advanced Linear Models for Data Science 2: Statistical Linear Models

Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: - A basic understanding of linear algebra and multivariate calculus. - A basic understanding of statistics and regression models. - At least a little familiarity with proof based mathematics. - Basic knowledge of the R programming language...

14. Complete Mathematics Masterclass: College & University Level

4.8

(321)

All the Applied Mathematics Needed in Science, Programming, Engineering, IT & Business - Theory, Examples & Exercises...

15. Use Probability & Statistics accurately, in Decision making

4.6

(1,743)

Lessons for Leaders and Managers: Avoid the common Misconceptions and Mistakes, in Probability & Statistics...

16. Pre-Algebra Explained

4.6

(518)

Master Pre-Algebra with 700 Practice Questions! Prepare for High School Math: Algebra, Geometry, Trigonometry...

17. Algebra 2 & Trigonometry: A Complete High School Curriculum

4.4

(517)

Includes videos and over 300 pages of quizzes/worksheets (answer keys provided!)...

18. Statistics & Mathematics for Data Science & Data Analytics

4.6

(1,486)

Learn the statistics & probability for data science and business analysis...

19. Master Discrete Mathematics: Sets, Math Logic, and More

4.9

(1,366)

Master Discrete Mathematics: Learn and master all of Discrete Math - Logic, Set Theory, Combinatorics, Graph Theory, Etc...