Data Science Math Skills

开始时间: 08/01/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 计算机科学

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/learn/datasciencemathskills

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课程详情

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. Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to more advanced material. Topics include: ~Set theory, including Venn diagrams ~Properties of the real number line ~Interval notation and algebra with inequalities ~Uses for summation and Sigma notation ~Math on the Cartesian (x,y) plane, slope and distance formulas ~Graphing and describing functions and their inverses on the x-y plane, ~The concept of instantaneous rate of change and tangent lines to a curve ~Exponents, logarithms, and the natural log function. ~Probability theory, including Bayes’ theorem. While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization. Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel." Good luck and we hope you enjoy the course!

数据科学数学技能:数据科学课程包含数学-不能避免!本课程旨在向学习者讲授在几乎所有数据科学数学课程中取得成功所需要的基础数学,并且是为具有基本数学技能但未学习过代数或预微积分的学习者而设计的。数据科学数学技能介绍了数据科学所基于的核心数学,并且没有任何额外的复杂性,一次介绍了不熟悉的想法和数学符号。 完成本课程的学习者将掌握词汇资料,符号,概念和代数规则,所有数据科学家都必须知道这些词汇,符号,概念和代数规则,然后才能使用更高级的材料。 主题包括: 〜集合论,包括维恩图 〜实数线的性质 〜带不等式的区间符号和代数 〜用于求和和Sigma表示法 〜笛卡尔(x,y)平面上的数学,斜率和距离公式 〜在x-y平面上绘制和描述函数及其反函数, 〜瞬时变化率和曲线切线的概念 〜指数,对数和自然对数函数。 〜概率论,包括贝叶斯定理。 虽然本课程旨在概述数据科学所需的数学技能,但对于感兴趣的课程“掌握Excel中的数据分析”的学生而言,它可以被视为先决条件,该课程是Excel到MySQL数据科学专业化的一部分。掌握“数据科学数学技能”的学习者将为“成功掌握Excel中的数据分析”中介绍的更高级的数学概念做好充分的准备。 祝您好运,我们希望您喜欢这个课程!

课程大纲

This module contains three lessons that are build to basic math vocabulary. The first lesson, "Sets and What They’re Good For," walks you through the basic notions of set theory, including unions, intersections, and cardinality. It also gives a real-world application to medical testing. The second lesson, "The Infinite World of Real Numbers," explains notation we use to discuss intervals on the real number line. The module concludes with the third lesson, "That Jagged S Symbol," where you will learn how to compactly express a long series of additions and use this skill to define statistical quantities like mean and variance.

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课程简介

杜克大学 Data Science Math Skills(数据科学中的数学技巧),这门课程主要介绍数据科学中涉及的相关数学概念,让学生了解基本的数学概念,掌握基本的数学语言,内容涵盖集合论、求和的Sigma符号、数学上的笛卡尔(x,y)平面、指数、对数和自然对数函数,概率论以及叶斯定理等。

课程标签

数学 数据科学 数学机器 数学技巧 数据科学中的数学技巧

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