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Data Analytics Foundations for Accountancy I

Курс от University of Illinois Urbana-Champaign

Начальный≈ 66.7 чАнглийский

О курсе

Welcome to Data Analytics Foundations for Accountancy I! You’re joining thousands of learners currently enrolled in the course. I'm excited to have you in the class and look forward to your contributions to the learning community. To begin, I recommend taking a few minutes to explore the course site. Review the material we’ll cover each week, and preview the assignments you’ll need to complete to pass the course. Click Discussions to see forums where you can discuss the course material with fellow students taking the class. If you have questions about course content, please post them in the forums to get help from others in the course community. For technical problems with the Coursera platform, visit the Learner Help Center. Good luck as you get started, and I hope you enjoy the course!

Программа курса

9 модулей · 119 учебных материалов

01Course Orientation10 материалов

About the Course

Welcome to Data Analytics Foundations for Accountancy IВидео Meet Professor BrunnerВидео SyllabusЧтение About the Discussion ForumsЧтение

Учитесь у экспертов

Robert J. Brunner

Professor of Accountancy, Chief Disruption Officer, and Arthur Andersen Faculty Fellow

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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 66.7 ч

9 модулей

Язык: Английский

Субтитры: Арабский, Французский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Нидерландский, Корейский, Немецкий, Русский, Тайский, Индонезийский, Шведский, Турецкий, Испанский, Хинди, Японский, Казахский, Польский

Data Analytics Foundations for Accountancy I

О курсе

Навыки, которые вы освоите

Программа курса

About the Course

Учитесь у экспертов

Robert J. Brunner

About Your Classmates

Module 1 Information

Lesson 1-1: The Importance of Data Analytics in Modern Accountancy

Lesson 1-2: Introduction to the Course JupyterHub Server

Lesson 1-3: Introduction to Markdown

Lesson 1-4: Introduction to the Python Programming Language

Module 1 Graded Activities

Module 2 Information

Lesson 2-1: Why Accounting Students Should Learn to Code

Lesson 2-2: Basic Python Data Structures

Lesson 2-3: Python Functions

Lesson 2-4: Python Programming Concepts

Module 2 Graded Activities

Module 3 Information

Lesson 3-1: Why Use Python Instead of Excel?

Lesson 3-2: Introduction to the Unix Filesystem

Lesson 3-3: Reading and Writing Data to a File Using Python

Lesson 3-4: Introduction to the Pandas Module

Module 3 Graded Activities

Module 4 Information

Lesson 4-1: How the Pandas Module Can Support Standard Business Analytics

Lesson 4-2: Introduction to the Numpy Module

Lesson 4-3: Introduction to Descriptive Statistics

Lesson 4-4: Advanced Features of Pandas

Module 4 Graded Activities

Module 5 Information

Lesson 5-1: Creating Clear and Powerful Visualizations

Lesson 5-2: Visualization of Quantitative Data

Lesson 5-3: Constructing a Visualization in Python

Lesson 5-4: Exploring a One-Dimensional Data Set Visually Using Python

Module 5 Graded Activities

Module 6 Information

Lesson 6-1: Basics of Probability

Lesson 6-2: Conditional Probability and Bayes Theorem

Lesson 6-3: Calculating Probabilities and Applying Bayes Theorem in Python

Lesson 6-4: Introduction to Distributions

Module 6 Graded Activities

Module 7 Information

Lesson 7-1: Introduction to Scatter Plots

Lesson 7-2: Introduction to Numpy Matrices

Lesson 7-3: Statistical Issues When Exploring Multi-Dimensional Data

Lesson 7-4: Ordinary Linear Regression

Module 7 Graded Activities

Module 8 Information

Lesson 8-1: Why Do Accounting Students Need Data Analytics Skills?

Lesson 8-2: Basic Concepts Behind Density Estimation

Lesson 8-3: Kernel Density Estimation Functionality in Python

Module 8 Graded Activities