Acerca de este Curso
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Aprox. 56 horas para completar

Sugerido: 7 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Aprox. 56 horas para completar

Sugerido: 7 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
1 hora para completar

Course Orientation

You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.

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2 videos (Total 8 minutos), 4 readings, 1 quiz
4 lecturas
Syllabus10m
About the Discussion Forums10m
Updating Your Profile10m
Social Media10m
1 ejercicio de práctica
Orientation Quiz10m
8 horas para completar

Module 1: Foundations

This module serves as the introduction to the course content and the course Jupyter server, where you will run your analytics scripts. First, you will read about specific examples of how analytics is being employed by Accounting firms. Next, you will learn about the capabilities of the course Jupyter server, and how to create, edit, and run notebooks on the course server. After this, you will learn how to write Markdown formatted documents, which is an easy way to quickly write formatted text, including descriptive text inside a course notebook. Finally, you will begin learning about Python, the programming language used in this course for data analytics.

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5 videos (Total 29 minutos), 2 readings, 2 quizzes
2 lecturas
Module 1 Overview10m
Lesson 1-1 Readings10m
1 ejercicio de práctica
Module 1 Graded Quiz20m
Semana
2
8 horas para completar

Module 2: Introduction to Python

This module focuses on the basic features in the Python programming language that underlie most data analytics scripts. First, you will read about why accounting students should learn to write computer programs. Second, you will learn about basic data structures commonly used in Python programs. Third, you will learn how to write functions, which can be repeatedly called, in Python, and how to use them effectively in your own programs. Finally, you will learn how to control the execution process of your Python program by using conditional statements and looping constructs. At the conclusion of this module, you will be able to write Python scripts to perform basic data analytic tasks.

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5 videos (Total 29 minutos), 2 readings, 2 quizzes
5 videos
Introduction to Python Functions5m
Python Programming Concepts6m
2 lecturas
Module 2 Overview10m
Lesson 2-1 Readings10m
1 ejercicio de práctica
Module 2 Graded Quiz20m
Semana
3
8 horas para completar

Module 3: Introduction to Data Analysis

This module introduces fundamental concepts in data analysis. First, you will read a report from the Association of Accountants and Financial Professionals in Business that explores Big Data in Accountancy. Next, you will learn about the Unix file system, which is the operating system used for most big data processing (as well as Linux and Mac OSX desktops and many mobile phones). Second, you will learn how to read and write data to a file from within a Python program. Finally, you will learn about the Pandas Python module that can simplify many challenging data analysis tasks, and includes the DataFrame, which programmatically mimics many of the features of a traditional spreadsheet.

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5 videos (Total 29 minutos), 2 readings, 2 quizzes
5 videos
Python File I/O7m
Introduction to Pandas6m
2 lecturas
Module 3 Overview10m
Lesson 3-1 Readings10m
1 ejercicio de práctica
Module 3 Graded Quiz20m
Semana
4
8 horas para completar

Module 4: Statistical Data Analysis

This module introduces fundamental concepts in data analysis. First, you will read about how to perform many basic tasks in Excel by using the Pandas module in Python. Second, you will learn about the Numpy module, which provides support for fast numerical operations within Python. This module will focus on using Numpy with one-dimensional data (i.e., vectors or 1-D arrays), but a later module will explore using Numpy for higher-dimensional data. Third, you will learn about descriptive statistics, which can be used to characterize a data set by using a few specific measurements. Finally, you will learn about advanced functionality within the Pandas module including masking, grouping, stacking, and pivot tables.

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5 videos (Total 33 minutos), 2 readings, 2 quizzes
5 videos
Introduction to Descriptive Statistics10m
Advanced Pandas8m
2 lecturas
Module 4 Overview10m
Lesson 4-1 Readings10m
1 ejercicio de práctica
Module 4 Graded Quiz20m

Instructor

Avatar

Robert Brunner

Professor
Accountancy

Comienza a trabajar para obtener tu maestría

Este curso es parte del Master of Science in Accountancy (iMSA) completamente en línea de Universidad de Illinois en Urbana-Champaign. Si eres aceptado en el programa completo, tus cursos cuentan para tu título.

Acerca de Universidad de Illinois en Urbana-Champaign

The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs. ...

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando compras un Certificado, obtienes acceso a todos los materiales del curso, incluidas las tareas calificadas. Una vez que completes el curso, se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes participar del curso como oyente sin costo.

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