Acerca de este Curso
3.8
150 calificaciones
49 revisiones
Welcome to the second course in the Data Analytics for Business specialization! This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business. You’ll also learn how to summarize and visualize datasets using plots so that you can present your results in a compelling and meaningful way. We will use a practical predictive modeling software, XLMiner, which is a popular Excel plug-in. This course is designed for anyone who is interested in using data to gain insights and make better business decisions. The techniques discussed are applied in all functional areas within business organizations including accounting, finance, human resource management, marketing, operations, and strategic planning. The expected prerequisites for this course include a prior working knowledge of Excel, introductory level algebra, and basic statistics....
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Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Calendar

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Clock

Approx. 19 hours to complete

Sugerido: 5 hours/week...
Comment Dots

English

Subtítulos: English, Korean...

Habilidades que obtendrás

Regression AnalysisData CleansingPredictive ModellingExploratory Data Analysis
Globe

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Calendar

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Clock

Approx. 19 hours to complete

Sugerido: 5 hours/week...
Comment Dots

English

Subtítulos: English, Korean...

Programa - Qué aprenderás en este curso

Week
1
Clock
4 horas para completar

Exploratory Data Analysis and Visualizations

At the end of this module students will be able to: 1. Carry out exploratory data analysis to gain insights and prepare data for predictive modeling 2. Summarize and visualize datasets using appropriate tools 3. Identify modeling techniques for prediction of continuous and discrete outcomes. 4. Explore datasets using Excel 5. Explain and perform several common data preprocessing steps 6. Choose appropriate graphs to explore and display datasets ...
Reading
8 videos (Total: 38 min), 1 reading, 3 quizzes
Video8 videos
0. Introduction to the Module. Why Exploratory Data Analysis is Important3m
1. Data Cleanup and Transformation4m
2. Dealing With Missing Values6m
3. Dealing with Outliers3m
4. Adding and Removing Variables4m
5. Common Graphs7m
6. What is Good Data Visualization?4m
Reading1 lectura
Register for Analytic Solver Platform for Education (ASPE)10m
Quiz2 ejercicios de práctica
Week 1 Quiz48m
Week 1 Application Assignment 1 (optional): Data Cleanup6m
Week
2
Clock
2 horas para completar

Predicting a Continuous Variable

This module introduces regression techniques to predict the value of continuous variables. Some fundamental concepts of predictive modeling are covered, including cross-validation, model selection, and overfitting. You will also learn how to build predictive models using the software tool XLMiner....
Reading
8 videos (Total: 41 min), 2 quizzes
Video8 videos
1. Introduction to Linear Regression8m
2. Assessing Predictive Accuracy Using Cross-Validation5m
3. Multiple Regression4m
4. Improving Model Fit3m
5. Model Selection3m
6. Challenges of Predictive Modeling5m
7. How to Build a Model using XLMiner8m
Quiz2 ejercicios de práctica
Week 2 Quiz18m
Week 2 Application Assignment40m
Week
3
Clock
1 hora para completar

Predicting a Binary Outcome

This module introduces logistic regression models to predict the value of binary variables. Unlike continuous variables, a binary variable can only take two different values and predicting its value is commonly called classification. Several important concepts regarding classification are discussed, including cross validation and confusion matrix, cost sensitive classification, and ROC curves. You will also learn how to build classification models using the software tool XLMiner....
Reading
8 videos (Total: 33 min), 2 quizzes
Video8 videos
1. Introduction to Logistic Regression4m
2. Building Logistic Regression Model6m
3. Multiple Logistic Regression3m
4. Cross Validation and Confusion Matrix5m
5. Cost Sensitive Classification2m
6. Comparing Models Independent of Costs and Cutoffs3m
7. Building Logistic Regression Models using XLMiner6m
Quiz2 ejercicios de práctica
Week 3 Quiz14m
Week 3 Application Assignment26m
Week
4
Clock
4 horas para completar

Trees and Other Predictive Models

This module introduces more advanced predictive models, including trees and neural networks. Both trees and neural networks can be used to predict continuous or binary variables. You will also learn how to build trees and neural networks using the software tool XLMiner....
Reading
8 videos (Total: 32 min), 4 quizzes
Video8 videos
1. Introduction to Trees2m
2. Classification Trees5m
3. Regression Trees2m
4. Bagging, Boosting, Random Forest4m
5. Building Trees with XLMiner5m
6. Neural Networks5m
7. Building Neural Networks using XLMiner4m
Quiz3 ejercicios de práctica
Week 4 Quiz12m
Week 4 Application Assignment10m
Final Course Assignment Quiz40m
3.8

Principales revisiones

por HANov 20th 2017

this course teach you about the technical of using tools for predictive modeling. very useful for you who want to learn the fundamental of analytics.

por SKFeb 16th 2017

Its an excellent course and thanks to Professor for making this course so practice oriented.

Instructor

Dan Zhang

Professor
Leeds School of Business

Acerca de University of Colorado Boulder

CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies....

Acerca del programa especializado Advanced Business Analytics

The Advanced Business Analytics Specialization brings together academic professionals and experienced practitioners to share real world data analytics skills you can use to grow your business, increase profits, and create maximum value for your shareholders. Learners gain practical skills in extracting and manipulating data using SQL code, executing statistical methods for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results. The problems faced by decision makers in today’s competitive business environment are complex. Achieve a clear competitive advantage by using data to explain the performance of a business, evaluate different courses of action, and employ a structured approach to business problem-solving. Check out a one-minute video about this specialization to learn more!...
Advanced Business Analytics

Preguntas Frecuentes

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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