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Data Analytics Foundations for Accountancy II
  • Level Foundation
  • المدة 70 ساعات hours
  • الطبع بواسطة University of Illinois Urbana-Champaign
  • Offered by

عن

Welcome to Data Analytics Foundations for Accountancy II! 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!

الوحدات

About the Course

    • 3 Videos
    • 3 Readings
    • 1 Quiz
Show info about module content

3 Videos

  • Welcome to Data Analytics Foundations for Accountancy II
  • Meet Professor Brunner
  • Learn on Your Terms

3 Readings

  • Syllabus
  • About the Discussion Forums
  • Online Education at Gies College of Business

1 Quiz

  • Orientation Quiz

About Your Classmates

    • 2 Readings
    • 1 Discussion
Show info about module content

1 Discussions

  • Getting to Know Your Classmates

2 Readings

  • Updating Your Profile
  • Social Media

Module 1 Information

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Module 1

1 Readings

  • Module 1 Overview

Lesson 1-1: Artificial Intelligence and Accountancy

    • 1 Readings
Show info about module content

1 Readings

  • Lesson 1-1 Readings

Lesson 1-2: Introduction to Machine Learning

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Machine Learning Notebook

1 Videos

  • Introduction to Machine Learning

1 Readings

  • Lesson 1-2 Readings

Lesson 1-3: Introduction to Linear Regression

    • 1 Videos
    • 1 Lab
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1 Labs

  • Introduction to Linear Regression Notebook

1 Videos

  • Introduction to Linear Regression

Lesson 1-4: Introduction to k-Nearest Neighbors

    • 1 Videos
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to k-nn Notebook

1 Videos

  • Introduction to k-nn

Module 1 Graded Activities

    • 1 Quiz
    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Module 1 Programming Assignment

1 Labs

  • Module 1 Programming Assignment Notebook

1 Quiz

  • Module 1 Graded Quiz

Module 2 Information

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Module 2

1 Readings

  • Module 2 Overview

Lesson 2-1: Digital Supply Chains

    • 1 Videos
    • 1 Readings
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1 Videos

  • Introduction to Fundamental Algorithms

1 Readings

  • Lesson 2-1 Readings

Lesson 2-2: Introduction to Logistic Regression

    • 1 Videos
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Logistic Regression Notebook

1 Videos

  • Introduction to Logistics Regression

Lesson 2-3: Introduction to Decision Trees

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Decision Trees Notebook

1 Videos

  • Introduction to Decision Trees

1 Readings

  • Lesson 2-3 Readings

Lesson 2-4: Introduction to Support Vector Machine

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Support Vector Machine Notebook

1 Videos

  • Introduction to Support Vector Machine

1 Readings

  • Lesson 2-4 Readings

Module 2 Graded Activities

    • 1 Quiz
    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Module 2 Programming Assignment

1 Labs

  • Module 2 Programming Assignment Notebook

1 Quiz

  • Module 2 Graded Quiz

Module 3 Information

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Module 3

1 Readings

  • Module 3 Overview

Lesson 3-1: Production Data Analytics

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Modeling Success

1 Readings

  • Lesson 3-1 Readings

Lesson 3-2: Introduction to Bagging

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Bagging Notebook

1 Videos

  • Introduction to Bagging

1 Readings

  • Lesson 3-2 Readings

Lesson 3-3: Introduction to Boosting

    • 1 Videos
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Boosting Notebook

1 Videos

  • Introduction to Boosting

Lesson 3-4: Introduction to Pipelines

    • 1 Videos
    • 1 Lab
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1 Labs

  • Practical Concerns in Machine Learning

1 Videos

  • Introduction to ML Pipelines

Module 3 Graded Activities

    • 1 Quiz
    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Module 3 Programming Assignment

1 Labs

  • Module 3 Programming Assignment Notebook

1 Quiz

  • Module 3 Graded Quiz

Module 4 Information

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Module 4

1 Readings

  • Module 4 Overview

Lesson 4-1: Introduction to Overfitting

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Overfitting

1 Readings

  • Lesson 4-1 Readings

Lesson 4-2: Introduction to Cross-Validation

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Cross-Validation Notebook

1 Videos

  • Introduction to Cross-Validation

1 Readings

  • Lesson 4-2 Readings

Lesson 4-3: Introduction to Model-Selection

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Model-Selection Notebook

1 Videos

  • Introduction to Model-Selection

1 Readings

  • Lesson 4-3 Readings

Lesson 4-4: Introduction to Regularization

    • 1 Videos
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Regularization Notebook

1 Videos

  • Introduction to Regularization

Module 4 Graded Activities

    • 1 Quiz
    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Module 4 Programming Assignment

1 Labs

  • Module 4 Programming Assignment Notebook

1 Quiz

  • Module 4 Graded Quiz

Module 5 Information

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Module 5

1 Readings

  • Module 5 Overview

Lesson 5-1: Machine Learning Workflows

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Practical Machine Learning

1 Readings

  • Lesson 5-1 Readings

Lesson 5-2: Introduction to Naive Bayes

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Naive Bayes Notebook

1 Videos

  • Introduction to Naive Bayes

1 Readings

  • Lesson 5-2 Readings

Lesson 5-3: Introduction to Gaussian Processes

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Gaussian Processes Notebook

1 Videos

  • Introduction to Gaussian Processes

1 Readings

  • Lesson 5-3 Readings

Module 5 Graded Activities

    • 1 Quiz
    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Module 5 Programming Assignment

1 Labs

  • Module 5 Programming Assignment Notebook

1 Quiz

  • Module 5 Graded Quiz

Module 6 Information

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Module 6

1 Readings

  • Module 6 Overview

Lesson 6-1: Practical Concerns with Machine Learning

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Practical Concerns with Machine Learning

1 Readings

  • Lesson 6-1 Readings

Lesson 6-2: Introduction to Feature Selection

    • 1 Videos
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Feature Selection Notebook

1 Videos

  • Introduction to Feature Selection

Lesson 6-3: Introduction to Dimensional Reduction

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Dimension Reduction Notebook

1 Videos

  • Introduction to Dimension Reduction

1 Readings

  • Lesson 6-3 Readings

Lesson 6-4: Introduction to Manifold Learning

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Manifold Learning Notebook

1 Videos

  • Introduction to Manifold Learning

1 Readings

  • Lesson 6-4 Readings

Module 6 Graded Activities

    • 1 Quiz
    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Module 6 Programming Assignment

1 Labs

  • Module 6 Programming Assignment Notebook

1 Quiz

  • Module 6 Graded Quiz

Module 7 Information

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Module 7

1 Readings

  • Module 7 Overview

Lesson 7-1: Introduction to Clustering

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Clustering

1 Readings

  • Lesson 7-1 Readings

Lesson 7-2: Introduction to Spatial Clustering

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Spatial Clustering Notebook

1 Videos

  • Introduction to Spatial Clustering

1 Readings

  • Lesson 7-2 Readings

Lesson 7-3: Introduction to Density-Based Clustering

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Density-Based Clustering Notebook

1 Videos

  • Introduction to Density-Based Clustering

1 Readings

  • Lesson 7-3 Readings

Lesson 7-4: Introduction to Mixture Models

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Introduction to Mixture Models Notebook

1 Videos

  • Introduction to Mixture Models

1 Readings

  • Lesson 7-4 Readings

Module 7 Graded Activities

    • 1 Quiz
    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Module 7 Programming Assignment

1 Labs

  • Module 7 Programming Assignment Notebook

1 Quiz

  • Module 7 Graded Quiz

Module 8 Information

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Module 8

1 Readings

  • Module 8 Overview

Lesson 8-1: Introduction to Anomaly Detection

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • Introduction to Anomaly Detection

1 Readings

  • Lesson 8-1 Readings

Lesson 8-2: Statistical Anomaly Detection

    • 1 Videos
    • 1 Lab
Show info about module content

1 Labs

  • Statistical Anomaly Detection Notebook

1 Videos

  • Statistical Anomaly Detection

Lesson 8-3: Machine Learning and Anomaly Detection

    • 1 Videos
    • 1 Lab
Show info about module content

1 Labs

  • Machine Learning and Anomaly Detection Notebook

1 Videos

  • Machine Learning and Anomaly Detection

Module 8 Graded Activities

    • 2 Readings
    • 1 Quiz
    • 1 Plugin
    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Module 8 Programming Assignment

1 Labs

  • Module 8 Programming Assignment Notebook

2 Readings

  • Congratulations on completing the course!
  • Get Your Course Certificate

1 Quiz

  • Module 8 Graded Quiz

Auto Summary

"Data Analytics Foundations for Accountancy II," offered by Coursera, is a foundational course in Business & Management, led by an experienced instructor. The course spans 4200 minutes and offers interactive discussions and assignments. Available through Starter and Professional subscriptions, it's ideal for aspiring accountants and business professionals looking to enhance their data analytics skills. Join now to engage with a vibrant learning community and advance your career.

Robert J. Brunner
Instructor

Robert J. Brunner