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AI Applications for Business

(DV-MIS548.AB1)
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1

Preface

  • What’s New in the Eleventh Edition?
  • Plan of the Course
  • Resources, Links, and the Teradata University Network Connection
2

Overview of Business Intelligence, Analytics, Da...icial Intelligence: Systems for Decision Support

  • Opening Vignette: How Intelligent Systems Work for KONE Elevators and Escalators Company
  • Changing Business Environments and Evolving Needs for Decision Support and Analytics
  • Decision-Making Processes and Computerized Decision Support Framework
  • Evolution of Computerized Decision Support to Business Intelligence/Analytics/Data Science
  • Analytics Overview
  • Analytics Examples in Selected Domains
  • Artificial Intelligence Overview
  • Convergence of Analytics and AI
  • Overview of the Analytics Ecosystem
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
3

Artificial Intelligence Concepts, Drivers, Major Technologies, and Business Applications

  • Opening Vignette: INRIX Solves Transportation Problems
  • Introduction to Artificial Intelligence
  • Human and Computer Intelligence
  • Major AI Technologies and Some Derivatives
  • AI Support for Decision Making
  • AI Applications in Accounting
  • AI Applications in Financial Services
  • AI in Human Resource Management (HRM)
  • AI in Marketing, Advertising, and CRM
  • AI Applications in Production-Operation Management (POM)
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
4

Nature of Data, Statistical Modeling, and Visualization

  • Opening Vignette: SiriusXM Attracts and Engages ...on of Radio Consumers with Data-Driven Marketing
  • Nature of Data
  • Simple Taxonomy of Data
  • Art and Science of Data Preprocessing
  • Statistical Modeling for Business Analytics
  • Regression Modeling for Inferential Statistics
  • Business Reporting
  • Data Visualization
  • Different Types of Charts and Graphs
  • Emergence of Visual Analytics
  • Information Dashboards
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
5

Data Mining Process, Methods, and Algorithms

  • Opening Vignette: Miami-Dade Police Department I... Predictive Analytics to Foresee and Fight Crime
  • Data Mining Concepts
  • Data Mining Applications
  • Data Mining Process
  • Data Mining Methods
  • Data Mining Software Tools
  • Data Mining Privacy Issues, Myths, and Blunders
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
6

Machine-Learning Techniques for Predictive Analytics

  • Opening Vignette: Predictive Modeling Helps Better Understand and Manage Complex Medical Procedures
  • Basic Concepts of Neural Networks
  • Neural Network Architectures
  • Support Vector Machines
  • Process-Based Approach to the Use of SVM
  • Nearest Neighbor Method for Prediction
  • Naïve Bayes Method for Classification
  • Bayesian Networks
  • Ensemble Modeling
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
7

Deep Learning and Cognitive Computing

  • Opening Vignette: Fighting Fraud with Deep Learning and Artificial Intelligence
  • Introduction to Deep Learning
  • Basics of “Shallow” Neural Networks
  • Process of Developing Neural Network–Based Systems
  • Illuminating the Black Box of ANN
  • Deep Neural Networks
  • Convolutional Neural Networks
  • Recurrent Networks and Long Short-Term Memory Networks
  • Computer Frameworks for Implementation of Deep Learning
  • Cognitive Computing
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
8

Text Mining, Sentiment Analysis, and Social Analytics

  • Opening Vignette: Amadori Group Converts Consumer Sentiments into Near-Real-Time Sales
  • Text Analytics and Text Mining Overview
  • Natural Language Processing (NLP)
  • Text Mining Applications
  • Text Mining Process
  • Sentiment Analysis
  • Web Mining Overview
  • Search Engines
  • Web Usage Mining (Web Analytics)
  • Social Analytics
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
9

Prescriptive Analytics: Optimization and Simulation

  • Opening Vignette: School District of Philadelphi...ptimal Solution for Awarding Bus Route Contracts
  • Model-Based Decision Making
  • Structure of Mathematical Models for Decision Support
  • Certainty, Uncertainty, and Risk
  • Decision Modeling with Spreadsheets
  • Mathematical Programming Optimization
  • Multiple Goals, Sensitivity Analysis, What-If Analysis, and Goal Seeking
  • Decision Analysis with Decision Tables and Decision Trees
  • Introduction to Simulation
  • Visual Interactive Simulation
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
10

Big Data, Cloud Computing, and Location Analytics: Concepts and Tools

  • Opening Vignette: Analyzing Customer Churn in a Telecom Company Using Big Data Methods
  • Definition of Big Data
  • Fundamentals of Big Data Analytics
  • Big Data Technologies
  • Big Data and Data Warehousing
  • In-Memory Analytics and Apache SparkTM
  • Big Data and Stream Analytics
  • Big Data Vendors and Platforms
  • Cloud Computing and Business Analytics
  • Location-Based Analytics for Organizations
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
11

Robotics: Industrial and Consumer Applications

  • Opening Vignette: Robots Provide Emotional Support to Patients and Children
  • Overview of Robotics
  • History of Robotics
  • Illustrative Applications of Robotics
  • Components of Robots
  • Various Categories of Robots
  • Autonomous Cars: Robots in Motion
  • Impact of Robots on Current and Future Jobs
  • Legal implications of Robots and Artificial Intelligence
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
12

Group Decision Making, Collaborative Systems, and AI Support

  • Opening Vignette: Hendrick Motorsports Excels with Collaborative Teams
  • Making Decisions in Groups: Characteristics, Process, Benefits, and Dysfunctions
  • Supporting Group Work and Team Collaboration with Computerized Systems
  • Electronic Support for Group Communication and Collaboration
  • Direct Computerized Support for Group Decision Making
  • Collective Intelligence and Collaborative Intelligence
  • Crowdsourcing as a Method for Decision Support
  • Artificial Intelligence and Swarm AI Support of Team Collaboration and Group Decision Making
  • Human–Machine Collaboration and Teams of Robots
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
13

Knowledge Systems: Expert Systems, Recommenders,..., Virtual Personal Assistants, and Robo Advisors

  • Opening Vignette: Sephora Excels with Chatbots
  • Expert Systems and Recommenders
  • Concepts, Drivers, and Benefits of Chatbots
  • Enterprise Chatbots
  • Virtual Personal Assistants
  • Chatbots as Professional Advisors (Robo Advisors)
  • Implementation Issues
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
14

The Internet of Things as a Platform for Intelligent Applications

  • Opening Vignette: CNH Industrial Uses the Internet of Things to Excel
  • Essentials of IoT
  • Major Benefits and Drivers of IoT
  • How IoT Works
  • Sensors and Their Role in IoT
  • Selected IoT Applications
  • Smart Homes and Appliances
  • Smart Cities and Factories
  • Autonomous (Self-Driving) Vehicles
  • Implementing IoT and Managerial Considerations
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
15

Implementation Issues: From Ethics and Privacy to Organizational and Societal Impacts

  • Opening Vignette: Why Did Uber Pay $245 Million to Waymo?
  • Implementing Intelligent Systems: An Overview
  • Legal, Privacy, and Ethical Issues
  • Successful Deployment of Intelligent Systems
  • Impacts of Intelligent Systems on Organizations
  • Impacts on Jobs and Work
  • Potential Dangers of Robots, AI, and Analytical Modeling
  • Relevant Technology Trends
  • Future of Intelligent Systems
  • Lesson Highlights
  • Questions for Discussion
  • Exercises
  • References
A

Appendix: ChatGPT Training

  • Instructor Introduction
  • Download Course Resources
  • Module 1 - ChatGPT Fundamentals
  • 1.1 What is ChatGPT
  • 1.2 Use Cases for ChatGPT
  • 1.3 Role of ChatGPT
  • 1.4 Future of ChatGPT
  • 1.5 ChatGPT Statistics, Facts & Trends
  • 1.6 Limitations
  • 1.7 What is a Chatbot
  • 1.8 Understanding AI-ML
  • 1.9 Demonstration - Tools to Use with ChatGPT
  • 1.10 Business Benefits
  • 1.11 Whiteboard - How it all works
  • 1.12 Demonstration - How to Get Started with ChatGPT
  • 1.13 Demonstration - Example Prompts
  • 1.14 Discussion - ChatGPT Performance Issues
  • Module 1 Summary
  • Module 2 - ChatGPT Prompt Demonstrations
  • 2.1 What is a Prompt
  • 2.2 Best practices for writing prompts
  • 2.3 Prompt Demonstration - Asking Questions
  • 2.4 Prompt Demonstration - Top Ten Lists
  • 2.5 Prompt Demonstration - Long Form Docs
  • 2.6 Prompt Demonstration - Complex Form and Code
  • 2.7 Prompt Demonstration - Feedback
  • 2.8 Prompt Demonstration - Content Modification
  • 2.9 Prompt Demonstration - Instruction Generation
  • 2.10 Prompt Demonstration - Information Extraction
  • 2.11 Prompt Demonstration - Writing Computer Code
  • 2.12 Prompt Demonstration - Solving Math Problems
  • 2.13 Prompt Demonstration - Create YT Video Outline
  • 2.14 Prompt Demonstration - Write a Blog Article
  • 2.15 Prompt Demonstration - SEO Keywords
  • 2.16 Comparing Google Bard vs ChatGPT
  • Module 2 Summary
  • Course Closeout

1

Overview of Business Intelligence, Analytics, Da...icial Intelligence: Systems for Decision Support

  • Long Form Content Prompt I
2

Nature of Data, Statistical Modeling, and Visualization

  • Instruction Generation Prompt
3

Data Mining Process, Methods, and Algorithms

  • SEO Keywords Prompt
  • Long Form Content Prompt II
  • Complex Form and Code Prompt
4

Machine-Learning Techniques for Predictive Analytics

  • Information Extraction Prompt
5

Deep Learning and Cognitive Computing

  • Writing Computer Code Prompt
6

Text Mining, Sentiment Analysis, and Social Analytics

  • Long Form Content Prompt III
7

Prescriptive Analytics: Optimization and Simulation

  • Solving Math Problems Prompt
  • Asking Questions Prompt
8

Big Data, Cloud Computing, and Location Analytics: Concepts and Tools

  • Content Modification Prompt
9

Robotics: Industrial and Consumer Applications

  • Writing a Blog Article Prompt
  • Generating Feedback Prompt
10

Knowledge Systems: Expert Systems, Recommenders,..., Virtual Personal Assistants, and Robo Advisors

  • Ten Lists Prompt
11

Implementation Issues: From Ethics and Privacy to Organizational and Societal Impacts

  • Creating YT Video Outline Prompt

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