Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support

(DS-AI.AB1)/ISBN:9781644592915

This course includes
Lessons
TestPrep
Lab
Mentoring (Add-on)

Know the various types of data analytics with examples, products, services, and exercises by means of introducing artificial intelligence, machine learning, robotics, chatbots, Internet of Things, and Web/Internet-related enablers with uCertify’s course Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support.  

Lessons

15+ Lessons | 55+ Exercises | 280+ Quizzes | 492+ Flashcards | 492+ Glossary of terms

TestPrep

140+ Pre Assessment Questions | 140+ Post Assessment Questions |

Here's what you will learn

Download Course Outline

Lessons 1: Preface

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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Lessons 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

Hands-on LAB Activities (Performance Labs)

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

  • Identifying Types of Decision
  • Identifying Phases Involved in Decision Making
  • Understanding Business Intelligence
  • Identifying Enablers that belong to the Type of Business Analytics

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

  • Understanding Artificial Intelligence
  • Understanding AI Technologies

Nature of Data, Statistical Modeling, and Visualization

  • Identifying Steps Involved in Data Preprocessing
  • Understanding the Different Charts and Graphs

Data Mining Process, Methods, and Algorithms

  • Learning Data Mining Patterns
  • Identifying Tasks Involved in Data Mining Methods
  • Learning Data Mining Algorithms, Processes, and Methods

Machine-Learning Techniques for Predictive Analytics

  • Understanding Predictive Modeling
  • Identifying Activities Involved in an SVM Model

Deep Learning and Cognitive Computing

  • Understanding AI and its Advancements
  • Identifying Technologies Involved in Cognitive Computing and AI

Text Mining, Sentiment Analysis, and Social Analytics

  • Understanding Text Mining
  • Understanding Natural Language Processing

Prescriptive Analytics: Optimization and Simulation

  • Understanding Simulation
  • Understanding Visual Interaction Simulation

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

  • Understanding big data
  • Understanding big data and Cloud Computing

Robotics: Industrial and Consumer Applications

  • Understanding Robotics and AI
  • Understanding the Applications of Robotics

Group Decision Making, Collaborative Systems, and AI Support

  • Identifying the Software Tools
  • Understanding Group Decision Making

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

  • Understanding Chatbot

The Internet of Things as a Platform for Intelligent Applications

  • Understanding Sensor
  • Understanding Smart Home

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

  • Understanding the Implementation of Intelligent System