Get to 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 Seven Learning’s course Analytics, Data Science & Artificial Intelligence: Systems for Decision Support.
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, Data Science, Artificial Intelligence: Systems for Decision Support
- 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
- Discussion
- Exercises
Lessons 3: Artificial Intelligence Concepts, Drivers, Major Technologies, and Business Applications
- 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)
- Exercises
Lessons 4: Nature of Data, Statistical Modelling, and Visualisation
- SiriusXM Attracts and Engages Radio Consumers with Data-Driven Marketing
- Nature of Data
- Simple Taxonomy of Data
- Art and Science of Data Pre-processing
- Statistical Modeling for Business Analytics
- Regression Modelling for Inferential Statistics
- Business Reporting
- Data Visualisation
- Different Types of Charts and Graphs
- Emergence of Visual Analytics
- Information Dashboards
- References
Lessons 5: Data Mining Process, Methods, and Algorithms
- 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
Lessons 6: Machine-Learning Techniques for Predictive Analytics
- Predictive Modelling 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 Neighbour Method for Prediction
- Naïve Bayes Method for Classification
- Bayesian Networks
- Ensemble Modelling
Lessons 7: Deep Learning and Cognitive Computing
- 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
Lessons 8: Text Mining, Sentiment Analysis, and Social Analytics
- 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
Lessons 9: Prescriptive Analytics: Optimisation and Simulation
- Model-Based Decision Making
- Structure of Mathematical Models for Decision Support
- Certainty, Uncertainty, and Risk
- Decision Modelling with Spreadsheets
- Mathematical Programming Optimisation
- Multiple Goals, Sensitivity Analysis, What-If Analysis, and Goal Seeking
- Decision Analysis with Decision Tables and Decision Trees
- Introduction to Simulation
- Visual Interactive Simulation
Lessons 10: Big Data, Cloud Computing, and Location Analytics: Concepts and Tools
- Analysing 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 Organisations
Lessons 11: Robotics: Industrial and Consumer Applications
- 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
- Questions for Discussion
Lessons 12: Group Decision Making, Collaborative Systems, and AI Support
- Hendrick Motorsports Excels with Collaborative Teams
- Making Decisions in Groups: Characteristics, Process, Benefits, and Dysfunctions
- Supporting Group Work and Team Collaboration with Computerised Systems
- Electronic Support for Group Communication and Collaboration
- Direct Computerised 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
Lessons 13: Knowledge Systems: Expert Systems, Recommenders,Virtual Personal Assistants, and Robo Advisors
- 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
Lessons 14: The Internet of Things as a Platform for Intelligent Applications
- 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
Lessons 15: Implementation Issues: From Ethics and Privacy to Organisational and Societal Impacts
- Implementing Intelligent Systems: An Overview
- Legal, Privacy, and Ethical Issues
- Successful Deployment of Intelligent Systems
- Impacts of Intelligent Systems on Organisations
- Impacts on Jobs and Work
- Potential Dangers of Robots, AI, and Analytical Modelling
- Relevant Technology Trends
- Future of Intelligent Systems
Hands-on LAB Activities (Performance Labs)
Overview of Business Intelligence, Analytics, Data Science, Artificial 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 Modelling, and Visualisation
- 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: Optimisation 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 Organisational and Societal Impacts
- Understanding the Implementation of Intelligent System
Exam FAQs
FAQ's are not Available for this course.Summary
Standard:
Lessons:
15+ Lessons | 55+ Exercises | 280+ Quizzes | 492+ Flashcards | 492+ Glossary of Terms
Delivery Method:
Online
Language:
English