Explore decision-making through Decision Models and science. Practice using decision trees, influence diagrams, and probabilistic models to analyze uncertainties. 

Introduction

Choosing a cloud provider for NextGen

Empowering NextGen with Decision Models

Introduction to Decision Science

Identifying key principles of Decision Science

Decision Science for a new inventory system

Introduction to analysis methods

SWOT analysis in a retail giant

Analyzing an expansion strategy for Market Prime

Decisive Expansion: AdventureGear's youth move

Foundations of Decision Modeling

Discover effective risk management and optimization techniques to enhance decision outcomes. 

Constructing Decision Models

Decision Models in a supplier crisis

Probabilities in Decision Models

Exploring Probabilistic Models

Rolling twice: Probabilities with dice

Data analytics for Decision Models

Unraveling data analytics

Data analytics journey

Data analytics to improve customer satisfaction

Sensitivity Analysis for Decision Models

The value of Sensitivity Analysis

Sensitivity Analysis in household budget

Sensitivity Analysis for the Jones Household

Options

Alternatives

Uncertainties

Outcomes

Decision tools in a getaway dilemma

Techniques and Tools for Decision Modeling

Lastly, dive into strategic decision-making, autonomous decision systems, and their advanced applications.

Risk and uncertainty management

The value of managing risks and uncertainties

Assessing risks in a hospital's CRM project

Introduction to optimization

Essential principles of optimization

Sorting the optimization journey

Enterprise decision-making

Assisting in an acquisition

Ethics in an enterprise decision

Autonomous decision-making

Foundations of autonomous decision-making

Levels of autonomous systems

Wrap-up

Advanced Applications and Strategic Decisions

Did you know that an average adult makes anywhere from 20,000 to 35,000 decisions each day? Enhance your decision-making skills with this foundational course on Decision Models and discover its importance in navigating uncertainties and risks. Learn to construct and analyze Decision Models using tools like decision trees, influence diagrams, and sensitivity analysis. Gain practical skills in integrating data analytics to optimize outcomes and make strategic decisions aligned with organizational goals. Perfect for anyone looking to elevate decision-making abilities in a data-driven world.

<h2>Foundations of Decision Models</h2>
<p>Decision-making lies at the core of human existence. In today's data-driven world, where information overload is the norm, the ability to make informed decisions is in high demand. This dynamic course explores essential decision modeling techniques, empowering you with the skills to make confident choices.</p>
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<h2>Discover the Main Decision Factors</h2>
<p>This decision modeling course is designed for anyone interested in decision science, from curious individuals to professionals engaged in decision-making processes. No prior experience is required. The course covers essential concepts and strategies to enhance decision-making skills applicable across diverse industries and scenarios.</p>
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<p>The first part of the course builds a foundation by identifying the main factors in a decision and navigating the decision-making process with analysis methods to make informed decisions.</p>
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<h2>Explore Decision Models</h2>
<p>The course offers a comprehensive guide to decision modeling, featuring essential methods and tools such as decision trees, influence diagrams, probabilistic models, and sensitivity analysis using data analytics. Participants will gain the skills to construct, analyze, and optimize decision models to enable informed and effective decision-making.</p>
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<h2>Risk Management and Advanced Applications</h2>
<p>Finally, the course covers risk management and optimization techniques essential for strategic decision-making. Additionally, it explores autonomous decision systems and their advanced applications.</p>
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Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.

Decoding Decision Modeling

Decision Science Fundamentals

Gather raw data from various sources, including customer feedback forms, website analytics, and sales transactions.

Store the gathered data in a centralized database and ensure it is in a consistent format.

Remove duplicates, correct errors, and handle missing values to ensure the data is accurate and reliable.

Transform the cleaned data into a format suitable for analysis, such as aggregating data by customer segments or time periods.

Generate insights from the transformed data to identify patterns that can help the identification of gaps and improve customer satisfaction.

Data analytics to improve customer satisfaction

Decoding Decision Modeling

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