Explore the core principles of decision science and its significance in modern business. Develop a foundational understanding of decision modeling techniques, problem-framing strategies, and the ethical considerations surrounding data-driven decision-making.

Introduction to Decision Science

Descriptive versus prescriptive analytics

Options

Confirmation bias

Anchoring bias

Loss aversion

Common biases in Decision Science

Decision-making process

Ordering the steps in decision-making

Introduction to decision-making

Decision-making techniques

Expected value

Decision tree 

Game theory

Decision-making frameworks

Framing and problem definition

Project stakeholders

Business problem context

5 Whys

Fishbone diagram

SMART Goals

Problem framing techniques

Ethical considerations in decision-making

Spotting fairness failures

Fairness

Privacy and Security

Transparency and Reproducibility

Decision Science Ethics

Foundations of Decision Science

Gain practical skills in implementing decision science projects efficiently. Learn to define success criteria, assess data sources, perform quality checks, select relevant features, prioritize models, and foster a data-driven culture within your organization.

Defining success

Minimum Viable Product

Databases and quality checks

Location, location… database?

Which data delivers?

Model prioritization

Baseline before brilliance

Tweak the data, boost the model

Tracking performance

Matching metrics

Metrics to meaning

Efficient Decision Science

Discover the diverse applications of decision science across various industries, including marketing, finance, and operations. Master effective communication strategies for presenting data-driven insights to stakeholders and build consensus around data-informed decisions. Explore future trends and advancements in the field.

Decision science in business

What counts as decision science?

Scoping for success

Communicating data-driven insights

Storytelling success

Speak their language

Building a data-driven culture

Culture check

Step by step

The future of decision science

Future-forward or falling behind?

New frontiers

Wrap up

Decision Science in Action

Are you working in data science and looking to make a real impact on business decisions? This course is here to help!
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You’ll learn how to align data with strategic goals by mastering key decision science concepts and frameworks. Gain the skills to efficiently solve problems, communicate insights effectively, and foster a data-driven culture within your organization.

<h2>Learn Decision Science Fundamentals!</h2>
<p>Dive into the fundamentals of decision science, exploring core principles, methodologies, and real-world applications. You will develop a strong understanding of decision modeling, problem framing, and the ethical considerations involved in data-driven decision-making.</p>

<h2>Implement Like a Pro</h2>
<p>You will discover how to efficiently implement decision science projects, from defining clear success criteria to building a data-driven culture within your organization. The next chapter will equip you with practical techniques for data source assessment, quality checks, feature selection, and model prioritization.</p>

<h2>Master Decision Science Applications</h2>
<p>Expand your knowledge by exploring the diverse applications of decision science across various industries, including marketing, finance, and operations. You will practice and develop effective communication strategies to present data-driven insights to stakeholders and build consensus around data-informed decisions.</p>

<h2>Explore Future Trends</h2>
<p>Stay ahead of the curve by examining emerging trends and advancements in decision science. You will gain valuable insights into the integration of artificial intelligence (AI) in decision-making, the power of big data analytics, and the evolving role of human-in-the-loop decision-making.</p>


Solidify your decision science skills by designing data-informed frameworks and implementing efficient solutions. 

Demystifying Decision Science

Facial recognition software used by law enforcement agencies exhibits higher error rates for people of color

A targeted advertising platform shows ads for high-paying job opportunities primarily to men

A period-tracking app sold users' sensitive health data to third-party companies without their explicit consent

A financial institution was compromised by hackers, resulting in the theft of millions of customers' data

A self-driving car company did not disclose the limitations of their vehicle's autonomous driving system

A team of data scientists relies on undocumented data cleaning procedures

Decision Science Ethics

Demystifying Decision Science

Hands-on interactive exercise