Towards A Data Mindset
Towards A Data Mindset, available at $44.99, has an average rating of 5, with 18 lectures, based on 1 reviews, and has 1004 subscribers.
You will learn about What is data mindset Are averages misleading Should I reward (or penalize) extreme performance Is a lag indicator a reliable measure What are end to end measures Are inferences from a sample reliable What are outliers How to forecast future performance easily This course is ideal for individuals who are Professionals or Analysts or Students or Anyone who is curious to explore this topic It is particularly useful for Professionals or Analysts or Students or Anyone who is curious to explore this topic.
Enroll now: Towards A Data Mindset
Summary
Title: Towards A Data Mindset
Price: $44.99
Average Rating: 5
Number of Lectures: 18
Number of Published Lectures: 18
Number of Curriculum Items: 18
Number of Published Curriculum Objects: 18
Original Price: $84.99
Quality Status: approved
Status: Live
What You Will Learn
- What is data mindset
- Are averages misleading
- Should I reward (or penalize) extreme performance
- Is a lag indicator a reliable measure
- What are end to end measures
- Are inferences from a sample reliable
- What are outliers
- How to forecast future performance easily
Who Should Attend
- Professionals
- Analysts
- Students
- Anyone who is curious to explore this topic
Target Audiences
- Professionals
- Analysts
- Students
- Anyone who is curious to explore this topic
In a world driven by data, developing a robust data mindset is crucial for anyone looking to make informed decisions and drive improvement. This course is designed to equip participants with the foundational concepts and tools needed to harness the power of data effectively.
Key Topics:
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What Gets Measured Gets Improved: Introduction to the concept of y=f(x) and understanding that every problem or opportunity can be framed as an equation. This sets the stage for a data-driven approach to improvement.
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Averages Can Be Misleading: Dive into measures of central tendency versus dispersion and explore the importance of understanding the full picture that data presents.
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Lead vs. Lag Indicators: Learn the difference between indicators that predict future performance and those that reflect past performance, and how to use them effectively.
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Measure It Right: Explore the concept of end-to-end measures versus silo measures and the importance of accurate measurement to avoid the illusion of success.
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Sample It Right: Understand the principles of sampling and how to ensure your data is representative and reliable.
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Correlation and Causation: Uncover the differences between correlation and causation and the pitfalls of confusing the two.
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Should You Reward Extreme Performance?: Discuss the concept of regression to the mean and its implications for performance evaluation.
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Outliers: Learn how to identify and interpret outliers in your data and their impact on analysis.
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Forecasting: Gain insights into basic forecasting techniques and how to predict future trends based on historical data.
This course is designed for anyone looking to enhance their ability to think critically about data and apply data-driven principles to their work or personal life. Whether you’re a manager, analyst, or just someone interested in the power of data, this course will provide you with the tools and mindset needed to unlock the insights hidden within data.
Disclaimer: Please note that this course is focused on developing a data mindset and is not a technical course on data analysis or data science. It is designed to provide practical insights and foundational concepts for thinking critically about data in decision-making processes.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: Characteristics of Data Mindset
Chapter 2: What Gets Measured Gets Improved
Lecture 1: What Gets Measured Gets Improved
Chapter 3: Is average a reliable measure
Lecture 1: Averages Can Be Misleading
Lecture 2: Case Studies
Lecture 3: Easy Computations in Excel
Chapter 4: Lead Vs Lag Indicators
Lecture 1: Lead Vs Lag Indicators
Lecture 2: Examples
Chapter 5: Measure it right and Sample it right!
Lecture 1: Measure it right
Lecture 2: More Examples
Lecture 3: Sample it right
Lecture 4: More Examples
Chapter 6: Correlation
Lecture 1: Introduction
Lecture 2: Correlation Vs Causation
Lecture 3: Should you reward extreme performance
Chapter 7: Logical Fallacies
Lecture 1: Logical Fallacies
Chapter 8: Outliers
Lecture 1: Outliers
Chapter 9: Look ahead!
Lecture 1: Forecasting
Instructors
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SeaportAi .
Artificial Intelligence and Business Transformation Experts
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 0 votes
- 3 stars: 0 votes
- 4 stars: 0 votes
- 5 stars: 1 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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