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**BaDshaH** · 07-11-2023, 09:10 AM

[Image: co-RTZq-Ktn-BPUkuudh-Yp-BXz-Vkjq-Sk-Agh0.jpg]

Published 7/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.41 GB | Duration: 4h 6m

Master Data-Driven Decisions: Experimentation, Prototyping, MVPs & Performance Analysis

[b]What you'll learn[/b]
Understand the significance of data-driven decision-making in shaping business strategies.
Identify opportunities for experimentation and prototyping within their organization.
Design experiments and test hypotheses to validate or refine business ideas.
Develop effective prototypes and grasp the concept of a Minimum Viable Product (MVP).
Measure and analyze performance using Key Performance Indicators (KPIs) and other relevant metrics.
Optimize and scale business solutions by leveraging data-driven insights.
Foster a culture of continuous improvement through ongoing experimentation, prototyping, and data analysis.

[b]Requirements[/b]
Designed for beginners: This course assumes no prior knowledge of data-driven business strategy and will cover all the essential concepts from the ground up.
Practical, hands-on approach: Through case studies, real-life examples, and guided exercises, students will learn the practical application of data-driven strategies in various business scenarios.
Accessible language and resources: Complex concepts will be explained using clear, straightforward language, making it easier for beginners to grasp the material. Additional resources will be provided for those interested in further exploration.

[b]Description[/b]
Discover the power of data-driven decision-making with our comprehensive course, "Data-Driven Business: Experiment, Prototype & Improve." We designed the course for both beginners and seasoned professionals alike. This course provides the practical skills to create, test, and refine innovative business strategies using a data-driven approach.We structured the course into the following high-level sections:Introduction to Data-driven Business StrategyExperimentation and Hypothesis TestingFundamentals of Data-driven PrototypingCreation of Minimum Viable Products MVPs)Improving Solutions and ScalingThroughout this engaging course, you'll learn how to identify opportunities for experimentation and prototyping, design experiments to validate or refute hypotheses, and develop practical prototypes to test your ideas in the real world. You'll also gain a deep understanding of the Minimum Viable Product (MVP) concept and its crucial role in driving business success.By measuring and analyzing performance using Key Performance Indicators (KPIs) and other relevant metrics, you'll learn to draw actionable insights and make informed decisions to optimize your business solutions. As you progress through the course, we will equip you with the tools and techniques needed to foster a culture of continuous improvement within your organization through experimentation, prototyping, and data analysis.Our expert instructor brings years of experience in data-related use cases across Europe and has helped thousands of students succeed professionally. With a blend of real-world examples, case studies, and guided exercises, you'll gain hands-on experience applying data-driven methodologies to various business scenarios.Whether you're an aspiring entrepreneur, business owner, manager, or business analyst, this course offers a solid foundation in data-driven business strategy and development, empowering you to drive meaningful change within your organization. Enrol now and start transforming your business strategy with data-driven insights today!

Overview
Section 1: Welcome to the course!
Lecture 1 Welcome & Course Overview
Section 2: Course Introduction and Data-driven mindset
Lecture 2 Chapter Overview
Lecture 3 The Importance of Data-Driven Decision Making
Lecture 4 The Cost of Changing a Product
Lecture 5 Observation vs. Experiment
Lecture 6 Experiment vs. Prototype vs. MVP
Section 3: Experimentation and Hypothesis Testing
Lecture 7 Chapter Overview
Lecture 8 Generating Ideas
Lecture 9 My Additional Techniques for Generating Ideas
Lecture 10 Evaluating and Selecting Ideas
Lecture 11 My Additional Thoughts on Selecting Ideas
Lecture 12 Decompose, Simplify and Refine
Lecture 13 Establish Your Metrics
Lecture 14 Developing Testable Hypotheses
Lecture 15 Introduction to A/B Testing
Lecture 16 A/B Testing Requires Domain Knowledge
Lecture 17 Analyzing Experimental Results and A/B Test Outcomes
Section 4: Fundamentals of Data-Driven Prototyping
Lecture 18 Chapter Overview
Lecture 19 Low- and High-Fidelity Prototypes
Lecture 20 How can I fail as quickly as possible?
Lecture 21 Prototyping is not just for UX
Lecture 22 Prototyping Techniques
Lecture 23 Data Collection Methods for Prototyping
Lecture 24 I love the yellow walkman!
Section 5: Minimum Viable Product (MVP)
Lecture 25 Chapter Overview
Lecture 26 The Concept of MVP
Lecture 27 From Experiments and Prototypes to MVPs
Lecture 28 Value Proposition and Product Assumptions
Lecture 29 Usability Tests and Exhaust Data
Lecture 30 Iterate, Iterate, Iterate
Lecture 31 MVPs are Not Just For Startups
Lecture 32 Know When to Quit Polishing
Section 6: Integrating Lessons Learned
Lecture 33 Chapter Overview
Lecture 34 The Experiment Is The Product
Lecture 35 The Experiment Card
Lecture 36 Embrace Negative Outcomes
Lecture 37 Embrace the Culture of Experimentation and Continuous Improvement
Lecture 38 Let's Summarize and Recap
Aspiring entrepreneurs: Individuals looking to start their own business and seeking guidance on how to make informed decisions based on data-driven insights.,Business owners and managers: Professionals responsible for the strategic direction of their company, aiming to optimize processes and performance through experimentation and prototyping.,Marketing and product managers: Professionals focused on product development, customer acquisition, and retention, seeking to enhance their skills in data-driven decision-making.,Business analysts and consultants: Individuals providing strategic advice to clients, looking to incorporate data-driven methodologies into their toolkit.,Professionals transitioning to business roles: Individuals from non-business backgrounds interested in gaining a solid foundation in data-driven business strategy and development.

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