| File Name: | Data Science for Strategic Advantage Session 1 |
| Content Source: | https://www.udemy.com/course/data-science-for-strategic-advantage-session-1 |
| Genre / Category: | Programming |
| File Size : | 1.1 GB |
| Publisher: | udemy |
| Updated and Published: | December 1, 2025 |
This course is the English version of the “Practical Data Science Lecture Series,” originally published in Japanese. Artificial intelligence was used to assist with translation from Japanese to English and for narration of the explanations. All course structure, slides, and explanatory content are entirely original works by the instructor.
In the first session of this course, you will gain three essential areas of knowledge and skill that will serve as the foundation for your entire learning journey.
1. An overview of the world of data science
We begin by mapping analytical techniques that range from classical statistics to the most advanced methods in artificial intelligence. This “technology map” is designed to give you a bird’s-eye view of the entire lecture series, helping you understand how different methods connect and where they can be applied. With this map in hand, you will be ready to embark on a structured and meaningful exploration of data science.
2. The fundamental concepts of statistics
The starting point of Session One is classical statistics, often referred to as frequentist statistics. While data science today encompasses many diverse approaches, frequentist statistics remain the bedrock of nearly all analytical methods. Here, you will firmly master the fundamental concepts—such as populations, samples, probability distributions, and estimation—that provide the logical framework for more advanced techniques you will encounter later.
3. The principles of hypothesis testing and its application to problem solving
Hypothesis testing is a powerful tool for determining whether differences exist between data, but its logic can be subtle and is often misunderstood. The American Statistical Association has even issued warnings about the misuse of “statistical significance.” In this session, you will learn the correct interpretation of hypothesis testing and discover how it can guide real-world problem solving, from research decisions to business strategy.
By the end of Session One, you will not only understand the theoretical foundations of data science but also appreciate how these principles can be applied to practical challenges.
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