Intro to Probability Distributions

所在平台: Udemy

课程主页: https://www.udemy.com/course/intro-to-probability-distributions/

课程评论:没有评论

第一个写评论        关注课程

课程简介

本课程《概率分布入门》由经验丰富的数据科学家 Slava Razbash 主讲,旨在为学员提供对概率分布的直观理解。课程强调实用性和概念性,避免了冗长的数学理论和考试导向内容。 课程内容包括: * **离散概率分布**:以投掷六面骰子为例进行讲解,适合概率论初学者。 * **连续概率分布**:在前一知识基础上,通过更有趣的例子和一些数学历史进行介绍。 * **极端值与异常值**:这是课程的独特和实用部分,通常在入门课程中被忽略。 * **附加术语**:简要介绍工作场所中常用的一些相关术语。 讲师 Slava Razbash 自2011年起担任数据科学家,拥有澳大利亚顶尖大学的计量经济学应用硕士学位,具备丰富的行业实践经验。他指出,与其他侧重理论和考试的大学课程不同,本课程以学员的实际应用为出发点,用更经济实惠的方式(远低于大学学费)提供行业专家的知识。 课程尤其适合希望提升数据素养的个人,包括数据科学家、数据素养领导者,甚至AI工程师(因为LLM预测下一个token时就用到概率分布)。讲师鼓励学员选择本课程作为快速获得概率分布直观理解的跳板,为未来深入学习理论打下基础。 *如果完全没有概率论基础,建议先学习讲师提供的免费课程《概率论基础》。*

课程评论(0条)

课程详情

This is a rare opportunity to learn about probability distributions from an experienced data scientist. You will get an intuitive understanding of probability distributions. Whether you aspire to be a data scientist or just a data literate leader, probability distributions are an essential concept to understand. Whatever your journey, this course will boost your data literacy. A lot of courses on probability distributions will give you 10 hours of maths. And they will teach you to pass written exams. But they won't give you the conceptual and intuitive understanding that you can use in your role. So you need a short course that will give you an intuitive and practical understanding of the concepts without burying you in equations and theory that you'll never apply in your role. You might have looked into probability distributions before. You might have taken other courses. You might have looked through books, and you might have been left wondering, how does this apply outside of the classroom? The truth is that other training material on probability distributions is not created by experienced professional data scientists. Other courses are created to teach theory that you can use to pass exams and to publish academic papers. The university professors that teach these courses are not concerned about applying their theories outside of the classroom. In your personal learning journey, you have two paths. The first path involves learning all of the theory and then working as a data scientist for 14 years to truly understand it. Or the quicker path, take a short course where an experienced data scientist explains the concepts that you need to know. If your ultimate goal is to truly understand the theory, this course is the perfect primer. It's better to have an understanding of the concepts before diving into the details of the formulas, rather than learning the formulas before understanding what they're actually measuring. So who am I? My name is Slava Razbash. I've worked in data science roles since 2011. I've worked as a data scientist at some of the largest companies in Australia. I hold a master of applied econometrics from one of Australia's top universities, Monash University. So, you can see that I might know a thing or two about the practical application of probability distributions and data literacy. This course is a gentle introduction to the concept of a probability distribution. We start with discrete probability distributions. I'll use the example of rolling a six sided die to introduce the concept. I also used the six-sided die example in my probability theory basics course. If you're completely new to probability theory, then start there. Next, we build on your knowledge to introduce continuous probability distributions. The examples become more interesting and you will learn a little bit about mathematical history. The most unique and practical section of this course is the section on extreme values and outliers, because it's a topic that's usually left out of beginner courses. Finally, there's a short lecture to define some additional terms that you will hear in the workplace. Getting started is easy, just enrol in this course. By comparison, taking a subject at a university will cost you thousands of dollars, and your professors may not have worked outside of academia. Although this course doesn't cover as much as a university subject, it's much more affordable and it's taught by a real industry expert. So you get access to over 14 years of industry experience for much less money than you would spend in a restaurant. Now, there is a caveat. If you are completely new to probability theory, then you should start with my free probability theory basics course. It's free. It was originally designed as part one of this course. Now, some people might be thinking, I'm an AI engineer. I vibe code B2B SaaS unicorns. Why do I need to know about probability distributions? Well, did you know that LLMs predict the probability distribution of the next token? Understanding how it works will make you a better unicorn vibe coder, especially in the B2B space. From my experience, I can see that you have three different paths in front of you. You can do nothing and get replaced by someone who is more data literate than you. The second option is to jump into a long theory heavy course that will teach you to pass exams. You will then need years of industry experience to understand how the theory applies outside of the classroom. Or you can enroll in this course and get an intuitive introduction to probability distributions from an experienced data scientist and quickly boost your data literacy. You might choose to continue learning and then take a long theory heavy course later. Having already done this course as a foundation, you will understand the maths better because you will already have an intuitive understanding of the concepts. So if you want to quickly leverage my 14 years of data science experience, enrol in this course.

课程标签

0人关注该课程

主题相关的课程