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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-create-real-world-projects/
课程评论：没有评论
**课程名称：** 数据科学：创建真实世界项目 (Data Science: Create Real World Projects) **课程概述：** 本课程旨在帮助学员深入理解数据科学的核心概念，并掌握创建实际数据项目所需的关键技能。课程将首先解答“什么是数据科学”这一基础问题，阐释数据科学是如何通过跨学科的活动，利用数据来探究和解答科学、社会、政治、商业等领域中的具体问题的。 课程强调数据科学的关键组成部分：1. **数据**（从人类活动、地点和事物中收集或捕获的可测量信息单元）；2. **具体问题**（旨在理解现象，并能够通过数据中的模式观察、测试或建模来解答的问题）；3. **跨学科活动**（涉及领域知识、统计学和计算方法，以形成问题、评估数据适宜性、选择模型及做出推断）。 课程解释了数据科学为何重要，指出近年来数据的粒度、规模和可访问性呈爆炸式增长。引用谷歌首席经济学家 Hal Varian 的观点，强调数据科学将是未来十年最热门的职业之一，而数据处理、价值提取、可视化和沟通的能力将成为至关重要的技能，不仅限于专业人士，也适用于各教育阶段的学生。 **课程组织结构：** * **第一部分：** Anaconda 及编辑器/库的设置。 * **第二部分：** 学习数据科学的生命周期和方法论。 * **第三部分：** 学习数据预处理技术，包括数据清洗、归一化和转换。 * **第四部分：** 介绍一些机器学习模型，如线性回归和逻辑回归。 * **第五部分：** 项目实践一：酒店预订预测系统。 * **第六部分：** 项目实践二：自然语言处理。 * **第七部分：** 项目实践三：人工智能。 * **第八部分：** 课程总结与告别。
FAQ about Data Science:What is Data Science?Data science encapsulates the interdisciplinary activities required to create data-centric artifacts and applications that address specific scientific, socio-political, business, or other questions.Let's look at the constituent parts of this statement:1. Data: Measurable units of information gathered or captured from activity of people, places and things.2. Specific Questions: Seeking to understand a phenomenon, natural, social or other, can we formulate specific questions for which an answer posed in terms of patterns observed, tested and or modeled in data is appropriate.3. Interdisciplinary Activities: Formulating a question, assessing the appropriateness of the data and findings used to find an answer require understanding of the specific subject area. Deciding on the appropriateness of models and inferences made from models based on the data at hand requires understanding of statistical and computational methodsWhy Data Science?The granularity, size and accessibility data, comprising both physical, social, commercial and political spheres has exploded in the last decade or more.According to Hal Varian, Chief Economist at Google and I quote:"I keep saying that the sexy job in the next 10 years will be statisticians and Data Scientist""The ability to take data-to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it-that's going to be a hugely important skill in the next decades, not only at the professional level but even at the educational level for elementary school kids, for high school kids, for college kids."************ ************Course Organization **************************Section 1: Setting up Anaconda and Editor/LibrariesSection 2: Learning about Data Science Lifecycle and MethodologiesSection 3: Learning about Data preprocessing: Cleaning, normalization, transformation of dataSection 4: Some machine learning models: Linear/Logistic RegressionSection 5: Project 1: Hotel Booking Prediction SystemSection 6: Project 2: Natural Language ProcessingSection 7: Project 3: Artificial IntelligenceSection 8: Farewell
