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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-for-beginners-n/
课程评论：没有评论
课程名称：数据科学入门 课程概述：本课程是一项全面的入门培训，系统地介绍了数据科学的世界，结合了基础理论与Python编程的实用技能。课程从基础开始，探索数据的定义，理解数据科学的角色和范围，深入研究基本的统计概念。你将学习重要的抽样技术和描述性统计，这些都是深入数据解读的基础。 接下来，课程将进入针对数据科学的Python基础内容，涵盖数据类型、控制流、函数和面向对象编程。通过这些技能，你将能够高效处理数据并编写清晰、可重用的代码。 此外，你将接触到两个重要的Python库——NumPy和Pandas，它们对于数值运算和数据处理至关重要。你将实践使用Pandas的Series和DataFrame创建和分析数据集。 在最后部分，你将获得探索性数据分析（EDA）的实践经验，学习数据获取、清洗、整理和准备的技术。这些都是在应用高级分析或机器学习之前的关键步骤。每个部分都有测验来评估你的学习效果。 完成本课程后，你将深入理解如何利用Python和数据科学原理，从原始数据中提取有意义的见解，为你在数据科学领域的旅程奠定坚实的基础。
This comprehensive course offers a structured introduction to the world of data science, combining foundational theory with practical skills in Python programming. Beginning with the basics, you'll explore what data is, understand the role and scope of data science, and delve into essential statistical concepts. You'll learn about key sampling techniques and descriptive statistics, which form the basis for insightful data interpretation.The course then moves into Python fundamentals tailored for data science, covering data types, control flow, functions, and object-oriented programming. With these skills, you'll be equipped to handle data efficiently and write clean, reusable code.Next, you'll be introduced to two essential Python libraries-NumPy and Pandas-that are pivotal for numerical operations and data manipulation. You'll practice creating and analyzing datasets using Pandas Series and DataFrames.In the final section, you'll develop hands-on experience with exploratory data analysis (EDA), learning techniques for data acquisition, wrangling, cleaning, and preparation. These are critical steps before applying advanced analytics or machine learning. Each section will have quiz to assess your performance.By the end of the course, you will have a strong understanding of how to use Python and data science principles to extract meaningful insights from raw data, setting a strong foundation for your journey in data science.
