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所在平台: Udemy |
课程主页: https://www.udemy.com/course/become-a-python-data-analyst/
课程评论：没有评论
课程名称：成为Python数据分析师 课程概述： Python编程语言已成为数据科学和分析领域的重要工具。本课程介绍Python在数据科学中最重要的工具和库，这些工具和库被称为“Python的数据科学技术栈”。课程为实践性课程，通过真实案例，学习如何使用Python进行数据科学与分析的最流行工具。 作者介绍： 阿尔瓦罗·丰特斯（Alvaro Fuentes）是一位数据科学家，拥有定量经济学和应用数学的硕士学位，在分析领域拥有超过10年的经验。他曾在危地马拉中央银行担任经济分析师，负责建立经济和金融数据模型。他创立了Quant Company，提供数据科学咨询和培训服务，并参与许多商业、教育、心理学和大众传媒等领域的项目咨询。他还在全球范围内教授了多门（在线和现场）课程，内容涵盖数据科学、数学、统计学、R编程和Python。作为一名Python爱好者，他在数据分析和预测中常用Python，并在一些软件项目中应用过该语言。此外，他也热衷于Spark在大数据处理中的应用，欣赏其简化复杂任务的方式。他不是软件工程师或开发人员，但对网络技术感兴趣，并具备R编程、Spark、SQL（PostgreSQL）、MS Excel、机器学习、统计分析、计量经济学和数学建模等技术技能。预测分析是他在专业和教学中都有经验的领域，他在咨询实践中使用Python工具解决实际问题，而预测分析主题也成为他在线教学的更广泛数据科学课程的一部分。 总结： 本课程为希望在数据分析领域运用Python的学习者提供实用的知识和技能，通过真实案例，帮助学生掌握Python的数据科学工具和技术，为未来的数据分析工作打下坚实基础。
The Python programming language has become a major player in the world of Data Science and Analytics. This course introduces Python's most important tools and libraries for doing Data Science; they are known in the community as "Python's Data Science Stack". This is a practical course where the viewer will learn through real-world examples how to use the most popular tools for doing Data Science and Analytics with Python. About the author: Alvaro Fuentes is a Data Scientist with an M.S. in Quantitative Economics and a M.S. in Applied Mathematics with more than 10 years of experience in analytical roles. He worked in the Central Bank of Guatemala as an Economic Analyst, building models for economic and financial data. He founded Quant Company to provide consulting and training services in Data Science topics and has been a consultant for many projects in fields such as; Business, Education, Psychology and Mass Media. He also has taught many (online and in-site) courses to students from around the world in topics like Data Science, Mathematics, Statistics, R programming and Python. Alvaro Fuentes is a big Python fan and has been working with Python for about 4 years and uses it routinely for analyzing data and producing predictions. He also has used it in a couple of software projects. He is also a big R fan, and doesn't like the controversy between what is the "best" R or Python, he uses them both. He is also very interested in the Spark approach to Big Data, and likes the way it simplifies complicated things. He is not a software engineer or a developer but is generally interested in web technologies. He also has technical skills in R programming, Spark, SQL (PostgreSQL), MS Excel, machine learning, statistical analysis, econometrics, mathematical modeling. Predictive Analytics is a topic in which he has both professional and teaching experience. Having solved practical problems in his consulting practice using the Python tools for predictive analytics and the topics of predictive analytics are part of a more general course on Data Science with Python that he teaches online.
