|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/projects-in-data-science-using-r/
课程评论：没有评论
课程名称：使用R进行数据科学项目 课程概述：数据科学是一个跨学科领域，利用科学方法、过程、算法和系统，通过分析结构化或非结构化数据来获取见解。它旨在通过使用R、Hadoop、机器学习等技术，从原始数据中发现隐藏模式。数据科学从医疗保健到零售等多个行业的广泛应用，具有改变多个领域的巨大潜力。随着数据量的快速增长，数据科学家的需求激增，平均薪资可达110,000美元，这与地域有关。 学习数据科学的原因： 1. 在商业、医疗、金融等多个领域均有需求。 2. 可进行复杂的数据分析。 3. 能通过数据操作发现隐藏模式。 4. 可进行精准预测。 选择本课程的理由：随着存储、修改和分析数据的需求不断增加，数据科学已成为最重要的领域之一。无论大小公司，都在寻求数据科学家或能够处理大量数据的人才。考虑到这些事实，我们设计了这个全面的在线教程，帮助您构建不同的实际项目。该教程提供超过5小时的视频，足以用最简单、易懂和实用的方式阐述数据科学的不同方面。 课程中涵盖的项目： 1. 对鸢尾花数据集的数据转换。 2. 宽格式与长格式数据的项目。 3. 对数据集进行连接的项目。 4. 关于图形、几何形状和转换的项目。 参加本课程，构建在数据驱动的世界中具有巨大潜力的不同实际项目。
Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems for gaining insights by analyzing the structured or unstructured data. Basically, it helps in finding hidden patterns from the raw data by using technologies like R, Hadoop, Machine Learning and others.With its use from the healthcare to retail, it has one of the greatest potentials to change numerous sectors to its entirety. Similar to the rise of data in recent years, the demands of data scientists have also exploded with average salaries being offered up to $110,000 depending upon the locality.Why you should learn Data Science?Desired in different fields like business, healthcare, finance and othersIn order to perform complicated data analysisTo find the hidden patterns by data manipulationFor making precise predictionsWhy you should take this course?The regular need for storing, modifying and analyzing data have made data science one of the most important field. From big to small companies, all are in a constant search for the data scientists or the individuals who understand and can work with a huge pool of data. Knowing all these facts, we have designed this comprehensive online tutorial which will help you in building different real-world projects. This tutorial with over 5 hours of videos will be sufficient enough to make you explain different aspects of data science in the most simplest, easiest and practical way.Projects covered in the course:Data Transformations on Iris DatasetProject on Wide and Long DataPerforming Joins on DatasetsProject on Facets, Geoms and TansformationsTake this course for building different real-world projects in Data Science which has great potential in the world ruled by data.
