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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-career-guide-interview-preparation/
课程评论：没有评论
课程名称：数据科学职业指南 - 面试准备 课程概述：根据Glassdoor的数据，数据科学家被认为是美国最佳的职业！数据科学家的平均基本工资超过12万美元，不仅薪酬优渥，还能参与解决世界上最有趣的问题。此外，数据科学家的职位在Glassdoor上被评为拥有最佳的工作与生活平衡。各大公司急需填补这一独特角色，本课程旨在帮助你顺利通过数据科学家面试。 本课程是成为数据科学家的终极资源。我们将首先对该领域进行总体概述，并讨论多个职业路径，包括产品分析师、数据工程师、数据科学家等。课程内容涵盖多种主题，包括概率、统计、机器学习、产品指标、示例数据集、A/B 测试、市场分析等。课程中包含来自全球顶尖科技公司（如亚马逊、Square、Facebook、谷歌、微软、AirBnb 等）的真实面试问题，并提供详细的释义和解决方案。无论是求职者希望全面了解潜在的面试问题，还是招聘者希望了解每个问题回答时需要关注的要点，这门课程都将提供极大的帮助。 在需要编程解决方案的问题中，将展示完全注释的Python和R代码示例，让学员能够更好地理解所用编程语言的代码，而无需担心语法问题。通过本课程，你将能够更好地准备面试，踏上数据科学家的职业之路。
According to Glassdoor, a career as a Data Scientist is the best job in America! With an average base salary of over $120,000, not only do Data Scientists earn fantastic compensation, but they also get to work on some of the world's most interesting problems! Data Scientist positions are also rated as having some of the best work-life balances by Glassdoor. Companies are in dire need of filling out this unique role, and you can use this course to help you rock your Data Scientist Interview! This course is designed to be the ultimate resource for getting a career as a Data Scientist. We'll start off with an general overview of the field and discuss multiple career paths, including Product Analyst, Data Engineering, Data Scientist, and many more. You'll understand the various opportunities available and the best way to pursue each of them. The course touches upon a wide variety of topics, including questions on probability, statistics, machine learning, product metrics, example data sets, A/B testing, market analysis, and much more! The course will be full of real questions sourced from employees working at some of the world's top technology companies, including Amazon, Square, Facebook, Google, Microsoft, AirBnb and more! The course contains real questions with fully detailed explanations and solutions. Not only is the course designed for candidates to achieve a full understanding of possible interview questions, but also for recruiters to learn about what to look for in each question response. For questions requiring coded solutions, fully commented code examples will be shown for both Python and R. This way you can focus on understanding the code in a programming language you're already familiar with, instead of worrying about syntax!
