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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-in-marketing-an-introduction-course-2021/
课程评论：没有评论
课程名称：2022年市场营销中的数据科学入门课程 课程概述：欢迎来到2022年市场营销中的数据科学入门课程！本课程旨在教你如何利用数据科学解决实际商业问题，并应用这些技术于真实案例研究中。传统企业正在大量招聘数据科学家，掌握如何运用这些技术解决问题将在未来十年中成为极为宝贵的技能。根据《哈佛商业评论》和Glassdoor的报道，“数据科学家”已连续四年位列美国最佳职位。 然而，数据科学的学习曲线十分陡峭，初学者常常因复杂的数学和编码而感到困惑。本课程旨在填补这些知识空白，帮助初学者自信地将数据科学的知识应用于实际商业问题。课程大纲涵盖数据科学的主要组成部分，学习路径包括： - 数据科学如何解决常见的市场营销问题 - 数据科学家的现代工具 - Python、Pandas、Scikit-learn 和 Matplotlib - 机器学习理论 - 线性回归、决策树和模型评估 - 市场营销中的数据科学 - 参与率建模 - 零售中的数据科学 - 客户细分、生命周期价值和客户/产品分析 - 无监督学习 - K均值聚类 - 推荐系统 - 协同过滤 课程还包括多个案例研究，涵盖市场营销和零售领域的实际应用，包括分析营销活动的转化率、预测广告表现的驱动因素、识别最佳客户以及客户生命周期价值分析等。 如今，企业对数据科学家的需求比以往任何时候都要高。那些忽视这一趋势的公司将会被竞争对手抛在身后。大多数新的数据科学职位并非出现在传统科技公司中，而是在传统的非科技企业中，包括大型零售商、银行、市场公司、政府机构、保险公司和房地产等领域。“消费者数据将在未来两到三年内成为最大的竞争优势，能够有效利用数据的企业将会胜出。” 随着数据科学家薪资的不断上涨，本课程力求将你从初学者培养成能够解决实际挑战的数据科学家。数据科学是21世纪的热门领域，科技革命才刚刚开始，数据科学位于最前沿。快来参加本课程，提前学习这些技术，解决各种市场营销问题！
Welcome to the Data Science in Marketing: An Introduction Course 2021This course teaches you how Data Science can be used to solve real-world business problems and how you can apply these techniques to solve real-world case studies.Traditional Businesses are hiring Data Scientists in droves, and knowledge of how to apply these techniques in solving their problems will prove to be one of the most valuable skills in the next decade!"Data Scientist has become the top job in the US for the last 4 years running!" according to Harvard Business Review & Glassdoor.However, Data Science has a difficult learning curve - How does one even get started in this industry awash with mystique, confusion, impossible-looking mathematics, and code? Even if you get your feet wet, applying your newfound Data Science knowledge to a real-world problem is even more confusing.This course seeks to fill all those gaps in knowledge that scare off beginners and simultaneously apply your knowledge of Data Science to real-world business problems.This course has a comprehensive syllabus that tackles all the major components of Data Science knowledge.Our Learning path includes:How Data Science and Solve Many Common Marketing ProblemsThe Modern Tools of a Data Scientist - Python, Pandas, Scikit-learn, and Matplotlib.Machine Learning Theory - Linear Regressions, Decision Trees, and Model Assessment.Data Science in Marketing - Modelling Engagement Rates.Data Science in Retail - Customer Segmentation, Lifetime Value, and Customer/Product AnalyticsUnsupervised Learning - K-Means Clustering.Recommendation Systems - Collaborative Filtering.Four (3) Data Science in Marketing Case Studies:Analysing Conversion Rates of Marketing Campaigns.Predicting Engagement - What drives ad performance?Who are Your Best Customers? & Customer Lifetime Values (CLV).Four (2) Retail Data Science Case Studies:Product Analytics (Exploratory Data Analysis TechniquesProduct Recommendation Systems.Businesses NEED Data Scientists more than ever. Those who ignore this trend will be left behind by their competition. In fact, the majority of new Data Science jobs won't be created by traditional tech companies (Google, Facebook, Microsoft, Amazon, etc.) they're being created by your traditional non-tech businesses. The big retailers, banks, marketing companies, government institutions, insurances, real estate and more."Consumer data will be the biggest differentiator in the next two to three years. Whoever unlocks the reams of data and uses it strategically will win."With Data Scientist salaries creeping up higher and higher, this course seeks to take you from a beginner and turn you into a Data Scientist capable of solving challenging real-world problems.-Data Scientist is the buzz of the 21st century for good reason! The tech revolution is just starting and Data Science is at the forefront. Get a head start applying these techniques to all types of Marketing problems by taking this course!
