Data Science Modeling and Analysis Bootcamp 1

行业背景提升实战项目

围绕具体问题完成实践，建立能展示、能解释个人贡献的项目经历。

以下为此类服务的一般说明，本项目的具体要求与内容请结合下方介绍确认。

哪些需求可以考虑这类服务？

学过理论或工具，但缺少从问题到成果的完整项目实践。
转专业、转岗位，希望建立与目标方向相关的技能与作品。
简历中的项目较薄弱，或尚不能清楚解释自己的工作与取舍。

为什么参加实战项目？

把学到的知识用于具体问题，练习分析、实现与复盘。
根据项目大纲形成可展示的成果，并梳理自己实际完成的部分。
练习讲清需求、方案选择、遇到的困难与解决过程，为求职表达积累素材。

如何判断是否适合自己？

不是每个人都需要再参加一个项目。如果你已有充分相关实践，可能更需要面试辅导。培训项目不自动等同于正式工作或实习经历，应如实描述。

项目成果、基础要求、授课形式与时间投入以本项目大纲为准；不同项目不统一承诺代码、报告或上线产品，也不统一采用 1 对 1 授课。

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本项目适用人群

It is mainly aimed at Master students or PhD students with a strong mathematical background and students seeking jobs in data science and artificial intelligence in North America. This bootcamp looks forward to helping students who want to apply for data science jobs stand out and lock in North American technical job offers in advance.

你将收获

学生将自己从0到1完成多个业界常用并且受欢迎的机器学习模型

硅谷FLAG导师推荐信和职位内推

项目结束后获得导师的1:1反馈与点评

你将学习的技能

编程技巧

模型理解

实战项目

课题介绍

We provide a wealth of open source data, covering various aspects such as food reviews, medical care, social media, etc, allowing students to choose the direction and topic modeling they are interested in. The bootcamp content covers three parts: programming skills, model understanding, and industrial level projects.

课程大纲

The bootcamp will be oriented towards causal relationship models and recommendation systems, explaining the mathematical theory explanation of the model, parameter selection, and programming skills, and completely leading students to complete two complex data science projects from data collection and cleaning to modeling output. . Students can define their own questions of interest, select data sets under the guidance of instructors, and present their complete models and explanations at the end of the class.

Introduction to Big Data & Data Analysis

考察：Select an interesting topic and dataset to start a data project

授课1小时; 学习1小时

Python & SQL for Data Scientist/Analyst -data manipulation -data visualization -machine learning model package

考察：Coding tasks: from easy to hard Project: Use Python/R to clean data and visualize data

授课2小时; 学习4小时

（3选2）Design an experiment for AB testing to validate a business related decision

考察：Feature engineering, dimension reduction; Effective Size Test, Measure Variability, Sanity Check

授课4小时; 学习8小时

（3选2）Design a causation analysis experiment and implement several causal models from end to end

考察：Build a machine learning model from scratch and train - validate - test it from end to end

授课4小时; 学习8小时

（3选2）Recommendation system -Design a recommendation system for product cross-sell recommendation -Implement several machine learning models to realize the recommendation system

考察：Project: Build a machine learning model from scratch and train - validate - test it from end to end

授课4小时; 学习10小时

Evaluate the model, interpret the results and tell a good story

考察：Finish the project and get reviewed and feedback from mentor

授课1小时; 学习2小时

课程导师