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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-methodology-in-action-using-dataiku/
课程评论：没有评论
课程名称：使用Dataiku的数据科学方法论实践 课程概述： 踏入数据科学的世界，参加我们的“使用Dataiku的数据科学实践”课程。这门课程旨在利用非结构化数据和人工智能建模的力量，为希望在该领域获得实用的动手经验的学员设计。课程采用修改版的CRISP-DM方法论，以Dataiku作为主要工具。 课程内容： 1. 数据科学家的分类：学习“点击者”和“编码者”之间的区别，重点介绍使用Dataiku工具的“点击者”方法。 2. 毕业项目：在综合性毕业项目中应用所学知识，获得真实世界中设计和原型制作数据科学项目的经验。 3. 全面方法论：课程开始时设置Dataiku环境并回顾我们独特的数据科学方法论。 4. 七步数据科学方法论：深入探讨整个流程的每个步骤，从描述用例到持续模型监控与评估，全部在Dataiku中完成。步骤包括： - 用例描述：理解并表述所选的数据科学用例。 - 数据描述：使用Dataiku探索数据源和数据集。 - 数据集准备：在Dataiku中获得准备数据集的实践经验。 - 模型开发：在Dataiku中应用聚类和回归等人工智能建模技术。 - 模型评估：学习如何测量和评估AI模型的结果。 - 模型部署：理解部署AI模型的过程。 - 模型监控：掌握对生产中模型的持续监控与评估。 这门课程专为希望获得入门级“点击者”体验的数据科学学习者量身定制。无论你是商业分析师、项目经理，还是对编码或高级机器学习感兴趣的人员，这门课程都将提供数据科学方法论及其实际应用的基础理解。您可以下载数据集，按照步骤说明操作，完成作业并提交最终笔记本，全面参与到这一沉浸式学习体验中。加入我们，提升您的数据科学技能，并将其应用于日常场景中。
Embark on a journey into the world of Data Science with our "Data Science in Action using Dataiku" course, designed to harness the power of unstructured data and AI modeling. This course is perfect for those who want a practical, hands-on experience in the field, following a modified CRISP-DM methodology with Dataiku as the primary tool.Course Overview:Categorization of Data Scientists: Learn the distinction between 'clickers' and 'coders' in data science, focusing on the 'clicker' approach using tools like Dataiku.Capstone Project: Apply your learning in a comprehensive capstone project, offering a real-world experience in designing and prototyping a Data Science engagement.Comprehensive Methodology: The course begins with setting up your Dataiku environment and reviewing our unique data science methodology.Seven-Step Data Science Methodology: Dive deep into each step of the process, from describing your use case to continuous model monitoring and evaluation, all within Dataiku. These steps include:Use Case Description: Understand and articulate your selected data science use case.Data Description: Explore data sources and datasets using Dataiku.Dataset Preparation: Get hands-on experience in preparing datasets within Dataiku.Model Development: Apply AI modeling techniques like clustering and regression in Dataiku.Model Evaluation: Learn how to measure and evaluate your AI model results.Model Deployment: Understand the process of deploying your AI models.Model Monitoring: Master continuous monitoring and evaluation of your models in production.This course is tailored for those seeking an introductory 'clicker' experience in data science. Whether you're a business analyst, project manager, or someone interested in coding or advanced machine learning, this course offers a foundational understanding of data science methodologies and practical applications using Dataiku. Download datasets, follow step-by-step instructions, complete assignments, and submit your final notebook to fully engage in this immersive learning experience. Join us to transform your data science skills and apply them in everyday scenarios.
