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所在平台: Udemy |
课程主页: https://www.udemy.com/course/generative-ai-for-data/
课程评论：没有评论
课程名称：用于数据工程和数据专业人员的生成性人工智能 概述：本课程是一个实践性的操作课程，旨在教导如何在数据工程中以及作为数据专业人员运用生成性人工智能（Gen AI）。我们将使用Python、OpenAI API和Jupyter Notebooks来编写和执行代码。生成性人工智能正在改变数据及数据工程的游戏规则，主要原因有二：一是数据专业人员使用生成性人工智能可以将任务完成速度提高16%，日常编码或分析数据的情况下速度甚至提升超过45%；二是生成性人工智能赋予数据工程师和分析师完成以前无法实现的新任务的能力，如从非结构化数据中提取特征/洞察或增强文本数据，这些现在都只能通过生成性人工智能实现。因此，生成性人工智能正在革新数据工程生命周期的每一个环节。无论你是数据分析师、数据科学家、数据工程师、数据专业人员还是数据经理，都需要学习如何将生成性人工智能嵌入到日常工作流程中。 本课程将帮助你更有效和高生产力地运用生成性人工智能。课程内容包括超过5.5小时的相关教学视频，具体讲解生成性人工智能对数据工程和数据专业人员生命周期的影响，并应用于真实案例。 学习内容包括： 1. 将生成性人工智能整合到工作流程中，包括数据生成、分析、存储、可视化等方面。 2. 提升工作效率，实现数据任务的快速完成。 3. 学习如何处理以前无法完成的数据任务，如从未结构化文本中提取见解或增强文本数据。 课程结构： 1. 生成性人工智能概述：了解生成性人工智能如何影响数据工程任务。 2. 环境设置：选择合适的工具，设置Python、VSCode和Jupyter Lab或使用Google Colab，并设置OpenAI API。 3. 数据生成和增强：学习创建合成数据、处理个人信息、平衡数据集等。 4. 生成性人工智能编程：了解如何运用生成性人工智能编写数据工程代码，包括数据清洗、建模和文档编写。 5. 生成性人工智能数据工程工具：探索如ChatGPT、Claude及其他工具。 6. 数据解析和提取：使用生成性人工智能从非结构化文本中提取数据。 7. 数据查询和分析：优化查询、开发和运行查询应用程序并转化为Web应用。 8. 数据增强、标准化和规范化：使用生成性人工智能对数据进行丰富、规范和标准化。 9. 结论与后续步骤：获取证书的方式及问题反馈途径。 如果你希望学习如何提高生产力并作为数据工程师有效运用生成性人工智能，这门课程将是你理想的选择。我们期待你的加入，并希望你能顺利获得证书。
Note: this is as practical hands-on-keyboard course on how to use Generative AI in Data Engineering (and as a Data Professional). We will be using Python, OpenAI API, and Jupyter Notebooks to write and execute code.Generative AI is changing the game in data and data engineering for two reasons:Do tasks faster - Data professionals who use Generative AI complete tasks 16% faster. This increases to more then 45% if you code / analyze data on a day-to-day basisDo new tasks - Generative AI enables data engineers and analysts to do so much more. In fact, some tasks like extracting features / insights from unstructured data or augmenting textual data is now only possible with Gen AI.This is why GenAI is revolutionizing each step of the data engineering lifecycle. It doesn't matter if you're a data analyst, data scientist, data engineer, data professional, or data manager - you need to learn how to embed Generative AI in your day-to-day workflows.That's what this course is all about - to make you more powerful and productive as a data professional with Generative AI.Learn from more than 5.5 hours of relevant instructional video content, with the only course that will practically teach you the different ways that Generative AI is impacting the data engineering and data professional lifecycle, and then apply that to real-life end-to-end examples.What is this course all about?This course is all about how you can practically embed Gen AI into your day-to-day workflows as a Data Engineer or Data Professional. It's a deep practical guide on how Generative AI is revolutionizing each step of the data engineering lifecycle, making you more productive and powerful. This is a technical and practical course (it's not theoretical or hand-wavy). Why learn Generative AI as a Data Professional or Data Engineer?There are two reasons: productivity and power. Generative AI can do certain things faster - like writing SQL queries, documentation, creating schemas, and analyzing simple data. Generative AI can do things that were not possible before, like extracting insights from unstructured text, imputing textual data, or augmenting data while maintaining context. You must know how to use Gen AI to avoid being left behind.How can Generative AI impact Data Engineering?Gen AI impacts Data Engineering in many different ways. Specifically, we'll look at 7 different archetypes:Data Generation and AugmentationWriting Generative AI Code with Gen AIData Parsing and ExtractionGen AI Data Engineering ToolsData Querying and AnalysisData Enrichment, Normalization, and StandardizationAnomaly Detection and CompressionWhat will you learn?Integrate Generative AI - Learn how to fully embed Generative AI as a Data Professional in your workflows (including data generation, analysis, storage, visualization, pipelines, and more)Be more productive - Generative AI is a productivity game changer - it can help you complete data tasks up to 20% faster (McKinsey), and even more if you write or use codeBe more powerful - Learn how to do more data tasks that weren't possible without Generative AI, like extracting insights from unstructured text or augmenting textual dataWhy choose this course?Complete guide - this is the 100% start to finish, zero to hero, basic to advanced guide on using Generative AI as a Data Engineer or Data Professional. There is no other course like it that teaches you everything from start to finish. It contains over 5.5 hours of instructional content!Structured to succeed - this course is structured to help you succeed. We first go through the fundamentals on how Generative AI can be used for Data Engineering. Then, we go through the 7 different archetypes of how Gen AI can be embedded into your workflows. We go through each, one-by-one, in full detail.Fully instructional - we not only go through important concepts, but also apply them. This is a practical hands-on-keyboard type course. This is not only a walkthrough of the all the features and theoretical concepts, but a course that actually uses real-life examples and integrates workflows with you.Step by step - we go through every single method of how Generative AI can impact Data Engineering step-by-step. We start with examples, then complete full end-to-end activities to apply what we've learned. Teacher response - if there's anything else you would like to learn, or if there's something you cannot figure out, I'm here for you! Look at the ways to reach out video.Course overviewIntroduction to Generative AI for Data Engineering - Get an overview of the course, learn how Generative AI impacts Data Engineering tasks, and become familiar with the course roadmap.Environment Setup - Set up your workspace with two options: download Python, VSCode, and Jupyter Lab, or use Google Colab. We'll also guide you through setting up the OpenAI API.Data Generation and Augmentation - Generate and augment data with Generative AI. Learn to create synthetic data, handle PII, balance datasets, and more. We'll also build a data augmentation app, from backend to frontend.Writing Data Engineering Code with Generative AI - Discover how to use Generative AI for writing data engineering code. This section includes data cleaning, modeling, documenting code, creating data schemas, and transferring data.Gen AI Data Engineering Tools - Explore tools like ChatGPT, Claude, custom GPTs, and other Gen AI tools for data engineering.Data Parsing and Extraction - Parse and extract data from unstructured text using Generative AI, including data from web scrapes, images, contracts, invoices, receipts, and perform named entity recognition.Data Querying and Analysis - Master querying and analyzing data with Generative AI. Optimize your queries, develop and run query apps, and convert them to web apps with front-end components.Data Enrichment, Normalization, and Standardization - use Generative AI to enrich, normalize, and standardize your data, covering feature enrichment, data imputation, and standardizing textual data for better models.Conclusion - this covers the certificate, next steps, and ways to get in touch.If you want to learn how to improve your productivity and be more powerful as a data engineer (in practice, not in theory) using Generative, then this is the course for you. We're looking forward to having you in the course and hope you earn the certificate.
