|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/ai-powered-data-science-projects-with-chatgpt-copilot/
课程评论：没有评论
课程名称：ChatGPT与Copilot在Python与R数据科学项目中的应用 课程概述：欢迎参加我们互动课程《ChatGPT与Copilot在Python与R项目中的完整指南》，该课程旨在为您提供解决真实数据科学问题的实践经验，利用AI、Copilot和ChatGPT。通过Udemy的30天退款保证，您无需担心课程无法满足您的期望。课程将使用Python和R（RStudio）进行讲授。我们在2024年4月更新了完整的安装指南，包括如何安装和配置Python与R，并解释了如何将RStudio连接到Python并将其用作Python的集成开发环境。每节课独立成章，集中于不同的数据科学挑战。您将学习如何有效地应用AI工具如Copilot和ChatGPT来应对这些挑战。 本课程的实用项目学习内容包括： - 数据清理与整理：学习如何整洁地组织数据，为分析做好准备，确保数据的准确性和易用性，使用Python的Pandas和R的dplyr。 - 导入不同格式的文件：掌握从不同文件类型中引入数据的技巧，方便您在Copilot和ChatGPT中使用各种数据。 - 数据可视化：通过图表直观地展示数据，识别模式与关键点，这是数据科学的重要组成部分。 - 使用表格进行数据可视化：学习如何用表格简单有效地展示数据，便于比较与理解。 - 从API获取数据：掌握如何从API收集实时数据，使您的数据科学项目使用新鲜的真实数据，Python和R都有优秀的库可用。 - 网页抓取：学习如何抓取各种格式的数据，包括文本和HTML表格，以捕获网站中的相关信息。 - 连接与提取SQL数据：了解如何从SQL数据库获取数据，这对于许多数据科学项目处理有组织的数据至关重要。 - 数据表操作与连接：深入学习高级表操作，如数据变换与表连接，以获得更多见解。 - 回归分析：理解回归分析的基本知识，以观察变量之间的关系并预测未来趋势。 - 文本挖掘：探索如何从文本中提取有用信息，这在使用ChatGPT分析大量文本数据时尤其重要。 - 机器学习：开始构建机器学习模型，从数据中寻找模式并做出预测，这是数据科学的核心内容。 - 投资回报分析：深入分析投资回报，帮助您基于数据做出明智决策，展示数据科学在金融中的实用价值。 在每个项目过程中，我们将利用Copilot和ChatGPT的优势，展示这些AI工具如何加速编程过程并提升工作质量。您将观察到，Python在解决某些问题上速度更快，而R在另一些问题上更具优势。 本课程非常适合希望利用AI增强数据科学技能的学员。 关于我：作为一名顾问，我深刻分析了这些工具的影响，亲身体验了它们在复杂项目中的实用价值。即使在看似难以优化的任务中，Copilot和ChatGPT的智能辅助也能显著节省时间。我平均每天节省至少一小时来处理通常需要大量努力的复杂挑战。这种效率提升不仅仅是完成任务更快，更是借助AI驱动的建议达成更高标准的工作，改变我们在数据科学中解决问题的方式。
Join our interactive course, "Complete Guide to ChatGPT & Copilot for Python & R Projects", designed to give you hands-on experience in solving real data science problems using AI, Copilot, and ChatGPT. With Udemy's 30-day money-back guarantee in place, there's no need to worry if the class doesn't meet your expectations.The course is taught both in Python and R with RStudio. A complete installation guide on how to install and configure Python and R, was added in April 2024. It also explains how to connect RStudio to Python and use it as Python's IDE.Each lesson in this course stands alone, focusing on a different data science challenge.You'll learn how to apply AI tools like Copilot and ChatGPT to navigate through these challenges efficiently.Incorporating AI tools like Copilot and ChatGPT into your data science workflow can significantly enhance your speed and efficiency, often doubling (X2) or even increasing productivity tenfold (X10), depending on the task at hand.Here's what we'll cover, using practical, project-based learning:Data Clean-up and Tidy: Learn how to organize your data neatly, making it ready for analysis. This is a key step in data science to ensure your data is accurate and easy to work with. Using Pandas with Python and dplyr with R.Load Files of Different Formats: Discover how to bring in data from different kinds of files. This skill is important in data science because it lets you work with all sorts of data in tools like Copilot and ChatGPT.Data Visualization with Graphs: Find out how to use graphs to show your data in a clear and interesting way. Graphs help you see patterns and important points, which is a big part of data science.Data Visualization with Tables: Learn how tables can help you display data simply and effectively, making it easier to compare and understand, a common task in data science.Fetch API Data: Gain skills in collecting live data from APIs. This means you can use fresh, real-world data in your data science projects with Copilot and ChatGPT. Both Python and R have great libraries to fetch API data.Web Scrapping: Learn how to scrape data that comes in various formats like text and HTML tables. This ensures you can capture all the relevant information from a website. Python and R will do these tasks differently depending on webpage.Connect and Fetch from SQL: Learn how to get data from SQL databases, which is essential for dealing with organized data in many data science projects.Data Table Manipulations and Joins: Get into more advanced ways to work with tables, like changing data and putting tables together to get more insights, a useful technique in data science.Regression Analysis: Understand the basics of regression analysis, which helps you see how things are connected and predict future trends, a key method in data science.Text Mining: Explore how to pull out useful information from text, an important skill in data science, especially when working with tools like ChatGPT to analyze large amounts of text data.Machine Learning: Start building machine learning models, which let you find patterns and make predictions from data, a core part of data science. Python is the clear winner but R catching up!Portfolio Return Analytics: Dive into analyzing investment returns, which helps you make smart decisions based on data, showing the practical value of data science in finance.Throughout each project, we'll leverage the strengths of both Copilot and ChatGPT to demonstrate how these AI tools can not only speed up your coding process but also improve the quality of your work. You will observe how Python may solve a problem quickly, but R struggles, and vice-versa.This course is perfect for those looking to enhance their data science skills with the power of AI.About me:As a consultant who has meticulously analyzed the impact of these tools, I've observed firsthand the tangible benefits they bring to complex projects. Even in scenarios where tasks seem inherently resistant to optimization, the intelligent assistance provided by Copilot and ChatGPT can lead to substantial time savings.On average, I save at least one hour per day while tackling complex challenges that would typically demand extensive effort. This efficiency gain is not just about completing tasks faster; it's about achieving a higher standard of work with the insightful, AI-driven suggestions that these tools offer, transforming the way we approach problem-solving in data science.
