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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-in-excel-2023-masterclass-for-data-science/
课程评论：没有评论
课程名称：《2024年Excel中的Python数据科学精英课程》 课程概述：解锁数据科学与金融的潜力，利用Excel 2024中全新的Python功能！准备好将您的数据分析和可视化技能提升到一个新水平吗？欢迎加入《2024年Excel中的Python数据科学精英课程》，这是一个终极课程，旨在使Excel用户能够无缝集成Python，以增强数据处理、分析、可视化和机器学习的能力。 课程亮点： - **协同效应**：通过将Excel熟悉的界面与Python编程的无限可能结合，深入探索数据科学的未来。 - **数据转换**：学习如何使用Python库轻松加载、清洗和转换数据，提升数据准备过程的效率。 - **高级分析**：掌握在Excel中使用Python强大库进行统计分析和机器学习的艺术，开启预测建模和决策的新视野。 - **数据可视化**：使用Python的数据可视化库创建惊人的图表、图形和互动仪表板，以讲述引人入胜的数据故事。 - **金融分析**：在Excel中执行更复杂的金融和投资工作流程，利用Python的强大库。 - **无缝集成**：发现如何将Python脚本无缝集成到Excel工作簿中，自动化重复任务，节省时间和精力。 - **与其他强大工具组合**：将全新的Python与xlwings结合使用，以提升您的项目。 适合人群： - 希望扩展技能集并探索Python数据分析能力的Excel爱好者。 - 渴望利用Python先进分析工具而不离开Excel环境的数据分析师、业务分析师和金融专业人士。 - 希望通过真实数据项目获得Python实践经验的数据科学学习者。 - 任何希望通过掌握最新数据分析技术来提升职业前景的人士。 选择本课程的理由： - **内容最新**：通过最新的Python集成功能保持领先。 - **实践学习**：参与动手项目和练习，巩固您的技能。 - **专家指导**：受益于经验丰富的讲师的指导，他们会简化复杂概念。 - **结业证书**：完成课程后获得Udemy结业证书，展示您的新技能。 讲师介绍：课程讲师亚历山大·哈格曼（Alexander Hagmann）是一位拥有超过15年Excel和Python经验的资深数据科学家和金融专业人士。他设计本课程的目的是帮助您弥合Excel与Python之间的差距，使数据分析和可视化变得更容易和强大。 注意：本课程假设您对Excel有基本了解，对Python有一定的先前知识。还需要在Windows机器上有效的Microsoft 365订阅（当前不支持MAC和Linux）。
Unlock the Power of Data Science and Finance with Python in Excel 2024 - the BRAND-NEW Excel Feature! Are you ready to take your data analysis and visualization skills to the next level? Welcome to the "Python in Excel 2024 Masterclass for Data Science," the ultimate course that empowers Excel users to seamlessly integrate Python into their workflow for enhanced data manipulation, analysis, visualization, and machine learning.Course Highlights:Harness the Synergy: Dive into the future of data science by merging Excel's familiar interface with the limitless possibilities of Python programming.Data Transformation: Learn how to effortlessly load, clean, and transform your data using Python libraries, supercharging your data preparation processes.Advanced Analytics: Master the art of statistical analysis and machine learning within Excel using Python's powerful libraries, opening up new horizons for predictive modeling and decision-making.Data Visualization: Create stunning charts, graphs, and interactive dashboards using Python's data visualization libraries to tell compelling data stories.Financial Analytics: Perform more complex Finance and Investment workflows within Excel using Python's powerful librariesSeamless Integration: Discover how to seamlessly integrate Python scripts into your Excel workbooks and automate repetitive tasks, saving you time and effort.Combination with other powerful Tools: Complementary usage of the brand-new Python in Excel together with xlwings will boost your projects.Who Is This Course For?Excel enthusiasts looking to expand their skill set and explore Python's data analysis capabilities.Data analysts, business analysts, and finance professionals wanting to leverage Python's advanced analytics tools without leaving the Excel environment.Data science aspirants eager to gain hands-on experience in using Python for real-world data projects.Anyone seeking to enhance their career prospects by mastering the latest data analysis techniques.Why Choose This Course?Up-to-date Content: Stay ahead of the curve with the latest Python integration features in Excel 2023.Practical Learning: Dive into hands-on projects and exercises that reinforce your skills.Expert Guidance: Benefit from the knowledge of experienced instructors who simplify complex concepts.Certificate of Completion: Showcase your newfound skills with a Udemy certificate upon course completion.Instructor Profile:Your course instructor, Alexander Hagmann, is a seasoned data scientist and finance professional with >15 years of experience in both Excel and Python. He has designed this course to help you bridge the gap between Excel and Python, making data analysis and visualization more accessible and powerful than ever before.Note: This course assumes a basic understanding of Excel and some prior knowledge of Python. A valid Microsoft 365 Subscription on a Windows machine is needed (MAC and Linux are currently not supported!)
