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所在平台: Udemy |
课程主页: https://www.udemy.com/course/learning-path-from-python-programming-to-data-science/
课程评论：没有评论
课程名称：学习路径：从Python编程到数据科学 课程概述：Python已成为大多数数据分析师和数据科学家的首选语言，用于执行各类数据科学任务。如果您希望在数据科学项目中实现Python，以增强数据发现能力，那么这个学习路径将非常适合您。该学习路径从基础入手，逐步引导您经历所有数据科学的阶段。Packt的视频学习路径是一系列按逻辑和逐步方式编排的独立视频产品，每个视频都在前一个视频的基础上构建技能。 课程开始时，我们将掌握Python的基本知识，随后介绍Python的基本和高级编程概念，再转向数据科学主题。您将学习如何利用Python生态系统中的核心数据科学库执行数据分析。此外，课程还将帮助您更好地理解数据可视化概念、应用它们并克服实现过程中可能遇到的挑战。接下来，您将学习使用多种机器学习算法解决实际问题。最后，课程将介绍深度学习，并简要讲解TensorFlow。 学习结束时，您将能够使用Python提高数据科学项目的效率。 专家介绍：我们汇集了以下几位杰出作者的最佳作品，以确保您的学习旅程顺利进行： - Daniel Arbuckle：南加州大学计算机科学博士。 - Benjamin Hoff：曾担任软件工程师和团队负责人，专注于图形处理、桌面应用开发和科学设施模拟，使用C++和Python。 - Dimitry Foures：具有应用数学和理论物理背景的数据科学家。 - Giuseppe Vettigli：在研究和学术界有多年工作经验的数据科学家。 - Igor Milovanović：经验丰富的开发者，拥有Linux系统知识和软件工程教育背景。 - Prateek Joshi：人工智能研究员，出版五本书籍的作者，TEDx演讲者。 - Eder Santana：电气与计算机工程博士研究生，研究主题为深度学习和递归神经网络。
Python has become the language of choice for most data analysts/data scientists to perform various tasks of data science. If you're looking forward to implementing Python in your data science projects to enhance data discovery, then this is the perfect Learning Path is for you. Starting out at the basic level, this Learning Path will take you through all the stages of data science in a step-by-step manner. Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. We begin this journey with nailing down the fundamentals of Python. You'll be introduced to basic and advanced programming concepts of Python before moving on to data science topics. Then, you'll learn how to perform data analysis by taking advantage of the core data science libraries in the Python ecosystem. You'll also understand the data visualization concepts better, learn how to apply them and overcome any challenges that you might face while implementing them. Moving ahead, you'll learn to use a wide variety of machine learning algorithms to solve real-world problems. Finally, you'll learn deep learning along with a brief introduction to TensorFlow. By the end of the Learning Path, you'll be able to improve the efficiency of your data science projects using Python. Meet Your Experts: We have combined the best works of the following esteemed authors to ensure that your learning journey is smooth: Daniel Arbuckle got his Ph.D. in Computer Science from the University of Southern California. Benjamin Hoff spent 3 years working as a software engineer and team leader doing graphics processing, desktop application development, and scientific facility simulation using a mixture of C++ and Python. Dimitry Foures is a data scientist with a background in applied mathematics and theoretical physics. Giuseppe Vettigli is a data scientist who has worked in the research industry and academia for many years. Igor Milovanović is an experienced developer, with strong background in Linux system knowledge and software engineering education. Prateek Joshi is an artificial intelligence researcher, published author of five books, and TEDx speaker. Eder Santana is a PhD candidate on Electrical and Computer Engineering. His thesis topic is on Deep and Recurrent neural networks.
