Python数据科学：Python编程与数据分析（2024） (英文)

Python数据科学：Python编程与数据分析（2024）

发布日期： 2024年5月
创建者： Start-Tech Trainings, Start-Tech Academy
格式： MP4 | 视频：h264，1280×720 | 音频：AAC，44.1 KHz，2声道
类型： 电子学习 | 语言： 英语 | 时长： 39节课（6小时5分钟） | 大小： 2.15 GB

你将学到什么：

• 对Python语法、脚本编写和基本编程概念（如变量、数据类型和线条光线操作）有全面的理解
• 掌握使用列表、字典、元组和集合在Python中有效组织和管理数据的技能
• 熟练运用Python中的条件语句和循环，自动化和优化数据处理任务
• 学会设计可重用的Python函数，高效执行重复任务，包括递归和Lambda函数的使用
• 获得在Python中读取和写入文件的技能，这对于实际应用中的数据处理任务至关重要
• 了解如何使用NumPy数组进行复杂的数学计算，并通过高性能有效处理大型数据集
• 掌握Pandas进行数据操纵和分析的使用；学习如何探索、清洗和转换数据以适合分析
• 发展使用Matplotlib和Seaborn库创建见解深刻的数据可视化的能力

先修要求：

• 无需具备Python或数据分析方面的经验；只需具备基本的计算机技能，并能访问互联网即可开始本课程。

课程简介： 您是否渴望成为数据科学家或者想要提升数据分析技能？您是否曾经因为大量数据而感到不知所措，不知如何将其转化为可行的见解？如果您的目标不仅是理解数据科学的广阔世界，还要将这些知识实际应用，那么这门课程专为您而设计。深入探索Python及其强大的库的变革性世界，开始您成为熟练数据科学家的旅程。本课程为掌握Python编程和数据分析提供了全面的指南，专门针对数据科学应用进行了调整。通过参与本课程，您将：建立Python编程的坚实基础，从基本语法到高级功能。掌握使用Python最强大的库处理和分析数据，包括NumPy用于数值数据，Pandas用于数据操纵，Matplotlib和Seaborn用于数据可视化。创建引人入胜的数据可视化，有效传达您的发现。实现数据操纵技术，清洗、转换数据，为分析做好准备。通过应用实际编程解决方案，解决现实世界的数据分析问题。

为什么学习这个主题至关重要？在当今数据驱动的世界中，分析和解释数据的能力至关重要。Python处于数据科学的前沿，提供了一个庞大的库和工具生态系统，使数据分析变得简单而强大。无论您是分析客户数据以指导业务决策，进行学术研究，还是为个人项目探索数据集，Python都提供了将数据转化为见解的能力。

在整个课程中，您将参与实践性活动，如编码练习、实际数据分析项目和创建数据可视化。这些实践经验旨在巩固您的学习，让您有信心将所学知识应用于专业环境。本课程的特点不仅在于涵盖的范围广泛，更在于对实际应用的关注。您将学习不仅是理论，还要如何将这些概念应用到实际场景中，为您的工作或学习做好准备。别再让数据让您感到不知所措。立即报名参加《Python数据科学：Python编程与数据分析》课程，解锁数据的潜力，并成为数据科学领域的宝贵资产。

Python for Data Science: Python Programming & Data Analysis (2024)Python for Data Science: Python Programming & Data Analysis (2024)

Published 5/2024
Created by Start-Tech Trainings,Start-Tech Academy
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 39 Lectures ( 6h 5m ) | Size: 2.15 GB

Transform data into insights using Python and its powerful Libraries such as Numpy, Pandas, MatplotLib, Seaborn etc.

What you’ll learn:
Gain a thorough understanding of Python syntax, script writing, and fundamental programming concepts such as variables, data types, and string operations
Become adept at using lists, dictionaries, tuples, and sets for organizing and managing data effectively within Python
Master the use of conditional statements and loops in Python to automate and optimize data processing tasks
Learn to design reusable Python functions to perform repetitive tasks efficiently, including knowledge of recursion and lambda functions
Acquire skills in reading from and writing to files in Python, crucial for data processing tasks in real-world applications
Understand how to use NumPy arrays for complex mathematical computations and effectively handle large datasets with high performance
Master the use of Pandas for data manipulation and analysis; learn how to explore, clean, and transform data into a suitable format for analysis
Develop the ability to create insightful visual representations of data using Matplotlib and Seaborn libraries of Python

Requirements:
No prior experience in Python or data analysis is required; just basic computer skills and access to a computer with an internet connection are necessary to start this course.

Description:
Are you aspiring to become a data scientist or aiming to enhance your data analysis skills? Have you ever found yourself overwhelmed by data, wondering how to turn it into actionable insights? If your goal is to not only understand the vast world of data science but also to apply this knowledge practically, then this course is designed with you in mind. Dive into the transformative world of Python and its powerful libraries, and start your journey towards becoming a proficient data scientist.This course offers a comprehensive guide to mastering Python programming and data analysis, tailored specifically for data science applications. By engaging with this course, you will:Develop a solid foundation in Python programming, from basic syntax to advanced functions.Master the art of handling and analyzing data using Python’s most powerful libraries, including NumPy for numerical data, Pandas for data manipulation, Matplotlib and Seaborn for data visualization.Create compelling data visualizations that communicate your findings effectively.Implement data manipulation techniques to clean, transform, and prepare your data for analysis.Solve real-world data analysis problems by applying practical programming solutions.Why is learning about this topic crucial? In today’s data-driven world, the ability to analyze and interpret data is indispensable. Python, being at the forefront of data science, offers an extensive ecosystem of libraries and tools that make data analysis accessible and powerful. Whether you’re analyzing customer data to inform business decisions, researching for academic purposes, or exploring datasets for personal projects, Python provides the capabilities to turn data into insights.Throughout this course, you’ll engage in hands-on activities such as coding exercises, real-world data analysis projects, and creating data visualizations. These practical experiences are designed to cement your learning and give you the confidence to apply your skills in a professional setting.What sets this course apart is not just the breadth of topics covered but the focus on practical application. You’ll learn not just the theory but how to apply these concepts in real-world scenarios, preparing you for immediate application in your work or studies.Don’t let data overwhelm you any longer. Take the first step towards unlocking its potential by enrolling in Python for Data Science: Python Programming & Data Analysis today. Transform data into insights and become an invaluable asset in the field of data science.

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