Complete guide to begin with Python for Data Science

所在平台: Udemy

课程主页: https://www.udemy.com/course/python-go-beginner-to-professional/

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## 零基础玩转Python数据科学:入门到精通 本课程是一站式Python学习指南,专为希望进入数据科学、数据分析及机器学习领域的朋友们设计。无论您是编程新手,还是已有代码基础但寻求进阶,本课程都能满足您的需求。 **课程亮点:** * **从零开始,循序渐进:** 详细讲解Python基础知识,包括数据类型(数字、列表、集合、元组、字典)、控制流(循环、条件语句)、函数(包括递归函数)等。 * **理论结合实践:** 通过大量图文并茂的示例和动手练习,帮助您深入理解概念并熟练掌握。 * **Jupyter Notebook实操:** 学习使用行业标准的Jupyter Notebook进行代码执行和项目开发,为未来求职打下基础。 * **全面技能提升:** 课程内容涵盖数据分析、机器学习和Python开发等关键领域,为您的职业发展铺平道路。 **谁适合学习:** * 从未接触过编程,希望系统学习Python并转向数据科学的初学者。 * 已有编程基础,希望深入学习Python高级特性和应用的学生或从业者。 **课程目标:** * 掌握Python基础语法和核心概念。 * 熟练运用Jupyter Notebook进行Python编程。 * 为数据分析、机器学习和Python开发工作做好准备。 开启您的Python数据科学之旅,从这里开始!

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A complete guide to begin your python learning for data science, data analysis and machine learning.For those, who has never written a single code in entire life and want to move into data science or advanced python, this course provides you a simple approach to learn coding from scratch using python as a tool and master it with illustrations and assignments.For those, who are already experienced in coding, but want to move into advanced python, this course provides you ample hands-on exercises and assignments for deeply understanding the concept.In this course, you will be learning from the very basics - which includes basic numbers, arithmetic operations, lists, sets, tuples, dictionaries, loops, if else statements, nested dictionaries, functions, recursive functions etc. We will be using Jupyter notebook in order to execute all the codes. Jupyter notebook is a tool that is being used by all the multinational organisation, who hire people for analytics and machine learning jobs.Key features: # Learn Python from scratch - from installation to writing your first code to understand the basics and finally to reach advance level. # No prior coding experience required. # Command yourself in Jupyter Notebook. # Prepare yourself for Data Analytics, Machine Learning, Python Development. Have a great learning ahead.

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