|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/a-z-python-bootcamp2021-basics-to-data-science-50-hours/
课程评论:没有评论
**课程概述:Python A to Z Bootcamp (2021) 基础-数据科学-API(50小时)** 该课程旨在帮助初学者和希望通过学习Python提升职业发展的程序员掌握Python编程的基础知识。Python是全球最受欢迎的编程语言之一,许多大型公司如Google和亚马逊在其关键应用中广泛使用。课程内容包括Python的基本语法、正则表达式、数据结构与算法以及API的实践应用。完成课程后,学员将能够自信地使用Python进行编程,这将有助于他们理解Python在不同情况下的应用,并成为初级Python程序员,获取硅谷的工作机会。 **课程特点:** - 包含80多个视频,为初学者提供所需的编程知识。 - 提供详细的安装过程以及Python语法、决策及循环结构的讲解。 - 涵盖数据类型、函数、模块、Excel操作、文件处理及面向对象编程(OOPS)概念。 - 介绍通用的数据处理工具和算法,包括排序、查找、动态规划等。 - 实践性强,课堂讲解配有完整的编码示例和相应的代码笔记,便于学员根据自己的学习习惯学习。 **课程内容:** 1. **基础知识**:包括递归、算法运行时间分析、数组、栈、链表、二叉树、哈希表等基本数据结构。 2. **正则表达式**:从日志中提取和修改文本信息。 3. **API基础**:学习如何使用Python实现API的请求和响应,包括创建简单的货币转换计算器。 4. **数据抓取**:从网页提取数据,处理机器人保护的网站信息,并将数据存储到数据库。 5. **Pandas与Numpy**:数据表示的创建和操作,矩阵的管理,数据可视化等。 6. **Scikit Learn**:使用Scikit-Learn实现数据科学和机器学习模型的全过程,包括模型评估与优化。 本课程将为学生提供信心和技能,使其能够在编程领域取得成功,同时承诺在未来两年内每季度更新至少一个视频模块,以帮助初学者不断进步。
Learn python basics by practicing Basic syntax, Regular Expression, Data structure & Algorithm and APIThis course is aimed at complete beginners who have never programmed before, as well as existing programmers who pursue to increase their career options by learning Python.Python is one of the most popular programming languages in the world - Huge companies like Google, amazon use it in mission critical applications like Google Search.By the end of the course you'll be able to code with confidence using Python programming. This will help you understanding the usage of python in different circumstance.Become a Junior Python Programmer and land a job in silicon valley.Get access to all the codes used in the course.This course will contain all 80+ videos explaining necessary things a beginner needs to know in a programming language.This course will get continuously updated for beginners to get learn more. I promise to get at least 1 video section to be added per quarter for the next 2 years.Objective of the Python basic content:Giving confidence that any student they can be a programmer.Detailed Installation processCovers syntax in Python.Decision making and loopsPython basics like Data types, functions, Modules.Excel OperationPython file handling.Regular Expression.Programming with OOPS Concept.Tools required for a Junior python developer job.This course will teach you Python in a practical manner, with every lecture comes a full coding screen cast and a corresponding code notebook! Learn in whatever manner is best for you!Help you in enabling processing the data from different source.File handling from different sources.The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. You will learn a lot of theory: how to sort data and how it helps for searching. How to break a large problem into pieces and solve them recursively and it makes sense to proceed greedily. Objective of the Python data structure content:Recursion.Algorithm run time analysisArraysStack Linked listData StructureBinary TreeBinary Search TreeAVL TreeHeap treeQueueSortingHash TableGraph TheoryMagic FrameworkComputer ProgrammingDynamic ProgrammingRegular expression (Regex):Fetch the textual information from logs.Perform the changes in the existing textual information for re-using.API Python:This section help you understand the working on API and how to implement the same using Python.Here we will learn how to get and post the request using API and implement the same.Will create a simple currency conversion calculator.We will also cover API for website which we need to sign in. We will be using the API keys and ID to login and fetch the details.We will explain how to structure and export the data in CSV using Pandas.Scraping:Fetch the dat from the URLGet the information from Robot protected the website.Fetch the information using paginationFetch the information by crawling the pages and storing it in DB.Pandas:Creation of Data representationData filteringData frameworkSelection and viewingData ManipulationNumpy:Datatypes in NumpyCreating arrays and Matrix.Manipulation of data.Standard deviation and variance.Reshaping of Matrix.Dot functionMini-project using Numpy and Pandas packageMatplotlib:Creation Plots - Line, Scatter, bar and Histogram.Creating plots from Pandas and Numpy dataCreation of subplotsCustomization and saving plotsScikit LearnEnd to end Implementation of Data science and Machine Learning model using Scikit-Learn(SKLearn)Explained the option of improving the results by changing parameters and Hyper-parameter in a model.Getting data readyChoosing estimatorsFitting the dataPredicting valuesEvaluation of resultsImproving the results of the modelSaving the model.Supervised LearningData analysis and Basic PlottingData Correlation in modellingGetting data ready for modellingModel explained in DetailImproving the Model Randomized SearchCVGrid Search CVUnsupervised LearningK-Means ClusterngFinding Distance between ClustersHierarchial ClusterngMini-Project