您想知道清理数据并从中获得有用见解的最佳方法吗？
您想节省时间并轻松执行探索性数据分析 (EDA) 吗？
那么这门课程适合你！！
据福布斯报道：“数据科学家或数据分析师 60% 的时间都花在清理和组织数据上……”
在本课程中，您不仅会了解行业层面的策略，而且我还会实际演示它们以更好地理解。
本课程由行业专家精心设计，以反映处理杂乱数据的真实场景。
本课程将帮助您学习复杂的数据分析技术和概念，以便更轻松地理解和数据操作。
我们将逐步引导您完成每个主题，解释每一行代码以供您理解。
本课程的结构如下：
- 基本概念介绍
- 数据分析工具简介
- 奖励：Python Crush 课程
- 如何正确处理 Python 数据类型
- 如何正确处理 Python 中的日期和时间
- 如何正确处理缺失值
- 如何正确处理异常值
- 如何正确处理数据不平衡
- 如何正确处理数据泄露
- 如何正确处理分类值
- 从初学者到高级数据可视化
不同的特征工程技术包括：
- Feature Encoding
- Feature Scaling
- Feature Transformation
- Feature Normalisation
- Automated Feature EDA Tools
- pandas-profiling
- Dora
- Autoviz
- Sweetviz
- Automated Feature Engineering
- RFECV
- FeatureTools
- FeatureSelector
- Autofeat
- Web scraping
- Wikipedia
- online bookstore
- Amazon .com
本课程旨在帮助初学者以及中级数据分析师、学生、业务分析师、数据科学和机器学习爱好者掌握在现实世界中自信地处理数据的基础。
您将学到什么：
使用 Python 进行主数据分析
初级数据分析技术高级
学习 2021 年最新的数据分析技能和技术
掌握如何处理杂乱数据（异常值、缺失值、数据不平衡、数据泄漏等）
知道如何在 Python 中处理复杂的数据清理问题
学习用于专业数据清理和分析的自动化现代工具和库
获得成为前 10% 数据分析和数据科学一员所需的技能
学习准备要构建的数据的最佳方法机器学习模型
掌握处理原始数据的不同技术
掌握可视化和数据讲故事的艺术
执行行业级数据工程
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 321 lectures (24h 55m) | Size: 10.9 GB
Learn Industry Level Data Cleaning, Data Preprocessing, And Advanced Feature Engineering. All You Need Is Covered!!
What you’ll learn:
Master Data Analysis With Python
Master Beginner To Advance Level Data Analytics Techniques
Learn The Latest Data Analytics Skills And Techniques In 2021
Master How To Deal With Messy Data(outliers, missing values, data imbalance, data leakage etc.)
Know How To Deal With Complex Data Cleaning Issues In Python
Learn Automated Modern Tools And Libraries For Professional Data Cleaning And Analysis
Get The Skill Needed To Be Part Of The Top 10% Data Analytics and Data Science
Learn The Best Ways To Prepare Your Data To Build Machine Learning Models
Master Different Techniques Of Dealing With Raw Data
Master The Art Of Visualisation And Data Story Telling
Perform Industry Level Data Engineering
Requirements
This course is a beginner to advance level course with a step-by-step walk through.
If you are a complete beginner, you have all the lessons from introduction to python to dealing with complex data issues and building a web-scraper.
If you already have the basics in Python, feel free to skip the Python Crush course at the BONUS session.
Description
Interested in the field of Data Analytics, Business Analytics, Data Science or Machine Learning?
Do you want to know the best ways to clean data and derive useful insights from it?
Do you want to save time and easily perform Exploratory Data Analysis(EDA)?
Then this course is for you!!
According to Forbes: “60% of the Data Scientist’s or Data Analyst’s time is spent in cleaning and organising the data…”
In this course, you will not just get to know the industry level strategies but also I will practically demonstrate them for better understanding.
This course has been practically and carefully designed by industry experts to reflect the real-world scenario of working with messy data.
This course will help you learn complex Data Analytic techniques and concepts for easier understanding and data manipulations.
We will walk you through step-by-step on each topic explaining each line of code for your understanding.
This course has been structured in the following form:
Introduction To Basic Concepts
Introduction To Data Analysis Tools
BONUS: Python Crush Course
How To Properly Deal With Python Data Types
How To Properly Deal With Date and Time In Python
How To Properly Deal With Missing Values
How To Properly Deal With Outliers
How To Properly Deal With Data Imbalance
How To Properly Deal With Data Leakage
How To Properly Deal With Categorical Values
Beginner To Advanced Data Visualisation
Different Feature Engineering Techniques including:
Feature Encoding
Feature Scaling
Feature Transformation
Feature Normalisation
Automated Feature EDA Tools
pandas-profiling
Dora
Autoviz
Sweetviz
Automated Feature Engineering
RFECV
FeatureTools
FeatureSelector
Autofeat
Web scraping
Wikipedia
online bookstore
Amazon .com
This course aims to help beginners, as well as an intermediate data analyst, students, business analyst, data science, and machine learning enthusiasts, master the foundations of confidently working with data in the real world.
Who this course is for
This course is from a beginner level to advance level, and therefore anyone interested in learning basic to complex Data Analytics techniques for Data Science and Machine Learning is strongly advised to enrol.
Anyone preparing for a career in Data Analytics, Data Science, Business Analytics, Business Intelligence, Machine Learning will highly find this course very useful.
Any student ready to learn how to deal with complex machine learning problems such as imbalance data, data leakage, basic to advanced Feature Engineering etc. is strongly recommended to enrol.
Anyone who is looking for a career transition to Data Analytics, Data Science, Business Analytics, Business Intelligence, Machine Learning role and wants to understand the concepts very well from scratch is recommended to enrol.
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