This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. You will learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing.
提供方
IBM课程信息
154,393 次近期查看
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中级
完成时间大约为14 小时
英语（English）
字幕：英语（English）
您将获得的技能
- Artificial Intelligence (AI)
- Machine Learning
- Feature Engineering
- Statistical Hypothesis Testing
- Exploratory Data Analysis
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
中级
完成时间大约为14 小时
英语（English）
字幕：英语（English）
提供方
IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
授课大纲 - 您将从这门课程中学到什么
完成时间为 2 小时
A Brief History of Modern AI and its Applications
Artificial Intelligence is not new, but it is new in a sense that it is easier than ever to get started using Machine Learning in business settings. In this module, we will go over a quick introduction to AI and Machine Learning and we will visit a brief history of the modern AI. We will also explore some of the current applications of AI and Machine Learning for you, to think about how you want to leverage them in your day to day business practice or personal projects.
完成时间为 2 小时
10 个视频 （总计 57 分钟）, 2 个阅读材料, 3 个测验
完成时间为 3 小时
Retrieving and Cleaning Data
Good data is the fuel that powers Machine Learning and Artificial Intelligence. In this module, you will learn how to retrieve data from different sources, how to clean it to ensure its quality.
完成时间为 3 小时
7 个视频 （总计 43 分钟）, 3 个阅读材料, 6 个测验
完成时间为 5 小时
Exploratory Data Analysis and Feature Engineering
In this module you will learn how to conduct exploratory analysis to visually confirm it is ready for machine learning modeling by feature engineering and transformations.
完成时间为 5 小时
15 个视频 （总计 104 分钟）, 3 个阅读材料, 7 个测验
完成时间为 3 小时
Inferential Statistics and Hypothesis Testing
Inferential statistics and hypothesis testing are two types of data analysis often overlooked at early stages of analyzing your data. They can give you quick insights about the quality of your data. They also help you confirm business intuition and help you prescribe what to analyze next using Machine Learning. This module looks at useful definitions and simple examples that will help you get started creating hypothesis around your business problem and how to test them.
完成时间为 3 小时
16 个视频 （总计 88 分钟）, 2 个阅读材料, 5 个测验
审阅
- 5 stars71.62%
- 4 stars20.48%
- 3 stars4.58%
- 2 stars2.29%
- 1 star1.01%
来自EXPLORATORY DATA ANALYSIS FOR MACHINE LEARNING的热门评论
由 NW 提供Dec 7, 2020
Recommended course for those wanting to advance their understanding about Exploratory Data Analysis for Machine Learning.
由 AM 提供Dec 17, 2020
Good introduction. The time estimates to complete assignments are off. Need a lot more material and direction for assignments to aid learning.
由 MB 提供Mar 30, 2021
This is a well-structured course with easy-to-understand lectures and practical examples that help a lot in real data analysis life.
由 PZ 提供Apr 6, 2021
Very well curated course. Walks through all the topics in detail. Would be better if the professor had a little bit higher voice.
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