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.
IBM課程信息
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
可靈活調整截止日期
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中級
完成時間大約為8 小時
英語（English）
字幕：阿拉伯語（Arabic）, 法語（French）, （歐洲人講的）葡萄牙語, 意大利語, 越南語, 德語（German）, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）
您將獲得的技能
Artificial Intelligence (AI)Machine LearningFeature EngineeringStatistical Hypothesis TestingExploratory Data Analysis
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
可靈活調整截止日期
根據您的日程表重置截止日期。
中級
完成時間大約為8 小時
英語（English）
字幕：阿拉伯語（Arabic）, 法語（French）, （歐洲人講的）葡萄牙語, 意大利語, 越南語, 德語（German）, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）
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.
教學大綱 - 您將從這門課程中學到什麼
完成時間為 1 小時
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 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.
完成時間為 1 小時
8 個視頻 （總計 47 分鐘）, 2 個閱讀材料, 3 個測驗
完成時間為 4 小時
Retrieving Data, Exploratory Data Analysis, and Feature Engineering
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, and how to conduct exploratory analysis to visually confirm it is ready for machine learning modeling.
完成時間為 4 小時
16 個視頻 （總計 148 分鐘）, 5 個閱讀材料, 5 個測驗
完成時間為 3 小時
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.
完成時間為 3 小時
10 個視頻 （總計 83 分鐘）, 2 個閱讀材料, 4 個測驗
審閱
來自EXPLORATORY DATA ANALYSIS FOR MACHINE LEARNING的熱門評論
由 DS 提供2020年11月30日
The only reason that I do not give it 5 stars is because the website of coursera is not good enough to handle the peer review assignments at the end of the course.
由 AM 提供2020年12月17日
Good introduction. The time estimates to complete assignments are off. Need a lot more material and direction for assignments to aid learning.
由 FF 提供2021年1月24日
if you really make the exercises and the final assignment the course really contributes you to better understand Data Analysis
由 AC 提供2020年9月30日
It is a really insightful and interactive learning experience. Furthermore, the trainers and coaches were very knowledgable.
常見問題
我什么时候能够访问课程视频和作业？
我订阅此证书后会得到什么？
完成课程后，我会获得大学学分吗？
還有其他問題嗎？請訪問 學生幫助中心。
