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.
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IBMÀ propos de ce cours
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Niveau intermédiaire
Approx. 8 heures pour terminer
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Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Anglais, Espagnol
Compétences que vous acquerrez
Artificial Intelligence (AI)Machine LearningFeature EngineeringStatistical Hypothesis TestingExploratory Data Analysis
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 8 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Anglais, Espagnol
Offert par
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.
Programme du cours : ce que vous apprendrez dans ce cours
1 heure pour terminer
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.
1 heure pour terminer
8 vidéos (Total 47 min), 2 lectures, 3 quiz
4 heures pour terminer
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.
4 heures pour terminer
16 vidéos (Total 148 min), 5 lectures, 5 quiz
3 heures pour terminer
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.
3 heures pour terminer
10 vidéos (Total 83 min), 2 lectures, 4 quiz
Avis
Meilleurs avis pour EXPLORATORY DATA ANALYSIS FOR MACHINE LEARNING
par DS30 nov. 2020
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.
par AM17 déc. 2020
Good introduction. The time estimates to complete assignments are off. Need a lot more material and direction for assignments to aid learning.
par MB30 mars 2021
This is a well-structured course with easy-to-understand lectures and practical examples that help a lot in real data analysis life.
par PZ6 avr. 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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