IBM
Exploratory Data Analysis for Machine Learning
IBM

Exploratory Data Analysis for Machine Learning

This course is part of multiple programs.

Taught in English

Some content may not be translated

Joseph Santarcangelo
Svitlana (Lana) Kramar

Instructors: Joseph Santarcangelo

94,601 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.6

(1,660 reviews)

|

95%

Intermediate level
Some related experience required
14 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

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Assessments

12 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.6

(1,660 reviews)

|

95%

Intermediate level
Some related experience required
14 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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There are 5 modules in this course

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.

What's included

10 videos2 readings3 quizzes1 discussion prompt

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.

What's included

7 videos3 readings3 quizzes3 app items

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.

What's included

15 videos3 readings3 quizzes4 app items

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.

What's included

16 videos2 readings3 quizzes2 app items1 discussion prompt

In this optional HONORS project you will apply your skills and knowledge learned throughout the course. You can select a dataset from the ones used in this Course or any other dataset of interest and apply all of the demonstrated techniques including, Data Cleaning, Feature Engineering, Exploratory Data Visualization, and Hypothesis Testing.

What's included

1 reading1 peer review

Instructors

Instructor ratings
4.5 (566 ratings)
Joseph Santarcangelo
IBM
28 Courses1,398,794 learners
Svitlana (Lana) Kramar
IBM
3 Courses104,063 learners

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IBM

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