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Machine Learning for Business

4.3+
22 reviews
Beginner

Understand the fundamentals of Machine Learning and how it's applied in the business world.

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2 Hours15 Videos48 Exercises
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Course Description

Learn the Basics of Machine Learning


This course will introduce the key elements of machine learning to the business leaders. We will focus on the key insights and base practices how to structure business questions as modeling projects with the machine learning teams.

Dive into the Model Specifics


You will understand the different types of models, what kind of business questions they help answer, or what kind of opportunities they can uncover, also learn to identify situations where machine learning should NOT be applied, which is equally important. You will understand the difference between inference and prediction, predicting probability and amounts, and how using unsupervised learning can help build meaningful customer segmentation strategy.
For Business

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In the following Tracks

Certification Available

Data Scientist in Python

Go To Track
Certification Available

Data Scientist in R

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Data Skills for Business

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  1. 1

    Machine learning and data use cases

    Free

    Machine learning is used in many different industries and fields. It can fundamentally improve the business if applied correctly. This chapter outlines machine learning use cases, job roles and how they fit in the data needs pyramid.

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    Machine learning and data pyramid
    50 xp
    Terminology clarification
    50 xp
    Order data pyramid needs
    100 xp
    Match tasks in data pyramid
    100 xp
    Machine learning principles
    50 xp
    Modeling types
    50 xp
    Find supervised and unsupervised cases
    100 xp
    Job roles, tools and technologies
    50 xp
    Job role responsibilities
    50 xp
    Match data projects with job roles
    100 xp
    Team structure types
    100 xp
  2. 4

    Managing machine learning projects

    This chapter will look into the best and worst practices of managing machine learning projects. We will identify most common machine learning mistakes, learn how to manage communication between the business and ML teams and finally address the challenges when deploying machine learning models to production.

    Play Chapter Now
For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

In the following Tracks

Certification Available

Data Scientist in Python

Go To Track
Certification Available

Data Scientist in R

Go To Track

Data Skills for Business

Go To Track

Collaborators

Collaborator's avatar
Hadrien Lacroix
Collaborator's avatar
Sara Billen
Karolis Urbonas HeadshotKarolis Urbonas

Head of Machine Learning and Science

Karolis is currently leading a Machine Learning and Science team at Amazon Web Services. He's a data science enthusiast obsessed with machine learning, analytics, neural networks, data cleaning, feature engineering, and every engineering puzzle he can get his hands on.
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Don’t just take our word for it

*4.3
from 22 reviews
64%
23%
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  • Pedro D.
    5 months

    Very useful

  • Maja L.
    6 months

    Really liked the course!

  • David C.
    6 months

    Very interesting subject! Loved it!

  • Muhammad A.
    9 months

    This is a very good course which offers a wide analytical perspective from a busniess point of view. This is a good step, an amalgamation of the (desired) field domain knowledge courses and coding excercises makes a perfect match.

  • oskar s.
    10 months

    a lot of practical excercises

"Very useful"

Pedro D.

"Really liked the course!"

Maja L.

"Very interesting subject! Loved it!"

David C.

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