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Data Analytics - Introduction to Machine Learning Course


Data Analytics - Introduction to Machine Learning
Data Analytics - Introduction to Machine Learning

Learn about machine learning and its use in data analytics.


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Course Description

In this free course Data Analytics – Introduction to Machine Learning you will learn about machine learning methods that help automate the analysis of data. These computing methods help find hidden insights and information within the data without being explicitly programmed where or what to search for within the data.

This course begins by introducing you to supervised and unsupervised learning. You will learn how to distinguish between each type of learning and how to use them to analyse data. You will also learn about linear regression and how it can be used. The course introduces concepts about regularization and how to avoid over-fitting by using regularization.

Next, you will learn about using Excel and Matlab to perform simple and multiple regression. You will learn about confidence levels and subset selections. You will learn how to distinguish between R² and adjustment R² and what they both measure. The course will finish by introducing what the K-NN approach is in data analytics and when this approach should be used.

This course will be of great interest to professionals who work in the areas of data analytics and data science and who would like to learn more about methods used in machine learning. It will also be of interest to learners who are interested in computer science and would like to learn more about how machine learning gives computers the ability to learn without being explicitly programmed.

CERTIFICATION

To qualify for your official ALISON Diploma, Certificate or PDF you must study and complete all modules and score 80% or more in each of the course assessments. A link to purchase your Diploma certificate will then appear under the My Certificates heading of your My Account page.

LEARNING OUTCOMES

Having completed this course you will be able to:
- Define the difference between supervised learning, unsupervised learning, and reinforced learning.
- Explain what linear regression is.
- Describe when regularization can be used.
- Distinguish between supervised and unsupervised data.
- Define what confidence level is.
- Explain how to use Excel to perform a Multiple Regression.
- Explain subset selections.
- Distinguish between R² and adjustment R².
- Describe the K-NN approach.

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Course Rating (By Learners): 3 stars based on 10 votes
Course Title: Data Analytics - Introduction to Machine Learning
Course #: 1037
Course Publisher: Channel 9
Course Category: 9
Content Origin:
Course Description: In this free course Data Analytics – Introduction to Machine Learning you will learn about machine learning methods that help automate the analysis of data. These computing methods help find hidden insights and information within the data without being explicitly programmed where or what to search for within the data.

This course begins by introducing you to supervised and unsupervised learning. You will learn how to distinguish between each type of learning and how to use them to analyse data. You will also learn about linear regression and how it can be used. The course introduces concepts about regularization and how to avoid over-fitting by using regularization.

Next, you will learn about using Excel and Matlab to perform simple and multiple regression. You will learn about confidence levels and subset selections. You will learn how to distinguish between R² and adjustment R² and what they both measure. The course will finish by introducing what the K-NN approach is in data analytics and when this approach should be used.

This course will be of great interest to professionals who work in the areas of data analytics and data science and who would like to learn more about methods used in machine learning. It will also be of interest to learners who are interested in computer science and would like to learn more about how machine learning gives computers the ability to learn without being explicitly programmed.
License: This course is available from Channel 9 OpenCourseWare through the following Creative Commons licence:
Creative Commons License
Release Date: 7th Dec 2016
Content  
Course Duration (Avg Learner): 2-3 Hours
Video/Audio: High
Audio Only: High
Animation: None
Assessments: Yes
Education Level
Age appropriateness: 18+ Years
Minimum Grade/Class Level: Third Level
Validation: Level 6
ALISON Testing: Yes
Certification Availability
PDF Download: Yes
Parchment: Yes
Framed Certification: Yes

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Free, Online Data Analytics - Introduction to Machine Learning Course.