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Overview
This Machine Learning with Python - A Practical Introduction course at IBMx dives into the basics of Machine Learning using Python, an approachable and well-known programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each.
Key facts
This course is part of IBM Data Science Professional Certificate Program
You'll look at real-life examples of Machine Learning and how it affects society in ways you may not have guessed!
We'll explore many popular algorithms including Classification, Regression, Clustering, and Dimensional Reduction and popular models such as Train/Test Split, Root Mean Squared Error and Random Forests.
Most importantly, you will transform your theoretical knowledge into practical skill using hands-on labs. Get ready to do more learning than your machine!
Programme Structure
What you will learn
- Explain the difference between the two main types of machine learning methods: supervised and unsupervised
- Describe Supervised learning algorithms, including classification and regression
- Describe Unsupervised learning algorithms, including Clustering and Dimensionality Reduction
- Explain how statistical modelling relates to machine learning and how to compare them
- Discuss real-life examples of the different ways machine learning affects society
- Build a prediction model using classification
Key information
Duration
- Part-time
- 35 days
- 4 hrs/week
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
- Self-paced
Campus Location
- Portland, United States
Disciplines
Software Engineering Machine Learning View 330 other Short Courses in Software Engineering in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
To obtain additional information about the programme, we kindly suggest that you visit the programme website, where you can find further details and relevant resources.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
-
International Applies to you
Applies to youNon-residents99 USD / full≈ 99 USD / full - Out-of-State99 USD / full≈ 99 USD / full
Additional Details
- Add a Verified Certificate for $99 USD
- Limited access: free
Funding
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