MIT Sloan and MIT Schwarzman College
Unsupervised Machine Learning: Unlocking the Potential of Data
Reimagine the untapped potential of your underutilized data by employing unsupervised machine learning techniques.
Starting soon
Start date
12 June 2024
Enroll by 04 June 2024
Course duration
6 weeks
Excluding orientation
Language
English
Access resources from start date
Effort
6–8 hours per week
Self-paced learning online
Course overview
Duration: 6 weeks (excluding orientation)
Traditionally, the process of training artificial intelligence (AI) models involved using large sets of annotated data. Consequently, unorganized and limited datasets that hold immense value are often disregarded. However, with the latest machine learning (ML) developments, businesses can leverage these untapped data sources to gain a competitive edge.
The Unsupervised Machine Learning: Unlocking the Potential of Data online short course, offered by the MIT Sloan School of Management and the MIT Schwarzman College of Computing, delves into the technical and strategic aspects of unsupervised learning techniques. Over six weeks, you’ll explore these approaches, their capabilities, limitations, use cases, and practical applications. Through this course, you’ll realize the latent potential of your data, regardless of its size or quality, and develop customized AI solutions that cater to your unique business challenges.
Is this course for you?
This program aims to assist business leaders in capitalizing on the possibilities presented by unsupervised machine learning. Technology managers and decision makers can formulate strategies for acquiring new data by gaining knowledge on how to utilize unstructured data. The program material will be valuable for IT and tech experts seeking the latest advancements in unsupervised learning and data analysts and scientists seeking to enhance their expertise in utilizing computer vision technologies.
The ability to code is not a prerequisite for this program. However, this program contains complex concepts that require an existing understanding and above-average knowledge of machine learning.
Course overview
Introduction
Duration: 6 weeks (excluding orientation)
Traditionally, the process of training artificial intelligence (AI) models involved using large sets of annotated data. Consequently, unorganized and limited datasets that hold immense value are often disregarded. However, with the latest machine learning (ML) developments, businesses can leverage these untapped data sources to gain a competitive edge.
The Unsupervised Machine Learning: Unlocking the Potential of Data online short course, offered by the MIT Sloan School of Management and the MIT Schwarzman College of Computing, delves into the technical and strategic aspects of unsupervised learning techniques. Over six weeks, you’ll explore these approaches, their capabilities, limitations, use cases, and practical applications. Through this course, you’ll realize the latent potential of your data, regardless of its size or quality, and develop customized AI solutions that cater to your unique business challenges.
Is this course for you?
This program aims to assist business leaders in capitalizing on the possibilities presented by unsupervised machine learning. Technology managers and decision makers can formulate strategies for acquiring new data by gaining knowledge on how to utilize unstructured data. The program material will be valuable for IT and tech experts seeking the latest advancements in unsupervised learning and data analysts and scientists seeking to enhance their expertise in utilizing computer vision technologies.
The ability to code is not a prerequisite for this program. However, this program contains complex concepts that require an existing understanding and above-average knowledge of machine learning.
What will set you apart
The ability to harness previously unused data within your organization to deploy ML models.
The technical foundation needed to address business challenges and drive AI initiatives through representation learning.
An understanding of the challenges, opportunities, and important considerations of generative models.
The skills to evaluate and interact with existing pre-trained models and leverage these effectively in your organization.
The skills required to build transparent and interpretable ML models in your context. Course curriculum
Orientation module
Welcome to your Online Campus
Module 1
The potential of data
Module 2
Learning and leveraging representations
Module 3
Generative models
Module 4
AI building blocks
Module 5
Adapting AI tools
Module 6
Challenges and the future
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Faculty Directors
Who you'll learn from
Antonio Torralba
Delta Electronics Professor of Electrical Engineering and Computer Science, Head of AI+D Faculty, EECS Department, MIT CSAIL
Vivek Farias
Patrick J. McGovern (1959) Professor, Professor of Operations Management, MIT Sloan School of Management
Phillip Isola
Associate Professor in EECS, MIT
Jacob Andreas
Assistant Professor, MIT CSAIL
Rama Ramakrishnan
Professor of the Practice, Data Science and Applied Machine Learning, MIT Sloan School of Management
About the certificate
Acquire the knowledge to leverage your data for building AI systems and earn an official certificate of completion from the MIT Sloan School of Management.
This program also counts toward an MIT Sloan Executive Certificate, which you can earn upon completion of four programs where at least three of the four come from your chosen certificate track and at least one is completed in person. Find full details here.
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We deliver market-led courses that equip working professionals with the expertise required to upskill, reskill or kickstart a completely new career. Through a data-driven approach, we analyze future skills requirements and ensure all courses address this need. We ensure that leading universities and institutions are your expert guides and our people, technology, and resources are your engine – together we power more than just education, we power your potential.
Read more about GetSmarter here and edX here.
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Payment options
You can pay your course fees before the course starts, or you may opt for a split payment plan on courses that are nine weeks and shorter. For courses 10 weeks and longer, there is a three-part payment plan available. To find out more about payment options please visit our Payment and Financing page, or contact an Enrollment Adviser, to find out which option you qualify for.
Manage your time
GetSmarter's learning model is designed to help you, as a working professional, improve your skills without compromising on work and family responsibilities. The course work is broken up into weekly, manageable bite-sized modules, with incremental deadlines, designed to help you pace yourself over the duration of the course and allow you the legroom to work when it suits you best.
At the beginning of each module you'll be presented with the course content and assignments necessary for completion. You also have access to your Success Adviser who will help you manage your time, and support you with any administrative or technical queries you might have.
Seek employer assistance
By improving your skills and industry knowledge, you'll have an influence on the success of your organization. Why wouldn't you ask your boss to help you fund your studies if it's going to have an impact on the way you do business?
Of our past students, 37 percent have received financial assistance from their employers. You can ask for help, too. Here is a guide to show you how to request financial assistance from your employer.
If you are a Learning & Development (L&D) manager, or involved in training and upskilling for an organization, you can request information regarding our corporate offering on our GetSmarter for business page.
How to change your start date
As part of our commitment to your professional development, GetSmarter offers you a two-week period to change your course start date or request your money back if you’re not fully satisfied.
To qualify for a deferral of your course start date, or to cancel your enrollment and receive a refund of your course fee, your request would need to reach our Success Advisers before the release of Module 2. For more information, please read our Terms and Conditions.
Discover the Online Campus
The Online Campus will be your virtual classroom for the duration of your course. Through its easy-to-use interface you'll have access to a diverse variety of course content formats including: interactive videos, module notes, practice quizzes, presentations, assignment briefs, and additional web resources.
On the Online Campus, you'll also be able to ask questions and interact with your fellow students and teaching team through the discussion forums. If you are looking for your Online Campus login, please see the list of university partner login pages here.
