The London School of Economics and Political Science
Machine Learning: Practical Applications
Acquire technical machine learning skills to address business challenges and guide decision-making processes.
Start date
05 March 2025
Course duration
8 weeks
Excluding orientation
Language
English
Access resources from start date
Effort
8–10 hours per week
Self-paced learning online
Course overview
The projected value of the data market by 2025, reflecting the escalating demand for skilled data specialists.
Tech Guide (Jan, 2024).
The forecasted global machine learning market size by 2032, up from $38.11 billion in 2022.
Precedence Research (Jul, 2023).
Duration: 8 weeks (excluding orientation)
The convergence of various fields, such as data mining, statistics, optimisation, and computing, has given rise to machine learning, which is rapidly gaining adoption across diverse industries. One of the key advantages of machine learning is its capability to handle large datasets and solve complex problems. From commercial applications like search engines and recommendation systems (think Netflix and Amazon) to financial institutions for predicting customer behaviour, compliance, risk, and algorithmic trading, machine learning is proving to be a game-changer.
If you're looking to upskill in machine learning and its applications, the London School of Economics and Political Science (LSE) offers an eight-week online technical course that covers a comprehensive range of machine learning methods. Through practical case studies and hands-on exercises, you'll learn how to apply machine learning models to real-world problems and interpret the resulting predictions to make informed business decisions. The course is designed to help you build your expertise in modern business analytics and gain valuable insights into how machine learning is used today.
Is this course for you?
If you are a mid to senior manager, data specialist, consultant, analyst, IT, or business professional looking to integrate machine learning techniques to improve data analytics in your organisation, this online certificate course is designed for you. This course offers an in-depth exploration of core principles and machine learning methods, which will benefit those interested in practical applications. Whether you are looking to upskill, transition into a data science role, or improve your understanding of business applications of data science, this course will help develop and validate your practical machine learning skills and knowledge.
Prerequisites
This course is technical in nature. It makes use of coding in R and covers the application of machine learning in business. Some algebraic and calculus knowledge is strongly advised, but is not required. Training in tertiary-level statistics and knowledge of a functional or object-oriented language are advantageous. HTML is not considered a programming language in this context. No specific software is required for this online certificate course.
This Machine Learning: Practical Applications online certificate course is certified by the United Kingdom CPD Certification Service, and may be applicable to individuals who are members of, or are associated with, UK-based professional bodies.
The course has an estimated 75 hours of learning.
Note: should you wish to claim CPD activity, the onus is upon you. The London School of Economics and Political Science (LSE) and GetSmarter accept no responsibility, and cannot be held responsible, for the claiming or validation of hours or points.
Course overview
Introduction
Duration: 8 weeks (excluding orientation)
The convergence of various fields, such as data mining, statistics, optimisation, and computing, has given rise to machine learning, which is rapidly gaining adoption across diverse industries. One of the key advantages of machine learning is its capability to handle large datasets and solve complex problems. From commercial applications like search engines and recommendation systems (think Netflix and Amazon) to financial institutions for predicting customer behaviour, compliance, risk, and algorithmic trading, machine learning is proving to be a game-changer.
If you're looking to upskill in machine learning and its applications, the London School of Economics and Political Science (LSE) offers an eight-week online technical course that covers a comprehensive range of machine learning methods. Through practical case studies and hands-on exercises, you'll learn how to apply machine learning models to real-world problems and interpret the resulting predictions to make informed business decisions. The course is designed to help you build your expertise in modern business analytics and gain valuable insights into how machine learning is used today.
Is this course for you?
If you are a mid to senior manager, data specialist, consultant, analyst, IT, or business professional looking to integrate machine learning techniques to improve data analytics in your organisation, this online certificate course is designed for you. This course offers an in-depth exploration of core principles and machine learning methods, which will benefit those interested in practical applications. Whether you are looking to upskill, transition into a data science role, or improve your understanding of business applications of data science, this course will help develop and validate your practical machine learning skills and knowledge.
Prerequisites
This course is technical in nature. It makes use of coding in R and covers the application of machine learning in business. Some algebraic and calculus knowledge is strongly advised, but is not required. Training in tertiary-level statistics and knowledge of a functional or object-oriented language are advantageous. HTML is not considered a programming language in this context. No specific software is required for this online certificate course.
This Machine Learning: Practical Applications online certificate course is certified by the United Kingdom CPD Certification Service, and may be applicable to individuals who are members of, or are associated with, UK-based professional bodies.
The course has an estimated 75 hours of learning.
Note: should you wish to claim CPD activity, the onus is upon you. The London School of Economics and Political Science (LSE) and GetSmarter accept no responsibility, and cannot be held responsible, for the claiming or validation of hours or points.
What will set you apart
The confidence to make more informed business decisions and solve complex problems by understanding how different machine learning models can be applied to a variety of data sets.
The skills to implement various machine learning techniques, including regression, variable selection, shrinkage methods, classification, dimension reduction, and unsupervised learning.
Upgraded mathematics and statistics knowledge, and the foundations of coding in R.
Knowledge of the latest frontiers of machine learning, such as neural networks, and how these can be applied to your business context.
Unlimited access to edX’s Career Engagement Network, offering you exclusive resources and events to support your professional journey and drive your career forward.Course curriculum
Orientation module
Welcome to your Online Campus
Module 1
Learning from data
Module 2
Principles of machine learning
Module 3
Regression
Module 4
Variable selection and shrinkage methods
Module 5
Classification
Module 6
Tree-based methods and ensemble learning
Module 7
Introduction to neural networks
Module 8
Unsupervised learning
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What past students
think
David Ooms
Independent digital transformation consultant and manager, Digitalize & Conquer
I had a very pleasant experience overall taking the Machine Learning: Practical Applications course. The course text explains the subject in clear wording and I truly appreciated the opportunity to apply the concepts on real-world datasets. The forum discussions also encouraged us to think about ways to use the knowledge and skills that were acquired in our own professional contexts. Totally worth the time invested!
Your Course Convenors
Dr Yining Chen
Associate Professor, Department of Statistics, LSE
Dr Kostas Kalogeropoulos
Associate Professor, Department of Statistics, LSE
Dr Xinghao Qiao
Associate Professor, Department of Statistics, LSE
About the certificate
Cultivate technical expertise in machine learning and earn an official certificate of competence from the London School of Economics and Political Science.
Assessment is continuous and based on a series of practical assignments completed online. In order to be issued with a digital certificate, you’ll need to meet the requirements outlined in the course handbook. The handbook will be made available to you as soon as you begin the course.
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Why choose GetSmarter?
GetSmarter operates as edX's partner for premium online short course products from the world's leading universities and institutions. With edX, we leverage our people, technology, and resources to power your education and your potential.
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.
Find out more about GetSmarter’s approach to digital learning, course design, and online delivery here.
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 visit your Account page here.
