The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events Specialist
No prior programming knowledge required
Download Brochure
TBD
10 weeks, online
4-6 hours per week
Our participants tell us that taking this programme together with their colleagues helps to share common language and accelerate impact.
We hope you find the same. Special pricing is available for groups.
The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events SpecialistBased on the information you provided, your team is eligible for a special discount, for Imperial Machine Learning for Decision Making starting on TBD .
We’ve sent you an email with enrolment next steps. If you’re ready to enrol now, click the button below.
Have questions? Email us at group-enrollments@emeritus.org.
You have been invited to Imperial Machine Learning for Decision Making.
To get started, please complete the information form on the following page.
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Gain a practical understanding of the tools and techniques used in machine learning applications for business. By the end of this programme, you will be able to:
of Netflix users select films recommended to them by the company’s ML algorithms
is the projected global ML market value by 2024
Investment in ML application in Q1 2019
This programme is designed for experienced managers and executives working in technology, including:
The programme is relevant across industries, including: IT Products & Services, Banking & Financial Services, Healthcare, Consulting, Education, FMCG, Retail, and Telecommunications.
No prior programming experience required.
What is machine learning, the machine learning process, the machine learning landscape, machine learning in the real world.
Is learning feasible at all, interpreting the bound, a probabilistic setting, when is machine learning feasible.
Which fit is "right", test set, validation set, the "training set - validation set - test set" approach.
Performance measures for regression, lift charts for classification problems, problems (use confusion matrix), lift charts for regression problems.
Oversampling, k-fold cross-validation.
K-nearest neighbours for classification, binary and categorical predictors, k-nearest neighbours for regression, distance functions, how should we choose k.
Motivation, exact Bayes classifiers, the Laplace Estimator, Bayes' Theorem, naïve Bayes classifiers.
Classification trees, choosing the best split: Part 2, regression trees, random forests and boosting algorithms, choosing the best split: Part 1, pruning a classification tree, bagging.
Motivation, hierarchical clustering is myopic, practical concerns of a cluster, hierarchical clustering, k-means clustering, analysis.
What is machine learning, the machine learning process, the machine learning landscape, machine learning in the real world.
K-nearest neighbours for classification, binary and categorical predictors, k-nearest neighbours for regression, distance functions, how should we choose k.
Is learning feasible at all, interpreting the bound, a probabilistic setting, when is machine learning feasible.
Motivation, exact Bayes classifiers, the Laplace Estimator, Bayes' Theorem, naïve Bayes classifiers.
Which fit is "right", test set, validation set, the "training set - validation set - test set" approach.
Classification trees, choosing the best split: Part 2, regression trees, random forests and boosting algorithms, choosing the best split: Part 1, pruning a classification tree, bagging.
Performance measures for regression, lift charts for classification problems, problems (use confusion matrix), lift charts for regression problems.
Motivation, hierarchical clustering is myopic, practical concerns of a cluster, hierarchical clustering, k-means clustering, analysis.
Oversampling, k-fold cross-validation.
Prerequisite: This programme will require prior knowledge of statistics, probability and linear algebra.
Note: For those wanting to develop deeper skills with analytics, academic credit from this programme can be applied to the Imperial MSc in Business Analytics in the future.
Professor Wolfram Wiesemann
Professor of Analytics and Operations, Imperial College Business School
Wolfram Wiesemann is Professor of Analytics and Operations at Imperial College Business School, London, where he also serves as the Academic Director of the MSc Business Analytics programme as well as a Fellow of the KPMG Centre for Advanced Business Analytics. Before joining the faculty of Imperial College Business School in 2013, he was a post-doctoral researcher at Imperial College London (2010-2011) and an Imperial College Research Fellow (2011-2012). He was a visiting researcher at the Institute of Statistics and Mathematics at Vienna University of Economics and Business, Austria, in 2010, the Computer-Aided Systems Laboratory at Princeton University, USA, in 2011 and the Industrial Engineering and Operations Research Department at Columbia University, USA, in 2012. Wolfram’s research interests revolve around the methodological aspects of decision-making under uncertainty and machine learning, as well as applications in operations management, energy and finance.
Upon completion of the programme, participants will be awarded a verified Digital Certificate by Imperial College Business School Executive Education.
Future learning:
For those who want to progress their skills to the next level, an academic credit from this programme can be applied to the Imperial MSc in Business Analytics in the future. The MSc programme enables graduates to understand the challenge of managing large data sets and to provide them with a skill set to meet this challenge. The programme combines academic rigour and practical relevance. To learn more, visit the programme website.
Please note that this programme contributes to earning Associate Alumni status. Visit the Associate Alumni page to find out more.
Download BrochureImperial College Executive Education also provides the Live Virtual AI and Machine Learning in Financial Services programme. This programme builds a strong foundation in AI, big data, and machine learning and helps you explore what innovation will look like within financial services. Digital Transformation: 5 Game-Changing Technologies for Business.
After reviewing the information on the programme landing page, we recommend you submit the short form above to gain access to the programme brochure, which includes more in-depth information. If you still have questions about whether this programme is a good fit for you, please email learner.success@emeritus.org, and a dedicated programme advisor will follow up with you very shortly.
Some programmes do have prerequisites, particularly the more technical ones. This information will be noted on the programme landing page, as well as in the programme brochure. If you are uncertain about programme prerequisites and your capabilities, please email us at the ID mentioned above.
Note that, unless otherwise stated on the programme web page, all programmes are taught in English, and proficiency in English is required.
More than 50 per cent of our participants are from outside the United States. Class profiles vary from one cohort to the next, but generally, our online certificates draw a highly diverse audience in terms of professional experience, industry and geography—leading to a very rich peer learning and networking experience.
Check back at this programme web page or email us to inquire if future programme dates or the timeline for future offerings have been confirmed yet.
Each programme includes an estimated learner effort per week. This is referenced at the top of the programme landing page under the Duration section, as well as in the programme brochure, which you can obtain by submitting the short form at the top of this web page.
We have designed this programme to fit into your current working life as efficiently as possible. Time will be spent among a variety of activities, including:
The programme is designed to be highly interactive while also allowing time for self-reflection and to demonstrate an understanding of the core topics through various active learning exercises. Please email us if you need further clarification on programme activities.
More than 300,000 learners across 200 countries have chosen to advance their skills with Emeritus and its educational learning partners. In fact, 90 per cent of the respondents of a recent survey across all our programmes said that their learning outcomes were met or exceeded.
All the contents of the course would be made available to students at the commencement of the course. However, to ensure the programme delivers the desired learning outcomes the students may appoint Emeritus to manage the delivery of the programme in a cohort-based manner the cost of which is already included in the overall course fee of the course.
A dedicated programme support team is available 24/5 (Monday to Friday) to answer questions about the learning platform, technical issues or anything else that may affect your learning experience.
Peer learning adds substantially to the overall learning experience and is an important part of the programme. You can connect and communicate with other participants through our learning platform.
Each programme includes an estimated learner effort per week, so you can gauge what will be required before you enrol. This is referenced at the top of the programme landing page under the Duration section, as well as in the programme brochure, which you can obtain by submitting the short form at the top of this web page. All programmes are designed to fit into your working life.
This programme is scored as a pass or no-pass. Participants must complete the required activities to pass and obtain the certificate of completion. Some programmes include a final project submission or other assignments to obtain passing status. This information will be noted in the programme brochure. Please email us if you need further clarification on any specific programme requirements.
Upon successful completion of the programme, you will receive a smart digital certificate. The smart digital certificate can be shared with friends, family, schools or potential employers. You can use it on your cover letter or resume and/or display it on your LinkedIn profile.
The digital certificate will be sent approximately two weeks after the programme, once grading is complete.
No, only verified digital certificates will be issued upon successful completion. This allows you to share your credentials on social networking platforms, such as LinkedIn, Facebook and Twitter.
No, there is no alumni status granted for this programme. In some cases, there are credits that count towards a higher level of certification. This information will be clearly noted in the programme brochure.
You will have access to the online learning platform and all the videos and programme materials for 12 months following the programme start date. Access to the learning platform is restricted to registered participants per the terms of agreement.
Participants will need the latest version of their preferred browser to access the learning platform. In addition, Microsoft Office and a PDF viewer are required to access documents, spreadsheets, presentations, PDF files and transcripts.
Yes, the learning platform is accessed via the internet, and video content is not available for download. However, you can download files of video transcripts, assignment templates, readings, etc. For maximum flexibility, you can access programme content from a desktop, laptop, tablet or mobile device.
Video lectures must be streamed via the internet, and any livestream webinars and office hours will require an internet connection. However, these sessions are always recorded, so you can view them later.
Yes, you can register up until seven days past the published start date of the programme without missing any of the core programme material or learnings.
The programme fee is noted at the top of this programme web page and usually referenced in the programme brochure as well.
Yes, you can do the bank remittance in the program currency via wire transfer or debit card. Please contact your programme advisor or email us for details.
Yes! Please email us with the details of the programme you are interested in, and we will assist you.
Please email us your invoicing requirements and the specific programme you’re interested in enrolling in.
Yes, the flexible payment option allows a participant to pay the programme fee in instalments. This option is made available on the payment page and should be selected before submitting the payment.
Please connect with us via email for assistance.
You may request a full refund within seven days of your payment or 14 days after the published start date of the programme, whichever comes later. If your enrolment had previously been deferred, you will not be entitled to a refund. Partial (or pro-rated) refunds are not offered. All withdrawal and refund requests should be sent to admissions@emeritus.org.
After the published start date of the programme, you have until the midpoint of the programme to request to defer to a future cohort of the same programme. A deferral request must be submitted along with a specified reason and explanation. Cohort changes may be made only once per enrolment and are subject to availability of other cohorts scheduled at our discretion. This will not be applicable for deferrals within the refund period, and the limit of one deferral per enrolment remains. All deferral requests should be sent to admissions@emeritus.org.