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
Learn the fundamentals of Python & drive business decisions with descriptive, predictive, and prescriptive analytics.
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18 October 2023
16 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 SpecialistTuition assistance is live as per below schedule. The full programme fee is £1880 as of the start date.
Imperial Business Analytics: From Data to Decisions is an online programme brought to you by Executive Education at Imperial College Business School. This immersive and interactive programme will:
You will draw on expertise from Imperial College Business School faculty, industry experts, case studies and your peers. You will also explore the practical applications of the analytical frameworks you are learning.
There is no prior programming knowledge required.
Percentage organizations are investing in data initiatives
Percentage organizations have appointed Chief Data or Analytics Officers, or both as one role
Percentage organizations are seeing returns on their data and AI investments
This international programme is designed for experienced professionals, including:
The programme’s content and lessons are applicable across industries, including: banking and financial services, IT, healthcare, consulting, advertising, education, fast moving consumer goods, retail, and telecommunications.
Professor Wolfram Wiesemann
Dr Alex Ribeiro-Castro
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.
Dr Alex Ribeiro-Castro
Data Scientist
Alex holds an advisory position linked to the Business Analytics MSc and is an occasional guest lecturer for Executive Education. He also works as a quantitative analyst for the financial industry. He was previously a Data Scientist and Senior Teaching Fellow at Imperial College Business School. Dr Ribeiro-Castro holds a MA and PhD in Mathematics from the University of California (Santa Cruz), and held a professorship in Mathematics from the Pontifical Catholic University (PUC-Rio) in Rio de Janeiro.
Learn the basics of statistics and probability, including theory and models, Bayes’ rule, conditional probability, probability distribution, binomial distribution, central limit theorem, and manipulating normal variables.
Gain an overview of operating systems; use variables in Python; create and manage lists; understand tuples and dictionaries in Python; delve into Boolean and conditional variables; expand your knowledge of functions, and work on code manipulation.
Evaluate data for business decisions; estimate statistics of a data set and maximum likelihood; learn detection and quantification of correlation; understand outliers and linear regression, and discover how these concepts are used in real-life applications.
Dive into machine learning; understand supervised learning; compare forecasting vs. inference; use nearest neighbors for classification; predict outcomes using regression trees; classify data using support vector machines; measure the similarity of data clusters, and predict outcomes for different clusters.
Build your knowledge of linear programming by tackling problems of optimisation, production planning, and capital budgeting; identify constraints and the optimal solution; model business problems as linear programmes; learn tricks of the trade.
Learn the basics of statistics and probability, including theory and models, Bayes’ rule, conditional probability, probability distribution, binomial distribution, central limit theorem, and manipulating normal variables.
Dive into machine learning; understand supervised learning; compare forecasting vs. inference; use nearest neighbors for classification; predict outcomes using regression trees; classify data using support vector machines; measure the similarity of data clusters, and predict outcomes for different clusters.
Gain an overview of operating systems; use variables in Python; create and manage lists; understand tuples and dictionaries in Python; delve into Boolean and conditional variables; expand your knowledge of functions, and work on code manipulation.
Build your knowledge of linear programming by tackling problems of optimisation, production planning, and capital budgeting; identify constraints and the optimal solution; model business problems as linear programmes; learn tricks of the trade.
Evaluate data for business decisions; estimate statistics of a data set and maximum likelihood; learn detection and quantification of correlation; understand outliers and linear regression, and discover how these concepts are used in real-life applications.
The case studies and industry examples featured throughout the programme provide a wide-ranging look at how companies, organisations, and governments are applying analytics techniques to solve business problems.
Using nearest neighbour methods in recommendation engines for TV shows and movies.
Open-sourcing Torchnet to accelerate AI research.
Using and sharing a deep learning toolkit to increase advances in AI.
Using an optimisation-based solution to improve the variety of product offerings.
Using discrete optimisation models for employee scheduling.
Using nearest neighbour methods in recommendation engines for music.
Using discrete optimisation models in construction.
Using optimisation models to lower transportation costs in coal acquisition.
Using nearest neighbour methods to improve facial recognition in the security industry.
Optimising blood processing to decrease cost per donation.
Using optimisation models to improve treatment of prostate cancer.
Using optimisation techniques to develop new flood protection standards.
Upon completion of the programme, participants will be awarded a verified Digital Certificate by Imperial College Business School Executive Education.
Please note that this programme contributes to earning Associate Alumni status. Visit the Associate Alumni page to find out more.
Download BrochureAt Imperial College Business School, we create people-centric learning experiences. From conception through to delivery, we are guided by the principle that learning is a creative, personal and above all, human process. Our high quality, crafted learning environments are highly interactive, community-orientated and actively tutored. Our programmes offer an engaging experience designed to facilitate natural learning behaviours.
RealNo compromises. Our online programmes offer the absolute equivalent of our campus-based programmes. They adopt the same rigorous academic standards, are delivered via our world-leading faculty and offer a comparable high-touch approach to the classroom experience.
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.
Flexible payment options available.