Imperial Business Analytics: From Data to Decisions

Learn the fundamentals of Python & drive business decisions with descriptive, predictive, and prescriptive analytics.

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Course Dates

STARTS ON

1 September 2022

Course Duration

DURATION

4 months, online
4-6 hours per week

Course Fee

PROGRAMME FEE

£1,790 £1,647 or get £179 off with a referral

Course Information Flexible payment available
Course Information Special group enrolment pricing
programme fee

£1,790 £1,647

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Why enrol for the Business Analytics programme?

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:

  • Take you through the fundamentals of the programming language Python to help you expand your understanding of business analytics.
  • It will teach you how to use descriptive, predictive and prescriptive analytics to identify, analyse and solve critical business problems.
  • It will help you understand and explore fundamental methods, frameworks and techniques of business analytics to make sense of your data and use it to make informed business decisions.

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.

Who is this programme for?

This international programme is designed for experienced professionals, including:

  • Technical managers implementing analytics in their function or organisation.
  • Professionals seeking to enter into the field of analytics & data science.
  • Mid-to-senior functional managers looking to improve their decision making using data.
  • Consultants aiming to develop their knowledge of business analytics.

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.

Drive business decisions with

Decorative image relating to Descriptive Analytics, Predictive Analytics and Prescriptive Analytics.

Modules

Module 1:

Maths and Statistics Primer

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.

Module 2:

Python Primer

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.

Module 3:

Descriptive Analytics

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.

Module 4:

Predictive Analytics

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.

Module 5:

Prescriptive Analytics

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.

Module 1:

Maths and Statistics Primer

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.

Module 4:

Predictive Analytics

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.

Module 2:

Python Primer

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.

Module 5:

Prescriptive Analytics

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.

Module 3:

Descriptive Analytics

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.

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Participant testimonials

Lin Emilie Lassen

"The combination of theory, maths and business application supported my learning and ability to apply the knowledge to my work straight away. Especially the assignments and multiple choices embedded in the course material helped test my grasp on the content."

— Lin Emilie Lassen, Product Owner, Swire Shipping

Christos Kotsis

"I liked the step by step approach, real and practical business world problems through which the material was delivered and of course the very good facilitators that provided explanations and examples to areas that needed more focus etc."

— Christos Kotsis, Treasurer & Risk Manager, A.M. Nomikos

Jared Phau

"The case studies and industry examples were pretty authentic and also effective in showing how these concepts could be used."

— Jared Phau, Senior Manager, Ministry of Health (Singapore)

Ben Dair

"A good introduction to machine learning and practical applications of data analysis and corresponding decision making."

— Ben Dair, Chief Product Officer at Motion Impossible

Case studies

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.

Netflix Using nearest neighbour methods in recommendation engines for TV shows and movies.

Netflix

Using nearest neighbour methods in recommendation engines for TV shows and movies.

Facebook Open-sourcing Torchnet to accelerate AI research.

Facebook

Open-sourcing Torchnet to accelerate AI research.

Microsoft Using and sharing a deep learning toolkit to increase advances in AI.

Microsoft

Using and sharing a deep learning toolkit to increase advances in AI.

Hewlett Packard Using an optimisation-based solution to improve the variety of product offerings.

Hewlett Packard

Using an optimisation-based solution to improve the variety of product offerings.

Union Airways Using discrete optimisation models for employee scheduling.

Union Airways

Using discrete optimisation models for employee scheduling.

Pandora Using nearest neighbour methods in recommendation engines for music.

Pandora

Using nearest neighbour methods in recommendation engines for music.

Kearns & Associates Using discrete optimisation models in construction.

Kearns & Associates

Using discrete optimisation models in construction.

New Bedford Steel Company Using optimisation models to lower transportation costs in coal acquisition.

New Bedford Steel Company

Using optimisation models to lower transportation costs in coal acquisition.

Security Industry Using nearest neighbour methods to improve facial recognition in the security industry.

Security Industry

Using nearest neighbour methods to improve facial recognition in the security industry.

American Red Cross Optimising blood processing to decrease cost per donation.

American Red Cross

Optimising blood processing to decrease cost per donation.

Memorial Sloan-Kettering Cancer Center Using optimisation models to improve treatment of prostate cancer.

Memorial Sloan-Kettering Cancer Center

Using optimisation models to improve treatment of prostate cancer.

The Netherlands Using optimisation techniques to develop new flood protection standards.

The Netherlands

Using optimisation techniques to develop new flood protection standards.

Faculty

Faculty Member Professor Wolfram Wiesemann

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... More info

Faculty Member Dr Alex Ribeiro-Castro

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... More info

Certificate

Example image of certificate that will be awarded after successful completion of this program

Certificate

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.

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The Imperial learning experience

Human

At 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.

Real

No 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.

FAQs

  • How do I know if this programme is right for me?

    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.


    Are there any prerequisites for this programme?

    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 learner.success@emeritus.org for assistance.


    Note that, unless otherwise stated on the programme web page, all programmes are taught in English, and proficiency in English is required.


    What is the typical class profile?

    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.


    What other dates will this programme be offered in the future?

    Check back at this programme web page or email us at learner.success@emeritus.org to inquire if future programme dates or the timeline for future offerings have been confirmed yet.

  • How much time is required each week?

    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.



    How will my time be spent?

    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:



    • Engaging with recorded video lectures from faculty
    • Attending webinars and office hours, as per the specific programme schedule
    • Reading or engaging with examples of core topics
    • Completing knowledge checks/quizzes and required activities
    • Engaging in moderated discussion groups with your peers
    • Completing your final project, if required

    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 contact us at learner.success@emeritus.org if you need further clarification on programme activities.



    What is it like to learn online with the learning collaborator, Emeritus?

    More than 250,000 professionals globally, across 80 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.

    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.


    How do I interact with other programme participants?

    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.

  • What are the requirements to earn the certificate?

    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 contact us at learner.success@emeritus.org if you need further clarification on any specific programme requirements.


    What type of certificate will I receive?

    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.


    Can I get the hard copy of the certificate?

    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.


    Do I receive alumni status after completing this programme?

    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.


    How long will I have access to the learning materials?

    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.

  • What equipment or technical requirements are there for this programme?

    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.


    Do I need to be online to access the programme content?

    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.

  • Can I still register if the registration deadline has passed?

    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.


    What is the programme fee and what forms of payment do you accept?

    The programme fee is noted at the top of this programme web page and usually referenced in the programme brochure as well.

    • Flexible payment options are available (see details below as well as at the top of this programme web page next to FEE).
    • Tuition assistance is available for participants who qualify. Please email learner.success@emeritus.org.

    What if I don’t have a credit card? Is there another method of payment accepted?

    Yes, you can do the bank remittance in the programme currency via wire transfer or debit card. Please contact your programme advisor or email us at learner.success@emeritus.org for details.


    I was not able to use the discount code provided. Can you help?

    Yes! Please email us at learner.success@emeritus.org with the details of the programme you are interested in, and we will assist you.


    How can I obtain an invoice for payment?

    Please email learner.success@emeritus.org with your invoicing requirements and the specific programme you’re interested in enrolling in.


    Is there an option to make flexible payments for this programme?

    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.


    How can I obtain a W9 form?

    Please email us at learner.success@emeritus.org for assistance.

  • What is the policy on refunds and withdrawals?

    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.



    What is the policy on deferrals?

    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.

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