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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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.

Participant testimonials

The best part was getting introduced to descriptive, predictive and prescriptive analytics in one programme, and gives a good overview. Often, these topics are treated separately, and it is then hard ...
Fabrice Dunand
Senior Director, Global Strategic Planning & Market Intelligence,
Ferring Pharmaceuticals
The assignments for each week were both interesting and well structured to test if you had understood the tutorial. I found this part the best method of applying hard theory to practical business situ...
Lynne Chang
Business Analyst,
Fidelity International
This programme is an excellent review for those who want to upgrade their skills and knowledge of statistics or analytics. It has helped me refocus my business mindset towards data.
Hansa Kraikosol
Managing Director,
Playmondo Group
The programme helped me learn the theory of basic machine learning, and it opened my knowledge of how I can use those methods to analyse the data and get the optimal solution.
Xupeng Ding
Marketing Analytics & Consumer Insights Lead,
Warner Bros. Entertainment
As an online executive programme, the programme gives a very good overview of business analytics, including hands-on practice. The office hours by the learning facilitators and professor webinars were...
Swapna Kartik
Client Data & Analytics Product Management Lead,
Citi

Drive business decisions with

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

Meet the faculty

Faculty Member Professor Wolfram Wiesemann
PROFESSOR WOLFRAM WIESEMANN

Professor of Analytics and Operations; Head of the Analytics, Marketing and Operations Department; Fellow, Imperial Business Analytics Centre Operations Management Department, Imperial College London

Wolfram Wiesemann is a professor of analytics and operations as well as the head of the Analytics, Marketing and Operations department at Imperial College Business School. In ...

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 t...

What you will learn

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.

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.

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.

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.

Certificate

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.

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

Didn't find what you were looking for? Write to us at learner.success@emeritus.org or Schedule a call with one of our Programme Advisers or call us at +44 208 629 1765 (UK) / +1 315 509 2976 (US) / +65 3138 2451 (SG)

Early registrations are encouraged. Seats fill up quickly!

Flexible payment options available.

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