Columbia’s MicroMasters® programme in Business Analytics will empower learners with the skills, insights and understanding to improve business performance using data, statistical and quantitative analysis, and explanatory and predictive modelling to help make actionable decisions.
The curriculum is designed to provide learners with a series of courses that emphasises the use of statistical analysis, computing tools, and mathematical models to predict the outcomes of various business decisions, and identify the best implementation.
This programme consists of four courses related to business analytics and contains specific elements to help you engage with the content and other people in the programme, network with the appropriate stakeholders, and progress through to the next step in your academic or professional career.
The Business Analytics MicroMasters® Programme from Columbia includes the following courses:
Analytics in Python
Learn the fundamental of programming in Python and develop the ability to analyse data and make data-driven decisions.
Data, Models and Decisions in Business Analytics
Learn fundamental tools and techniques for using data towards making business decisions in the face of uncertainty.
Develop quantitative models that leverage business data to forecast sales and support important marketing decisions.
Demand and Supply Analytics
Learn how to use data to develop insights and predictive capabilities to make better business decisions.
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No Need to Travel
04th February 2019
8-10hrs Effort per week/module
At the end of this programme, learners will be able to:
Apply methods, tools, and software for acquiring, managing/storing, and accessing structured and unstructured data.
Prepare data for statistical analysis, perform basic exploratory and descriptive analysis, and apply statistical techniques to analyse data.
Apply descriptive, predictive and prescriptive analytics to business modeling and decision-making.
Demonstrate orally, and in writing, the ability to explain complex analytical models and results.
Analytics in Python.
Data, Models and Decisions in Business Analytics.
Demand and Supply Analytics.
Live meetings, speaker series, peer networking, and more
Case studies and application problems.