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Accelerate your career in analytics

MicroMasters® Program in
Predictive Analytics for Business Applications
EdinburghX

What you will learn

  • Identify various business settings in which predictive analytics can be used
  • Formulate a predictive model suitable for a broad range of problem scenarios
  • Build and use predictive models both for classification and regression problems
  • Implement insights in Python
  • Interpret predictive models to solve business problems, and critically reflect on their outcomes

This is the age of Big Data. Market forecasts indicate that worldwide revenues for big data and business analytics solutions are expected to reach $189.1 billion this year, an increase of 12% since 2018. IDC expects worldwide BDA revenue will be $274.3 billion by 2022. (Source: IDC)

Organisations hold more information about their business environments than ever before. Increasingly, these organisations are recognising the role of data science in gaining insights and out-thinking competitors. As a result, there is a growing demand for employees and managers who have advanced analytics skills and the ability to make informed decisions that drive organisational success.

Predictive analytics is being adopted across many business sectors to predict trends and build models that support proactive business decisions and identify both risks and opportunities.

This MicroMasters® program has been designed by the University of Edinburgh to equip you with the skills to successfully set up and deploy your own predictive analysis. The program breaks the process down into four key parts that will help you to develop strong capabilities in this field.

You will be introduced to the major concepts used in a predictive model, learn how to prepare data for modelling, and build predictive models using a range of statistical and machine learning methodologies on a variety of real-life datasets. You will discuss, evaluate, implement, and test each approach to get you acquainted with performing a solid predictive exercise.

Prerequisites
This MicroMasters program is intended for those who have undergraduate level or equivalent professional experience/background in mathematics, statistics or similar subject area (linear algebra, calculus etc.). Previous experience with a procedural programming language is beneficial (Java, C, Python, Visual Basic etc.)

Expert instruction
5 graduate-level courses
Instructor-led
Assignments and exams have specific due dates
1 year
240 - 300 hours of effort
$1,500
USD
For the full program experience

Courses in this program

  1. EdinburghX's Predictive Analytics for Business Applications MicroMasters® Program

  2. Starts Sep 17, 2019
    8–10 hours per week, for 6 weeks
    In the age of Big Data, businesses need predictive analysts to help them excel against competitors. Take a deep-dive into the first steps of the predictive analytics process.
  3. Starts Nov 12, 2019
    8–10 hours per week, for 6 weeks
    Gain an in-depth understanding of evaluation and sampling approaches for effective predictive modelling.
  4. Starts Jan 14, 2020
    8–10 hours per week, for 6 weeks
    Learn how to use regression and Bayesian inference to build statistical predictive models.
  5. Starts Mar 10, 2020
    8–10 hours per week, for 6 weeks
    Learn how to build predictive models using tree-based and other machine learning approaches.
  6. Starts May 26, 2020
    8–10 hours per week, for 6 weeks
    Apply your predictive modelling acumen in a business case setting.
  7. What is a MicroMasters Program?
    MicroMasters programs are a series of graduate level courses from top universities designed to advance your career. MicroMasters program certificates showcase deep learning and in-demand skills to employers and can help you get started on a path toward completing an advanced degree.

    How to Earn a MicroMasters Program Certificate
    To earn the program certificate, learners must complete and successfully earn a verified certificate in all four courses in this program, in addition to the final project.

    From Program Certificate to a Master’s Degree
    MicroMasters programs are designed to offer learners a pathway to an advanced degree and can count as credit toward completing a Master’s degree program. Learners who successfully earn this MicroMasters program certificate may apply for admission to a Master’s program, and if accepted, the MicroMasters program certificate will count towards the degree.

    Learners who successfully earn this MicroMasters program certificate can apply to the on-campus Masters in Business Analytics at the University of Edinburgh. Successful completion of the MicroMasters program does not guarantee acceptance to the Master’s but, if accepted, the 30 credits awarded from the MicroMasters program will be recognised as credit obtained towards the 180 credits required for the full MSc. Visit the University of Edinburgh Business Analytics Entry Requirements page for more information.

    • Demand for Business/Management Analyst roles in the USA is predicted to grow by 14.3% over the next 10 years, attracting an average annual salary of $81k. (Source: Bureau of Labor Statistics (projected growth) and Burning Glass analysis)
    • Skills such as Python and machine learning are in very high demand in virtually every business sector
    • A deep understanding of predictive analysis has become pivotal to business success
    • Career opportunities include business analyst, data scientist and management consultant

Meet your instructors

from The University of Edinburgh (EdinburghX)
Dr Galina Andreeva
Senior Lecturer in Management Science
The University of Edinburgh
Dr Johannes De Smedt
Dixons Carphone Lecturer in Business Analytics
The University of Edinburgh
Dr Matthias Bogaert
Lecturer in Business Analytics
The University of Edinburgh

Experts from EdinburghX committed to teaching online learning

Program endorsements

The University of Edinburgh has proved itself to be enormously progressive when it comes to offering courses focused on data and technology, including the Data Science Graduate Apprenticeship launched with PwC. As PwC begins to use artificial intelligence as a way to solve problems in society, we would certainly be keen to see candidates with a MicroMasters in Predictive Analytics.

Thomas Pulling, Partner, PwC

Enrolling Now

$1,500
USD
5 courses in 1 year
Pursue the Program

FAQs

  • Certificates are issued by edX under the name of EdinburghX and are delivered online through the edX platform. You will receive an individual certificate for each MicroMasters program course that you pass as a verified learner. Learners who pass all four MicroMasters program courses and the final project on the verified track will receive a MicroMasters program certificate.

  • You must achieve a grade of 50 or higher to pass each course in the program. You can view the University of Edinburgh’s Extended Common Marking Scheme (https://www.ed.ac.uk/student-administration/exams/regulations/common-marking-scheme) for more information (see section CMS4: Postgraduate Assessment Mark).

  • We strongly advise taking the MicroMasters program courses sequentially to build up skills and knowledge in preparation for the final project.

  • Gaining the MicroMasters program certificate is one possible route for entry to the on-campus MSc Business Analytics. Successful completion of the MicroMasters program does not guarantee acceptance to the Master’s but, if accepted, the 30 credits awarded from the MicroMasters program will be recognised as credit obtained towards the 180 required for the full MSc. Visit the University of Edinburgh Business Analytics Entry Requirements (https://www.business-school.ed.ac.uk/msc/business-analytics/entry-requirements) page for more information.

  • This MicroMasters program is intended for those who have undergraduate level or equivalent professional experience/background in mathematics, statistics or similar subject area (linear algebra, calculus etc.) and want to kick-start their career or advance their skills in this field. Previous experience with a procedural programming language is beneficial (Java, C, Python, Visual Basic etc.).

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