• Length:
    6 Weeks
  • Effort:
    8–10 hours per week
  • Price:

    FREE
    Add a Verified Certificate for $150 USD

  • Institution
  • Subject:
  • Level:
    Advanced
  • Language:
    English
  • Video Transcript:
    English

Prerequisites

You should be familiar with an undergraduate level, or have a background, in mathematics and statistics. Previous experience with a procedural programming language is beneficial (e.g. Python, C, Java, Visual Basic).

About this course

The prevalence of data within companies allows business analysts to adopt a range of predictive modelling algorithms, enabling them to analyse aspects of the business such as customer churn and sales forecasting. 
 
This course introduces you to the full lifecycle of building a predictive model, from eliciting the question, to preparing the data, and finally building the first model. All this will be illustrated and put into practice, step by step, using Python. 
 
Interpreting a business case and transforming it into a predictive model can be challenging. It requires an analyst to understand its inner workings and the ways data can offer new insights. Getting a firm grasp on the different types of predictive models available, and what data requirements they have, allows analysts to make confident predictions in the appropriate situations. 
 
You will explore the data discovery process in full detail, discovering how we can make a connection between the predicting and predicted variables that are in the picture. You will also learn about key data transformation and preparation issues, which form the backdrop to an introduction in Python. Through analysis of real-life data, you will develop an approach to implement a simple linear regression model. 
  
This course is the first in the MicroMasters programme and will prepare you for future courses which dive further into the details of modelling both classification and regression problems with statistical and machine learning methods. All of the methods are framed within the context of case studies, giving you the practical skills needed to begin or advance your career as a predictive analyst.

What you'll learn

In this course, you will:
  • Develop an understanding of the predictive analytics process  
  • Learn how to use Python for predictive analytics
  • Learn how to gather data and prepare a dataset for modelling
  • Build predictive models to solve real-world business problems
Week 1: Introduction to Predictive Modelling 
Week 2: Python and Predictive Modelling
Week 3: Variables and the Modelling Process 
Week 4: Transformation and Preparation of Data 
Week 5: Data Quality Problems and Other Anomalies 
Week 6: Regression and Case Study

Meet your instructors

Dr Johannes De Smedt
Dixons Carphone Lecturer in Business Analytics
The University of Edinburgh

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Frequently asked questions

What type of activities will I complete on the course? 
This course foregrounds self-directed and active ways of learning: reading, coding in Python, knowledge check quizzes, and peer discussion. In addition, the course features videos that demonstrate relevant predictive analysis techniques and concepts.  

What software will I be required to use? 
All coding activities on this course will be hosted on Vocareum. You will be able to access this free software directly within the edX platform. There is no requirement to purchase further software in order to complete this course.  

What do I need to complete the course?
For successful completion of this course, you will need access to a computer or mobile device and a reliable internet connection.

Who can take this course?

Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.