Introduction to Predictive Analytics using Python (edX)

Introduction to Predictive Analytics using Python (edX)
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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).
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Introduction to Predictive Analytics using Python (edX)
Learn the predictive modelling process in Python. Create the insights needed to compete in business. This course provides you with the skills to build a predictive model from the ground up, using Python. You will learn the full lifecycle of building the model. First, you'll understand the data discovery process and discover how to make connections between the predicting and predicted variables. You will also learn about key data transformation and preparation issues, which form the backdrop to an introduction in Python for data analytics.

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Through the analysis of real-life data, you will also develop an approach to implement simple linear and logistic regression models. These real-life examples include assessments on customer credit card behavior and case studies on sales volume forecasting.

This course is the first in the Predictive Analytics using Python MicroMasters program and will prepare you for modeling classification and regression problems with statistical and machine learning methods.


What you'll learn

In this course you will:

- Understand the predictive analytics process

- Gather and prepare data for predictive modeling

- Clean datasets to prevent data quality issues in your models

- Implement linear and logistic regression models using real-life data


Syllabus


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



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MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Course Auditing
124.00 EUR
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).

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.