Business Intelligence Buyer's Guide

The 8 Best Predictive Analytics Courses & Online Training for 2023

Best Predictive Analytics Courses

Best Predictive Analytics Courses

The editors at Solutions Review have compiled this list of the best predictive analytics courses and online training to consider taking.

SR Finds 106The core focus of predictive modeling is to use explanatory variables from past occurrences and exploit them to predict the previously unknown future. The accuracy and usability of predictive analytics is wholly dependent on how granular the analysis has been run and the type of assumptions that are being made. Forward-thinking organizations will utilize predictive models for a variety of business functions. Some of the most common ways this type of analysis is being used is to detect fraud, optimize marketing campaigns, improve operations, and to manage risk.

With this in mind, we’ve compiled this list of the best predictive analytics courses and online training to consider if you’re looking to grow your data analytics skills for work or play. This is not an exhaustive list, but one that features the best predictive analytics courses and training from trusted online platforms. We made sure to mention and link to related courses on each platform that may be worth exploring as well.

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The Best Predictive Analytics Courses

TITLE: Predictive Analytics for Business Nanodegree

OUR TAKE: In collaboration with Alteryx, this Udacity training comes recommended by Solutions Review. It shows you how predictive analytics and business intelligence can solve real-world problems, and takes 3 months to complete.

Platform: Udacity

Description: Learn to apply predictive analytics and business intelligence to solve real-world business problems. Students who enroll should be familiar with algebra and descriptive statistics and have experience working with data in Excel. Working knowledge of SQL and Tableau is a plus, but not required.

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TITLE: Introduction to Predictive Analytics in Python

OUR TAKE: In this course, you will learn how to build a logistic regression model with meaningful variables. You will also learn how to use this model to make predictions and how to present it and its performance to business stakeholders.

Platform: DataCamp

Description: In this course, you will learn how to build a logistic regression model with meaningful variables. You will also learn how to use this model to make predictions and how to present it and its performance to business stakeholders. The course is instructed by Nele Verbiest, a senior data scientist at Python Predictions. At Python Predictions, she developed several predictive models and recommendation systems in the fields of banking, retail and utilities.

More “Top-Rated” DataCamp paths: Power BI – Data Analytics Essentials with Power BI: Intermediate Predictive Analytics in PythonPredictive Analytics using Networked Data in R

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TITLE: The Essential Elements of Predictive Analytics and Data Mining

OUR TAKE: This course provides that perspective through the lens of a veteran practitioner who has completed dozens of real-world projects. It is one of the most popular on the LinkedIn Learning platform.

Platform: LinkedIn Learning

Description: This course provides that perspective through the lens of a veteran practitioner who has completed dozens of real-world projects. Keith McCormick is an independent data miner and author who specializes in predictive models and segmentation analysis, including classification trees, cluster analysis, and association rules.

More “Top-Rated” LinkedIn Learning paths: Power BI – Data Analytics Essentials with Power BI: Predictive Analytics Essential Training for Executives, Python: Working with Predictive AnalyticsBusiness Analytics Foundations: Predictive, Prescriptive, and Experimental Analytics

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TITLE: Predictive Modeling and Analytics

OUR TAKE: This course offers flexible deadlines for busy professionals, a shareable certificate, and 100 percent online access. It is course 2 in the Advanced Analytics for Business specialization. It takes 11 hours to complete.

Platform: Coursera

Description: This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business.

More “Top-Rated” Coursera paths: Power BI – Data Analytics Essentials with Power BI: Practical Predictive Analytics: Models and Methods, Python Data Products for Predictive Analytics Specialization, Predictive Analytics and Data Mining

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TITLE: Implementing Predictive Analytics with TensorFlow

OUR TAKE: When you are finished with this course, you will have the skills and knowledge of TensorFlow needed to solve data science and machine learning problems. It is top-rated on Pluralsight.

Platform: Pluralsight

Description: In this course, you will learn foundational knowledge of solving real-world data science problems. First, you will explore the basics of implementing supervised learning problems including linear regression and neural networks. Next, you will discover how recommendation systems can be implemented using TensorFlow. Finally, you will learn how to understand and implement reinforcement learning systems.

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TITLE: Introduction to Time Series Analysis and Forecasting in R

OUR TAKE: You will learn how to visualize, clean, and prepare your data. After that, you will learn about statistical methods used for time series. You will hear about autocorrelation, stationarity, and unit root tests.

Platform: Udemy

Description: You will learn about different ways in how you can handle date and time data in R. Things like time zones, leap years or different formats make calculations with dates and time especially tricky for the programmer. You will learn about POSIXt classes in R Base, the chron package, and especially the lubridate package.

More “Top-Rated” Udemy paths: Logistic Regression (Predictive Modeling) workshop using R, Understanding Regression Techniques, Logistic Regression using SAS – Indepth Predictive Modeling, R Programming: Advanced Analytics In R For Data Science

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TITLE: Machine Learning for Predictive Analytics

OUR TAKE: Learn what is possible with the state of machine learning in today’s world, its limits, risks, and rewards, and how to apply this knowledge to benefit your organization. The course contains over 6+ hours of video instruction and quizzes and demos to test and further your understanding of the material.

Platform: Experfy

Description: This course will address this issue and will help you understand what exactly machine learning and predictive analytics are, what are its limits and its potential risks, and why it may benefit your organization. Using real-world case studies and many other examples of current and potential future industry usage, this course will help you better understand why many corporations are adopting or should be adopting machine learning to better enable their future.

More “Top-Rated” Experfy paths: Power BI – Data Analytics Essentials with Power BI: Scaling Advanced Analytics

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NOW READ: The Best Predictive Analytics Certifions Online

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