5 Best Regression Analysis Courses For Beginners Online in 2024

Best Regression Analysis online courses from top instructors. Learn Regression Analysis from the best certification courses, tutorials and programs.

5 Best Regression Analysis Courses For Beginners Online in 2024
Best Regression Analysis Courses

What is Regression Analysis?

Regressional Analysis is basically the statistical process for estimating the relationships between a dependent variable and one or more independent variables with the purpose of estimating future moves in an investment portfolio's performance.

Regression analysis is used heavily by financial advisors and freelance traders as a way to anticipate what assets might perform well in the future.

Why Regression Analysis is used?

Regression analysis is one of the most useful techniques out there for analyzing data, specifically when it comes down to uncovering relationships between different units of analysis. This process of investigating interactions allows us to correctly identify what matters the most.

Some examples of Regression Analysis include determining which variable is having an effect on a certain topic of interest. The processes the analysts use let you know which factors you can confidently determine matter most, and how they may possibly be impacted by other key factors.

Top Regression Analysis Courses Online List

  1. Statistics for Data Science and Business Analysis

  2. Complete Linear Regression Analysis in Python

  3. Machine Learning for Data Analysis: Regression & Forecasting

  4. Excel Analytics: Linear Regression Analysis in MS Excel

  5. The Data Science Course 2022: Complete Data Science Bootcamp

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Best Regression Analysis Online Training, Tutorials, and Programs

1. Statistics for Data Science and Business Analysis

Statistics you need in the office: Descriptive & Inferential statistics, Hypothesis testing, Regression analysis.

The course includes:

  • Sample Or Population Data
  • The Fundamentals of Descriptive Statistics
  • Business Analytics
  • Measures of Central Tendency, Asymmetry, and Variability
  • Distributions
  • Estimators and Estimates
  • Confidence Intervals: Advanced Topics
  • Hypothesis Testing
  • Practical Example: Hypothesis Testing
  • The Fundamentals of Regression Analysis
  • Subtleties of Regression Analysis
  • Assumptions for Linear Regression Analysis
  • Dealing with Categorical Data

Initially, you will understand the fundamentals of statistics and learn how to work with different types of data. You will learn to plot different types of data and calculate the measures of central tendency, asymmetry, and variability.

Next, you will learn to calculate correlation and covariance. You will also understand distinguishing and working with different types of distributions. This Regression Analysis tutorial will teach you how to estimate confidence intervals and perform hypothesis testing.

Moving on, you will learn how to make data-driven decisions and understand the mechanics of regression analysis. You will also learn how you can carry out regression analysis and understand the concepts needed for data science even with Python and R!

  • Course rating: 4.6 out of 5.0 ( 31,155 Ratings total)
  • Duration: 5 h
  • Certificate: Certificate on completion
  • View Course

2. Complete Linear Regression Analysis in Python

Learn Regression Analysis in Python from scratch.

The course includes:

  • Setting up Python and Jupyter Notebook
  • Basics of Statistics
  • Introduction to Machine Learning
  • Data Preprocessing
  • Linear Regression

With this Regression Analysis course, you will learn how to solve real-life problems using the Linear Regression technique. You will also understand the Preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression.

Next, you will learn how to predict future outcomes basis past data by implementing the Simplest Machine Learning algorithm. The main purpose of this course is to understand how to interpret the result of the Linear Regression model and translate them into actionable insight.

Additionally, you will learn the basics of statistics and concepts of Machine Learning and gain an in-depth knowledge of data collection and data preprocessing for Machine Learning Linear Regression problems.

  • Course rating: 4.2 out of 5.0 ( 1,212 Ratings total)
  • Duration: 7 h 30 m
  • Certificate: Certificate on completion
  • View Course

3. Machine Learning for Data Analysis: Regression & Forecasting

Machine Learning is made simple with Excel! Regression models for advanced data analysis & business intelligence (no code!)

The course includes:

  • Getting Started
  • Intro to Regression
  • Regression Modeling
  • Model Diagnostics
  • Time-Series Forecasting

During this Regression Analysis course, you will learn how to build foundational machine learning & data science skills, without writing complex code. You will learn to use intuitive, user-friendly tools like Microsoft Excel to introduce & demystify machine learning tools & techniques.

Moving on, this analysis course will help you learn how to predict numerical outcomes using regression modeling and time-series forecasting techniques. You will also learn how to calculate diagnostic metrics like R-Squared, Mean Error, F-Significance, and P-Values to diagnose the model quality.

Plus, you will explore unique, hands-on case studies to see how regression analysis can be applied to real-world business intelligence use cases.

  • Course rating: 4.7 out of 5.0 ( 159 Ratings total)
  • Duration: 2 h 30 m
  • Certificate: Certificate on completion
  • View Course

4. Excel Analytics: Linear Regression Analysis in MS Excel

Linear Regression analysis in Excel. Analytics in MS Excel includes regression analysis, Goal seek, and What-if analysis.

In this course, you will learn how to:

  • Identify the business problem which can be solved using the linear regression technique of Machine Learning.
  • Create a linear regression model in Excel and analyze its result.
  • Confidently practice, discuss and understand Machine Learning concepts.

With this Regression Analysis course, you will learn how to solve real-life problems using the Linear Regression technique. You will also understand the Preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression.

Next, you will learn how to predict future outcomes basis past data by implementing the Simplest Machine Learning algorithm. The main purpose of this course is to understand how to interpret the result of the Linear Regression model and translate them into actionable insight.

Additionally, you will learn the basics of statistics and concepts of Machine Learning and gain an in-depth knowledge of data collection and data preprocessing for Machine Learning Linear Regression problems.

  • Course rating: 4.7 out of 5.0 ( 695 Ratings total)
  • Duration: 3 h
  • Certificate: Certificate on completion
  • View Course

5. The Data Science Course 2022: Complete Data Science Bootcamp

Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning.

The course includes:

  • Understanding of the Data Science field
  • Type of Analysis
  • Mathematics
  • Statistics
  • Python
  • Applying advanced statistical techniques in Python
  • Data Visualization
  • Machine Learning
  • Deep Learning

This Regression Analysis program will help you learn how to impress interviewers by showing an understanding of the data science field and learning how to pre-process data. Here, you will understand the mathematics behind Machine Learning which is an absolute necessity.

Next, you will learn to start coding in Python and understand how to use it for statistical analysis. You will comprehend performing linear and logistic regressions in Python and carrying out cluster & factor analysis.

By the end of this Regression Analysis course, you will be able to create Machine Learning algorithms in Python, using NumPy, statsmodels, and sci-kit-learn.

  • Course rating: 4.6 out of 5.0 ( 107,716 Ratings total)
  • Duration: 29 h 30 m
  • Certificate: Certificate on completion
  • View Course

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