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Linear Regression Online Courses

Linear regression is a fundamental and extensively used type of predictive analysis. Learn Linear Regression Programs from the World’s Top Universities.

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Overview of Learning Linear Regression Courses with upGrad

Linear Regression plays a key role in predictive analytics. No matter if you are predicting trends, developing insights into consumer behavior, or informing business decisions, Linear Regression has become a fundamental skill in the data-intensive world in which we live.

upGrad’s Linear Regression programs provide practical experience in creating, interpreting, and assessing regression models under the mentorship of experts from the industry. upGrad’s popular data science courses, including online linear regression courses, are practical; you don’t just learn the theory, but learn how to apply it.

Why Learning Linear Regression is Crucial in 2025

  • Powers key predictive models used in business, healthcare, and finance
  • Forms the foundation of more advanced machine learning techniques
  • Helps professionals make data-driven decisions with confidence
  • In high demand across industries, hiring for Data Analyst and Data Scientist role
  • Enhances your resume and sets you apart in competitive job markets

Who Should Take Linear Regression Online Courses

  • Beginners exploring the field of data science or analytics
  • Students looking to build a strong foundation in statistics and modeling
  • Working professionals aiming to upskill in predictive analytics
  • Career switchers wanting to enter the data-driven tech world
  • Anyone curious about how numbers turn into insights


What Will You Learn in upGrad’s Linear Regression Online Courses?

upGrad offers a broad variety of data science online courses, aiming to provide the skills that are highly sought after in the industry, such as linear regression, one of the fundamental methods in predictive analytics.

If you are pursuing a full degree course or exploring free data science courses, you can be assured that upGrad offers practical training in linear regression during the course. 

Among the highly rated programs that include courses on linear regression are:

Topics You’ll Learn in Linear Regression Courses from upGrad:

upGrad courses cover the following key subjects to help you become proficient in linear regression:

  • The Linear Regression Model: Familiarize yourself with the linear regression equation for modeling the relationship between predictor variables and an outcome variable that is continuous, and learn how to make accurate predictions.
  • Forms of Linear Regression: Investigate forms including Simple Linear Regression and Multiple Linear Regression, which address one or more predictor variables.
  • Steps to construct the linear regression algorithm: Get familiarized with how to construct a linear regression model from the pre-processing of data to the application of the most common procedure to train this model, the least squares method.
  • Assumptions of Linear Regression: Learn what important linear regression assumptions such as linearity, independence, and homoscedasticity are and how to test them with actual data.
  • Interpreting Regression Coefficients: Understanding the meaning and implications of regression coefficients, that is, the nature of the impact that predictors have on the target variable.
  • Least Squares Regression Line (LSRL): Understand the Least Squares Regression Line, which is the basis for linear regression and the focus of the “least squares” process that reduces errors of prediction.
  • Ordinary Least Squares (OLS) Method: Learn to apply the approach of Ordinary Least Squares, which is the most widely used technique for estimating the coefficients of a linear regression model.

Data Science Course Instructors

Learn From The Best

Learn Data Science fundamentals from expert instructors who help you excel in your careers by imparting cutting-edge analytics and machine learning skills.

8

Instructors

10

Industry Experts

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Dr. Atif Waraich

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Faculty - Computer Science

A Senior faculty of Engineering and Technology at LJMU who has multiple publications in the health care domain 

LJMU Profile
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Chandrashekar Ramanathan

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Dean Academics

Prof. Chandrashekar has a PhD from Mississippi State University and experience of over 10 years in several multinational organisations. 

IIITB Profile
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Prof. G. Srinivasaraghavan

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Professor

Prof. Srinivasaraghavan has a PhD in Computer Science from IIT-K and 18 years of experience with Infosys and several other MNCs. 

IIITB Profile
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Tricha Anjali

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Ex-Associate Dean

Prof. Anjali has a PhD from Georgia Institute of Technology as well as an integrated MTech (EE) from IIT Bombay. 

LinkedIn ProfileLinkedin
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Debabrata Das

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Director, IIITB

Dr. Debabrata Das is Director of IIITB. He has received his PhD from IIT-KGP. His main areas of research are IoT and Wireless Access Network 

IIITB Profile
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Prof. Dhiya Al-Jumeily

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Professor - Artificial Intelligence

A senior member of the IEEE and a chartered IT Professional, he is a fellow of the UK Higher Education ACademy 

LJMU Profile
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Prof. Paulo Lisboa

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Head of Dept - Applied Mathematics

Studied mathematical physics at LU and was the chairman of Industrial Mathematics at KMJU in 1996 and Head of Graduate School in 2002 

LJMU Profile
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Dr. Gabriela Czanner

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Faculty - Engineering and Technology

A Senior lecturer at Department of Applied Mathematics at LJMU. Her research focus is advanced statistics for decision support 

LJMU Profile

Data Science Projects

Learn by Doing

Our data science online certification programs have projects to apply theoretical knowledge in practical scenarios, helps you to tackle real-world problems.

16+

Industry projects to choose from

Slide 1 of 17

In this assignment, you will work for a consumer finance company which specialises in lending various types of loans to urban customers and use EDA to analyse the patterns present in the data. This will ensure that the applicants are capable of repaying the loan are not rejected.

Data Visualisation

Data Analysis

Data Interpretation

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Credit EDA Assignment

In this assignment, you will work for a consumer finance company which specialises in lending various types of loans to urban customers and use EDA to… Know More

Skills learned

Data Cleaning

Data Visualisation

Data Analysis

Data Interpretation

MySQL Queries

Data Manipulation

Data Analysis

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RSVP Case Study

In this assignment, you will work on a movies dataset using SQL to extract exciting insights about popular films and the factors that drive a film. 

Skills learned

MySQL

MySQL Queries

Data Manipulation

Data Analysis

ML Modelling

Model Evaluation

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Bike Sharing Assignment

Build a regression model to understand the factors on which the demand for bike sharing systems vary on and help a company optimise its revenue. 

Skills learned

Linear Regression

ML Modelling

Model Evaluation

In this case study, the company requires you to build a machine learning classification model wherein using some demographics and behavioral data of the leads (potential buyers), it will be able to identify the ones most likely to convert.

Decision Trees

Classification

ML Modelling

Model Evaluation

Business Problem Solving

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Lead Scoring Case Study

In this case study, the company requires you to build a machine learning classification model wherein using some demographics and behavioral data of t… Know More

Skills learned

Logistic Regression

Decision Trees

Classification

ML Modelling

Model Evaluation

Business Problem Solving

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them from the perspective of a business analyst.

Tree Models

Model Selection

Feature Engineering

Classification

ML Modelling

Model Evaluation

Business Problem Solving

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Model Selection Case Study - Telecom Churn

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customer… Know More

Skills learned

Logistic Regression

Tree Models

Model Selection

Feature Engineering

Classification

ML Modelling

Model Evaluation

Business Problem Solving

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them from the perspective of a data scientist.

Tree Models

Boosting

Model Selection

Regularization

Feature Engineering

Classification

ML Modelling

Model Evaluation

Business Problem Solving

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Advanced ML Case Study - Telecom Churn

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customer… Know More

Skills learned

Logistic Regression

Tree Models

Boosting

Model Selection

Regularization

Feature Engineering

Classification

ML Modelling

Model Evaluation

Business Problem Solving

Lexical Processing

Regex

POS Tagging

Dependency Parsing

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Syntactic Processing Assignment

Use the techniques such as POS tagging and Dependency parsing to extract information from unstructured text data. 

Skills learned

Natural Language Processing

Lexical Processing

Regex

POS Tagging

Dependency Parsing

Sqoop

Redshift

Spark

ETL Pipeline

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ETL Project

Make use of Sqoop, Redshift & Spark to design an ETL data pipeline. 

Skills learned

AWS

Sqoop

Redshift

Spark

ETL Pipeline

Analyse movie data from the past 100 years and find out various insights to determine what makes a movie do well. Use data manipulation, slicing, and various other dataframe operations to successfully find usable insights from the movies.

Data Processing

Data Visualisation

Data Analysis

Dashboarding

Data Storytelling

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IPL Visualization Assignment

Analyse movie data from the past 100 years and find out various insights to determine what makes a movie do well. Use data manipulation, slicing, and … Know More

Skills learned

Tableau/Power BI

Data Processing

Data Visualisation

Data Analysis

Dashboarding

Data Storytelling

Linear Regression

ML Model Evaluation

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Advanced Regression

Build a regularized regression model to understand the most important variables to predict 

Skills learned

ML Modeling

Linear Regression

ML Model Evaluation

Hadoop

MapReduce Programming

mrjob

Linux

Sqoop

Apache HBase

SQL

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MapReduce Programming Assignment

Perform MapReduce Programming in a big data environment on a large dataset. 

Skills learned

AWS

Hadoop

MapReduce Programming

mrjob

Linux

Sqoop

Apache HBase

SQL

Big Data with Spark

PySpark

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Big Data Case Study

Understand how a big data project in the industry is taken up and solved through a comprehensive big data case study on cloud. 

Skills learned

AWS

Big Data with Spark

PySpark

Python

Data Analysis

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SQL & Python Lab

Solve intensive programming questions in a competitive lab environment to showcase and evaluate your SQL and Python coding skills. 

Skills learned

SQL

Python

Data Analysis

Understand the factors that drive the Airbnb business and help the team leads tackle problems and bottlenecks through extensive data analysis on UI tools.

Data Storytelling techniques

Data Visualisation

Tableau

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Airbnb Case Study

Understand the factors that drive the Airbnb business and help the team leads tackle problems and bottlenecks through extensive data analysis on UI to… Know More

Skills learned

Data Analysis

Data Storytelling techniques

Data Visualisation

Tableau

Spark

Spark Streaming

Apache Kafka

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Retail Project

Build an end-to-end real-time data processing application using Spark Streaming and Kafka. 

Skills learned

AWS

Spark

Spark Streaming

Apache Kafka

Domain understanding

Data Analysis

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Business Case Study

Understand how data projects are taken up in the industry and implement the steps required to successfully manage and complete a data project. 

Skills learned

Business Problem Solving

Domain understanding

Data Analysis

In this assignment, you will build a complete neural network using Numpy. You will implement all the steps required to build a network - feedforward, loss computation, backpropagation, weight updates etc. You will use the MNIST dataset to train your model to classify handwritten digits between 0-9.

Neural Networks

PyTorch

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NN Assignment

In this assignment, you will build a complete neural network using Numpy. You will implement all the steps required to build a network - feedforward, … Know More

Skills learned

Deep Learning

Neural Networks

PyTorch

Career Paths After Completing a Linear Regression Course

After gaining top skills in a Linear Regression Course, you’ll be equipped to explore high-demand roles across the data ecosystem. Completing the Linear Regression course qualifies you for many data and analytics positions. If you are just beginning or ready to take your next step in your career, the career roles given below allow you to engage your talents in meaningful, applied work.

Here are some popular career paths you can apply for:

  • Data Analyst – ₹4 to ₹9 LPA
  • Business Analyst – ₹6 to ₹13 LPA
  • Data Scientist – ₹7 to ₹17 LPA
  • Data Engineer – ₹6 to ₹14 LPA
  • Product Analyst – ₹8 to ₹16 LPA
  • Analytics Consultant – ₹11 to ₹18 LPA
  • Statistician: ₹3 to ₹8 LPA 
  • Quantitative Analyst (Quant): ₹12.5 - 24 LPA

Source: Glassdoor

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Our Placement Numbers

Excel in data-driven careers with our certification in Data Science, boasting a high rate of successful student placements. Get hired by top companies.

57%
Average Salary Hike
₹1.23 Cr
Highest Salary Offered
6000+
Career Transitions
300+
Hiring Partners

Top Recruiters

Tech Mahindra
Amazon
Tata
Wipro
Microsoft
TCS
Infosys
Flipkart
IBM
HDFC Bank
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upGrad's student mentor played a very importany role in my learning journey

upGrad's student mentors played a crucial part in my learning journey. I followed them and they helped a lot in clarifying my queries related to my online data science course. They also gave me placement assistance as a part of my data science course, where they perfectly guide you on how to start a career as a Data Analyst.

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Abhinay Bandaru

Product Analyst, Head Infotech

3 Years of Experience

The upGrad's placement drive helped me to secure a job in MNC

My online data science course's content was so well-structured that it helped me grasp concepts that were entirely new to me. Thanks to upGrad's placement drive, I was able to secure a job at Kantar Analytics.

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Additional benifits of upGrad helped a lot in terms of gaining practical exposure

upGrad's online data science courses are truly amazing. The mentorship through industry veterans, BaseCamps, and student mentors makes the programme extremely engaging. I Would definitely endorse the data science programme for its rich content and comprehensive approach to Data Science.

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Technology Project Manager & Commercial Strategy Associate, Victory Farms

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Being online, it was like a university experience

Learning with upGrad for my data science course was like going back to University for me. Their data science certification, career support and mentorship calls really helped me switch to a career in the field of Data Science.

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News Analyst, Thomson Reuters

6 Years of Experience

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Learner Support and Services

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Industry Mentors

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    Receive one-on-one feedback from our seasoned data science faculty on submissions and personalized feedback to improvement

    Our Data Science Syllabus is designed to provide you with ample of industry relevant knowledge with examples

Why Choose upGrad for Linear Regression Online Courses?

Looking to become a data scientist and want to learn linear regression? upGrad’s linear regression course is part of its complete, industry-aligned online data science courses, which are meant to equip you with the real-world skills you need to get a job. Below are the reasons why upGrad can be a good option even when other data science courses come with different data science course fees and syllabi.

Feature/Criteria

upGrad

Other Institutes

Course Structure

In-depth linear regression course as part of a comprehensive data science course syllabus

Mostly surface-level concepts, often lacking practical applications

University Collaborations

Partnered with top institutions like IIIT Bangalore, LJMU, and O.P. Jindal

Limited or local university tie-ups with lesser-known credibility

Certifications

Globally recognized certificates in data science and machine learning, useful for career advancement

Basic certifications with limited professional recognition

Industry Projects

Real-world projects on least squares regression, model evaluation, and prediction use cases

Fewer practical projects; mostly theory or outdated datasets

Career Support

Personal mentorship, resume building, and placement support, ideal for job-ready skills

Minimal or no structured career support post-completion

Tools & Languages

Hands-on with Python, R, SQL, and libraries like scikit-learn for regression modeling

Often tool-limited; may focus mainly on Excel or manual methods

Faculty Expertise

Taught by a mix of top academicians and real-world data science experts

Mainly academic-focused with limited industry exposure

Learning Format

100% online linear regression online course with flexible, self-paced learning

Fixed timing, less flexible for working professionals

Specialization

Covers regression coefficients, the least squares method, OLS regression, model assumptions, and diagnostics

Limited to theory with no emphasis on real-world regression modeling

Best For

Ideal for beginners, working professionals, and career switchers looking for a full-fledged data science online course

More suited for theory-based learners or classroom-style instruction

Fees

Offers EMI options and value-driven pricing compared to data science course fees elsewhere

Either too expensive or low-cost with compromised quality

Free Learning Options

Access to free data science courses and modules for beginners

Few or no free introductory lessons provided

Frequently Asked Questions

1. What is linear regression?

Linear regression is a statistical method for modeling the relationship between an independent variable and a dependent variable. It's commonly applied in predictive analytics and serves as the foundation for numerous machine learning algorithms.


2. Why is it necessary to study linear regression?

Learning linear regression allows you to work with trends, forecasts, and create building blocks for a more advanced data science and machine learning career. It's one of the key things you learn in any linear regression course or data science online course.


3. What is the potential for career opportunities when you learn linear regression?

Taking a linear regression course can open the doors for work like Data Analyst, Machine Learning Engineer, Business Analyst, and Research Scientist, particularly in data-driven industries.


4. How will I be able to learn linear regression from taking online classes?

Online linear regression courses offer convenience and interactive learning with project-based hands-on work so that you can implement regression models on actual data sets without the requirement for a classroom environment.


5. What are the advantages of enrolling in an online Linear Regression course?

You receive organized content, instructor-guided courses, lifetime access to content, and instant feedback, all adjusted according to your pace. Most data science courses online feature linear regression as a major module.


6. What are the best linear regression courses for employee training and upskilling?

Courses provided by upGrad, which are part of complete data science courses, are best suited for team upskilling. They provide real-world implementation, flexible modes, and certification from well-known universities.


7. Are linear regression courses offers financial aid?

Yes, upGrad frequently offers financial assistance, EMI options, and scholarships to make it simpler to pursue quality linear regression training.


8. Do I get access to recorded lectures and course content?

Of course! Most online linear regression courses include lifetime video lecture access, downloadable content, and supporting reading materials.


9. What is the refund policy of these courses?

Refund policies differ across platforms.upGrad offers a clear refund policy, which is communicated at the time of enrollment for each data science or linear regression course.


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  1. The above statistics depend on various factors and individual results may vary. Past performance is no guarantee of future results.

  2. The student assumes full responsibility for all expenses associated with visas, travel, & related costs. upGrad does not .