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    4.89

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    4.94

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    4.7

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    4.7

University & Pro Programs

img icon UNIVERSITY
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Northwestern University

18 months  • Online

Live Sessions
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Master Data Science & Machine Learning in Python
136 coding exercises 6 projects
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Hands-On Data Science Using Python
1 coding exercise 1 project

Free Data Science Courses

img icon BASICS
Introduction to Data Science
star   4.5 71.2K+ learners 1 hr

Skills: Fundamentals of DataScience, Basics of Data Preprocessing techniques, Statistical Distributions,A/B Testing, Time series analysis, Fundamentals of Big Data, Database, Tables, Relationships,Relational Database Management System, Non- relational Databases

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Data Science Foundations
star   4.45 657.3K+ learners 2 hrs

Skills: Collection & preprocessing, Statistical analysis, Probability, Data acquisition, Supervised & unsupervised learning, Feature engineering, Model evaluation, Classification, Prediction, Clustering, R & Python analysis, Data visualization, Ethics & privacy

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Python for Data Science
star   4.43 119K+ learners 2 hrs

Skills: Data Analytics, Problem-solving, Insights, Predictive Modeling, Business Intelligence, Data Science Process, Data Preprocessing Techniques,Data Science Components ,Career Trajectory, Programming Basics,Data Handling using Python,Numpy and Pandas

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R for Data Science
star   4.54 14.9K+ learners 2 hrs

Skills: Basics of R, Data structures in R, Data Manipulation in R, Data Visualisation in R

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Excel for Data Science for Beginners
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star   4.49 20.2K+ learners 1.5 hrs

Skills: Date and Time,Aggregation,Lookups,Pivot Tables,Errors in Excel

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Data Preprocessing
star   4.54 10K+ learners 2 hrs

Skills: Data Preparation,Feature Engineering,Variable Scaling,Variable Transformation,Binning the Data,Lambda Function,Correlation Checks for Bivariate Data,Outlier Treatment,Outlier Identification,Data Manipulation,Encoding Categorical Variables

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SQL for Data Science
star   4.51 177K+ learners 3 hrs

Skills: Data Analysis, SQL, SQLite, Power BI, SQL With Python, SQL Clauses, GROUP BY Statement, HAVING Clause, Aliases In SQL, Joins in SQL, Subqueries, Python Concepts With SQL

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Data Science Mathematics
star   4.34 15.6K+ learners 1 hr

Skills: Mathematics for Data Science, Case studies

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Data Visualization With Power BI
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star   4.52 365.3K+ learners 1.5 hrs

Skills: Power BI usage, data loading, creating reports, dashboards, slicers & filters, visual interactivity

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Data Visualization using Tableau
star   4.52 115.3K+ learners 2 hrs

Skills: Business Intelligence Fundamentals, Data Visualization Principles, Introduction to Tableau, Understanding Data Types, Navigating the Tableau Interface, Creating Dashboards, Visual Analytics Techniques, Hands-on Tableau Exercises, Integrating Data Sources.

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Exploratory Data Analysis Essentials
star   4.51 102.9K+ learners 1.5 hrs

Skills: Exploratory data analysis, summary statistics, data cleaning, visualization (histograms, boxplots, scatter), handling missing values

img icon BASICS
Financial Risk Analytics
star   4.55 90.4K+ learners 2 hrs

Skills: Credit & market risk analysis, counterparty risk management, regulatory capital, derivative valuation, XVA, risk identification, hedging strategies, and quantitative model validation

img icon BASICS
Introduction to Data Science
star   4.5 71.2K+ learners 1 hr

Skills: Fundamentals of DataScience, Basics of Data Preprocessing techniques, Statistical Distributions,A/B Testing, Time series analysis, Fundamentals of Big Data, Database, Tables, Relationships,Relational Database Management System, Non- relational Databases

img icon BASICS
Data Science Foundations
star   4.45 657.3K+ learners 2 hrs

Skills: Collection & preprocessing, Statistical analysis, Probability, Data acquisition, Supervised & unsupervised learning, Feature engineering, Model evaluation, Classification, Prediction, Clustering, R & Python analysis, Data visualization, Ethics & privacy

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Python for Data Science
star   4.43 119K+ learners 2 hrs

Skills: Data Analytics, Problem-solving, Insights, Predictive Modeling, Business Intelligence, Data Science Process, Data Preprocessing Techniques,Data Science Components ,Career Trajectory, Programming Basics,Data Handling using Python,Numpy and Pandas

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R for Data Science
star   4.54 14.9K+ learners 2 hrs

Skills: Basics of R, Data structures in R, Data Manipulation in R, Data Visualisation in R

img icon BASICS
Excel for Data Science for Beginners
star   4.49 20.2K+ learners 1.5 hrs

Skills: Date and Time,Aggregation,Lookups,Pivot Tables,Errors in Excel

img icon BASICS
Data Preprocessing
star   4.54 10K+ learners 2 hrs

Skills: Data Preparation,Feature Engineering,Variable Scaling,Variable Transformation,Binning the Data,Lambda Function,Correlation Checks for Bivariate Data,Outlier Treatment,Outlier Identification,Data Manipulation,Encoding Categorical Variables

img icon BASICS
SQL for Data Science
star   4.51 177K+ learners 3 hrs

Skills: Data Analysis, SQL, SQLite, Power BI, SQL With Python, SQL Clauses, GROUP BY Statement, HAVING Clause, Aliases In SQL, Joins in SQL, Subqueries, Python Concepts With SQL

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Data Science Mathematics
star   4.34 15.6K+ learners 1 hr

Skills: Mathematics for Data Science, Case studies

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Data Visualization With Power BI
star   4.52 365.3K+ learners 1.5 hrs

Skills: Power BI usage, data loading, creating reports, dashboards, slicers & filters, visual interactivity

img icon BASICS
Data Visualization using Tableau
star   4.52 115.3K+ learners 2 hrs

Skills: Business Intelligence Fundamentals, Data Visualization Principles, Introduction to Tableau, Understanding Data Types, Navigating the Tableau Interface, Creating Dashboards, Visual Analytics Techniques, Hands-on Tableau Exercises, Integrating Data Sources.

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Exploratory Data Analysis Essentials
star   4.51 102.9K+ learners 1.5 hrs

Skills: Exploratory data analysis, summary statistics, data cleaning, visualization (histograms, boxplots, scatter), handling missing values

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Financial Risk Analytics
star   4.55 90.4K+ learners 2 hrs

Skills: Credit & market risk analysis, counterparty risk management, regulatory capital, derivative valuation, XVA, risk identification, hedging strategies, and quantitative model validation

Learn Data Science For Free

These free data science courses online provide a complete learning path, covering everything from the basics to advanced topics. Whether you're a beginner learning core concepts like Python, R, data preprocessing, statistics, and SQL, or you want to expand your skills with machine learning, AI, and data visualization tools like Power BI and Tableau. These courses cover key skills including data cleaning, statistical analysis, predictive modeling, and data-driven decision-making. 

Starting with foundational concepts, you'll learn to handle and process data using tools like Python, R, and SQL, and perform statistical analysis and data visualization. As you progress, you'll gain hands-on experience with advanced topics like predictive modeling, feature engineering, and time series analysis. These free data science courses online help you build the expertise needed for roles in data science, analytics, and machine learning, preparing you for real-world challenges.

Skills You’ll Gain in These Best Free Data Science Courses 

  • Programming & Tools: Python (Numpy, Pandas), SQL, R, Tableau, Power BI.

  • Mathematics & Statistics: Statistical analysis, Probability, Descriptive/Inferential Statistics.

  • Data Analysis & Visualization: Techniques for data cleaning, EDA (Exploratory Data Analysis), and tools like Tableau or Matplotlib.

  • Cloud Computing: Familiarity with platforms like AWS, Azure, or Google Cloud for managing large datasets.

  • Machine Learning: Supervised/Unsupervised learning, Algorithms, Prediction.

  • Data Handling: Data cleaning, Preprocessing, Visualization, Feature Engineering
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Get started with these courses

img icon BASICS
Predict Footballer Transfer Market Value using Data Science
star   4.64 785 learners 0.5 hr

Skills: Python,EDA

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Predicting FIFA winner using Data Analytics
star   4.38 968 learners 1 hr

Skills: Python,Tableau,EDA

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Applications of Data Science & Machine Learning
star   4.65 1.2K+ learners 1 hr

Skills: Statistical analysis, Deep Learning, how to work and process large and unstructured data sets, and Data Visualization and among others.

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Python for Machine Learning and Data Science
star   4.65 10K+ learners 3 hrs

Skills: Introduction to NumPy, Pandas and Data Visualization in Python

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Applying Analytics to Business Problems
star   4.72 2.8K+ learners 2 hrs

Skills: Analytics in Business Problems, Case Study on Play store Ad Revenue

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Foundations of Data Visualization using Tableau
star   4.52 6.1K+ learners 2 hrs

Skills: Visual Analytics Basics, Importing Data into Tableau, Bar Chart, Line Chart, Histogram

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Intro to Exploratory Data Analysis with Excel
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star   4.59 16.3K+ learners 1.5 hrs

Skills: EDA Basics ,Data Analysis ,Data Cleaning,Data Manipulation,Univariate Analysis

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Excel for Data Science for Beginners
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star   4.49 20.2K+ learners 1.5 hrs

Skills: Date and Time,Aggregation,Lookups,Pivot Tables,Errors in Excel

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Data Analytics using Excel
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star   4.68 56.2K+ learners 1.5 hrs

Skills: Data Analytics Introduction, Phases of Data Analytics, Data Cleaning, Excel Functions, Sorting and Filtering, Lookup Functions, Conditional Formatting, Data Validation, Pivot Tables, Data Visualization with Excel

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Apriori Algorithm
star   4.67 1.6K+ learners 2 hrs

Skills: Conjoint Analysis,Market Basket Analysis,Apriori Algorithm

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LDA in Entertainment Industry
star   4.64 1K+ learners 1 hr

Skills: Application of LDA, Building Pipelines, Data Balancing, Data Validation

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Marketing and Retail Analytics
star   4.62 37.9K+ learners 3 hrs

Skills: RFM Analysis, KINME

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k-fold Cross Validation
star   4.61 1.8K+ learners 1 hr

Skills: Introduction to Cross Validation, Process of Cross Validation, Types of Cross Validation

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Forecasting Hospital Blood Requirements
star   4.61 2K+ learners 2 hrs

Skills: Forecasting Hospital Blood Requirements

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Data Science in FMCG
star   4.6 4.9K+ learners 1 hr

Skills: Data Science in FMCG, Modelling, Probability Distribution, Optimization of Modelling

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Linear Programming for Data Science
star   4.59 12.1K+ learners 3 hrs

Skills: Linear Programming

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Data Science Foundations
star   4.45 657.3K+ learners 2 hrs

Skills: Collection & preprocessing, Statistical analysis, Probability, Data acquisition, Supervised & unsupervised learning, Feature engineering, Model evaluation, Classification, Prediction, Clustering, R & Python analysis, Data visualization, Ethics & privacy

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Data Visualization With Power BI
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star   4.52 365.3K+ learners 1.5 hrs

Skills: Power BI usage, data loading, creating reports, dashboards, slicers & filters, visual interactivity

img icon BASICS
SQL for Data Science
star   4.51 177K+ learners 3 hrs

Skills: Data Analysis, SQL, SQLite, Power BI, SQL With Python, SQL Clauses, GROUP BY Statement, HAVING Clause, Aliases In SQL, Joins in SQL, Subqueries, Python Concepts With SQL

img icon BASICS
Python for Data Science
star   4.43 119K+ learners 2 hrs

Skills: Data Analytics, Problem-solving, Insights, Predictive Modeling, Business Intelligence, Data Science Process, Data Preprocessing Techniques,Data Science Components ,Career Trajectory, Programming Basics,Data Handling using Python,Numpy and Pandas

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Data Visualization using Tableau
star   4.52 115.3K+ learners 2 hrs

Skills: Business Intelligence Fundamentals, Data Visualization Principles, Introduction to Tableau, Understanding Data Types, Navigating the Tableau Interface, Creating Dashboards, Visual Analytics Techniques, Hands-on Tableau Exercises, Integrating Data Sources.

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Exploratory Data Analysis Essentials
star   4.51 102.9K+ learners 1.5 hrs

Skills: Exploratory data analysis, summary statistics, data cleaning, visualization (histograms, boxplots, scatter), handling missing values

img icon BASICS
Financial Risk Analytics
star   4.55 90.4K+ learners 2 hrs

Skills: Credit & market risk analysis, counterparty risk management, regulatory capital, derivative valuation, XVA, risk identification, hedging strategies, and quantitative model validation

img icon BASICS
Introduction to Analytics
star   4.51 88.5K+ learners 2 hrs

Skills: Spectrum of Analytics, Descriptive Analytics

New

img icon BASICS
Predict Footballer Transfer Market Value using Data Science
star   4.64 785 learners 0.5 hr

Skills: Python,EDA

img icon BASICS
Predicting FIFA winner using Data Analytics
star   4.38 968 learners 1 hr

Skills: Python,Tableau,EDA

img icon BASICS
Applications of Data Science & Machine Learning
star   4.65 1.2K+ learners 1 hr

Skills: Statistical analysis, Deep Learning, how to work and process large and unstructured data sets, and Data Visualization and among others.

img icon BASICS
Python for Machine Learning and Data Science
star   4.65 10K+ learners 3 hrs

Skills: Introduction to NumPy, Pandas and Data Visualization in Python

img icon BASICS
Applying Analytics to Business Problems
star   4.72 2.8K+ learners 2 hrs

Skills: Analytics in Business Problems, Case Study on Play store Ad Revenue

img icon BASICS
Foundations of Data Visualization using Tableau
star   4.52 6.1K+ learners 2 hrs

Skills: Visual Analytics Basics, Importing Data into Tableau, Bar Chart, Line Chart, Histogram

img icon BASICS
Intro to Exploratory Data Analysis with Excel
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star   4.59 16.3K+ learners 1.5 hrs

Skills: EDA Basics ,Data Analysis ,Data Cleaning,Data Manipulation,Univariate Analysis

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Excel for Data Science for Beginners
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star   4.49 20.2K+ learners 1.5 hrs

Skills: Date and Time,Aggregation,Lookups,Pivot Tables,Errors in Excel

Trending

img icon BASICS
Data Analytics using Excel
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star   4.68 56.2K+ learners 1.5 hrs

Skills: Data Analytics Introduction, Phases of Data Analytics, Data Cleaning, Excel Functions, Sorting and Filtering, Lookup Functions, Conditional Formatting, Data Validation, Pivot Tables, Data Visualization with Excel

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Apriori Algorithm
star   4.67 1.6K+ learners 2 hrs

Skills: Conjoint Analysis,Market Basket Analysis,Apriori Algorithm

img icon BASICS
LDA in Entertainment Industry
star   4.64 1K+ learners 1 hr

Skills: Application of LDA, Building Pipelines, Data Balancing, Data Validation

img icon BASICS
Marketing and Retail Analytics
star   4.62 37.9K+ learners 3 hrs

Skills: RFM Analysis, KINME

img icon BASICS
k-fold Cross Validation
star   4.61 1.8K+ learners 1 hr

Skills: Introduction to Cross Validation, Process of Cross Validation, Types of Cross Validation

img icon BASICS
Forecasting Hospital Blood Requirements
star   4.61 2K+ learners 2 hrs

Skills: Forecasting Hospital Blood Requirements

img icon BASICS
Data Science in FMCG
star   4.6 4.9K+ learners 1 hr

Skills: Data Science in FMCG, Modelling, Probability Distribution, Optimization of Modelling

img icon BASICS
Linear Programming for Data Science
star   4.59 12.1K+ learners 3 hrs

Skills: Linear Programming

Popular

img icon BASICS
Data Science Foundations
star   4.45 657.3K+ learners 2 hrs

Skills: Collection & preprocessing, Statistical analysis, Probability, Data acquisition, Supervised & unsupervised learning, Feature engineering, Model evaluation, Classification, Prediction, Clustering, R & Python analysis, Data visualization, Ethics & privacy

img icon BASICS
Data Visualization With Power BI
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star   4.52 365.3K+ learners 1.5 hrs

Skills: Power BI usage, data loading, creating reports, dashboards, slicers & filters, visual interactivity

img icon BASICS
SQL for Data Science
star   4.51 177K+ learners 3 hrs

Skills: Data Analysis, SQL, SQLite, Power BI, SQL With Python, SQL Clauses, GROUP BY Statement, HAVING Clause, Aliases In SQL, Joins in SQL, Subqueries, Python Concepts With SQL

img icon BASICS
Python for Data Science
star   4.43 119K+ learners 2 hrs

Skills: Data Analytics, Problem-solving, Insights, Predictive Modeling, Business Intelligence, Data Science Process, Data Preprocessing Techniques,Data Science Components ,Career Trajectory, Programming Basics,Data Handling using Python,Numpy and Pandas

img icon BASICS
Data Visualization using Tableau
star   4.52 115.3K+ learners 2 hrs

Skills: Business Intelligence Fundamentals, Data Visualization Principles, Introduction to Tableau, Understanding Data Types, Navigating the Tableau Interface, Creating Dashboards, Visual Analytics Techniques, Hands-on Tableau Exercises, Integrating Data Sources.

img icon BASICS
Exploratory Data Analysis Essentials
star   4.51 102.9K+ learners 1.5 hrs

Skills: Exploratory data analysis, summary statistics, data cleaning, visualization (histograms, boxplots, scatter), handling missing values

img icon BASICS
Financial Risk Analytics
star   4.55 90.4K+ learners 2 hrs

Skills: Credit & market risk analysis, counterparty risk management, regulatory capital, derivative valuation, XVA, risk identification, hedging strategies, and quantitative model validation

img icon BASICS
Introduction to Analytics
star   4.51 88.5K+ learners 2 hrs

Skills: Spectrum of Analytics, Descriptive Analytics

Our learners also choose

Learner reviews of the Free Data Science Courses

Our learners share their experiences of our courses

4.5
69%
22%
6%
1%
2%
Reviewer Profile

5.0

Country Flag India
“Comprehensive and Engaging Data Science Learning Experience!”
Great Learning's Data Science course exceeded my expectations! The curriculum was well-structured, with insightful lectures, hands-on projects, and real-world applications. The instructors explained complex concepts in an easy-to-understand manner, making learning engaging and effective. I highly recommend this course to anyone looking to build a strong foundation in Data Science!

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Reviewer Profile

5.0

Country Flag India
“Completed Intro to Data Science: Skills and Analysis!”
I enjoyed the Introduction to Data Science course for its hands-on approach and practical applications. The course covered essential topics like data cleaning, visualization techniques using Python libraries such as Matplotlib and Seaborn, and statistical analysis.

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Reviewer Profile

5.0

Country Flag Philippines
“Perfect Course for Data Science Novices!”
This course provides a fantastic introduction to data science. It covers key concepts, tools, and methodologies, making it ideal for beginners eager to dive into the data-driven world.

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Reviewer Profile

4.0

“Data Science Beginner Course Introduction”
I really enjoyed my data science course! The blend of statistics, programming, and analytical thinking was fascinating. I loved learning how to extract insights from data and apply various machine learning techniques. The hands-on projects allowed me to work with real datasets, which made the concepts come alive. I also appreciated the collaborative environment, where sharing ideas with classmates enhanced my understanding. Overall, the course sparked my passion for data science and motivated me to explore it further.

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Reviewer Profile

5.0

Country Flag United States
“A Great Introduction to Data Science”
This was very easy to enroll in and watch. The course covered many topics about data science and the different fields that come together. For someone who is not sure about this career, I highly recommend this course. I felt like I was in a University lecture hall and I learned a great deal of information. I'm ready to continue!

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Reviewer Profile

5.0

“Introduction to Data Science is an Engaging Course that Explores Key Concepts like Data Analysis, Visualization, and Predictive Modeling.”
I enjoyed the clarity of concepts and the practical examples that made understanding easier. The step-by-step approach to data analysis and the integration of real-world applications were particularly engaging.

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Reviewer Profile

5.0

Country Flag India
“The Curriculum is Comprehensive and Covers Key Concepts Thoroughly.”
The Introduction to Data Science course by Great Learning provides an excellent foundation for beginners looking to explore the field of data science. The course content is well-structured, starting with an overview of data science concepts and their applications across industries. The emphasis on understanding the data lifecycle—data collection, cleaning, analysis, visualization, and interpretation—is particularly valuable for building a solid base.

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Reviewer Profile

5.0

Country Flag Morocco
“Exploring Data Science: Key Takeaways from My Learning Experience”
The course provided a comprehensive overview of key topics such as data analysis, statistical methods, and data visualization, helping me understand how data science can be applied to solve real-world problems. I particularly appreciated how the course emphasized the importance of data-driven decision-making and the various tools available for analyzing and interpreting data. The real-world examples and case studies gave me practical insights into how data science is used across different industries.

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Reviewer Profile

5.0

“Course: Introduction to Data Science”
The easiest to follow course, attractive and well-organized.

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Reviewer Profile

5.0

Country Flag Nigeria
“It Was Straight to the Point and Easily Understood”
Keep up the good work. I loved everything about the course and I learned so much.

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Meet your faculty

Meet industry experts who will teach you relevant skills in artificial intelligence

instructor img

Dr. Abhinanda Sarkar

Senior Faculty & Director Academics, Great Learning
  • 30+ years of experience in data science, ML, and analytics.
  • Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.
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Dr. Bappaditya Mukhopadyay

Professor, Analytics & Finance
With an MA in Economics from Delhi School of Economics and PHD from ISI, Dr. Mukhopadhyay is currently the professor and chairperson of the PGPBA program at Great Lakes Institute of Management. He is also the visiting professor of the University of Ulm, Germany, and distinguished Professorial Associate, Decision Sciences and Modelling Program, Victoria University, Australia. His areas of interest and expertise include applied economic theory, game theory, analytics, statistics, econometrics, derivatives and financial risk management, survey design, execution, and others.   Noteworthy achievements: Ranked 4th Amongst the "20 Most Prominent Analytics & Data Science Academicians In India: 2018". Prominent Credentials: He has various research papers published in national as well as international journals. He is currently working on a book titled Measuring and Managing Credit Risk. He has been the Managing Editor at Journal of Emerging Market Finance and Journal of Infrastructure and Development, member of Index Committee, member of Research Advisory Committee, Research Advisory Committee, NICR, Expert member in Faculty Selection committees at various Business schools, among others. Research Interest: Information economics and contract theory, financial risk management, credit risk and agency theory, microfinance institutions, financial Inclusion, analytics in public policy. Teaching Experience: He has more than 20 years of teaching experience in economics, finance.
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Mr. Bharani Akella

Data Scientist
Bharani has been working in the field of data science for the last 2 years. He has expertise in languages such as Python, R and Java. He also has expertise in the field of deep learning and has worked with deep learning frameworks such as Keras and TensorFlow. He has been in the technical content side from last 2 years and has taught numerous classes with respect to data science.
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Denver Dias

Senior Data Science Consultant
  • Holds 8+ yrs exp. & delivered AI solutions for Fortune 500 firms
  • Expert in A/B testing, ML models, and predictive analytics
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Dr. D Narayana

Senior Faculty, Academics, Great Learning
  • 18+ years in AI, ML, and financial engineering solutions
  • PhD in Mathematics from Pierre and Marie Curie University, France
instructor img

Mr. Vishal Padghan

Vishal has 3+ years of experience in the field of Data Science, Digital Marketing and Cloud Computing. He has expertise in Cloud platforms Like AWS, Azure and has exposure to Paid Marketing, Organic Marketing and Content. He has been in the Digital space from the last 3 years and also, he has been involved in teaching numerous classes for Digital Marketing and Cloud Computing
instructor img

Mr. Vishal Padghan

Vishal has 3+ years of experience in the field of Data Science, Digital Marketing and Cloud Computing. He has expertise in Cloud platforms Like AWS, Azure and has exposure to Paid Marketing, Organic Marketing and Content. He has been in the Digital space from the last 3 years and also, he has been involved in teaching numerous classes for Digital Marketing and Cloud Computing
instructor img

Mr. Rounak Dholakia

Academic Operations Head (PGP DSBA)
He currently heads the academic operations for PGP DSBA. Mr Rounak is a seasoned analytics practitioner with 10+ years of experience in providing analytical solutions to Fortune 500 clients across different industry vertical – banking, retail, CPG and pharmacy retail.
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Dr. P K Viswanathan

Professor, Analytics & Operations
Dr. P K Viswanathan, currently serves as a professor of analytics at Great Lakes Institute of Management. He teaches subjects such as business statistics, operations research, business analytics, predictive analytics, ML analytics, spreadsheet modeling and others. In the industrial tenure spanning over 15 years, he has held senior management positions in Ballarpur Industries (BILT) of the Thapar Group and the JK Industries of the JK Organisation. Apart from executing corporate consultancy assignments, Dr. PK Viswanathan has also designed and conducted training programs for many leading organizations in India. He has degrees in MSc (Madras), MBA (FMS, Delhi), MS (Manitoba, Canada), PHD (Madras).   Noteworthy achievements: Ranked 12th in the "20 Most Prominent Analytics & Data Science Academicians In India: 2018". Current Academic Position: Professor of Analytics, Great Lakes Institute of Management. Prominent Credentials: He has authored a total of four books, three of which are on Business Statistics and one on Marketing Research published by the British Open University Business School, UK. Research Interest: Analytics, ML, AI. Patents: He has original research publications exclusively on analytics where he has developed modeling and demonstrated their decision support capabilities. These are: Modelling Credit Default in Microfinance — An Indian Case Study, PK Viswanathan, SK Shanthi, Modelling Asset Allocation and Liability Composition for Indian Banks. Teaching Experience: He has been teaching analytics for more than two decades but has been into active and intense teaching since analytics started witnessing a meteoric growth with the advent of R and Python. Ph.D. in the application of Operations Research from Madras University.
instructor img

Mr. Gaelim Holland

Senior Data Scientist
Gaelim is a Senior Data Scientist with more than a decade of experience in Data Science, Artificial Intelligence, and Machine Learning. He is an expert in Programming languages like R Programming, Python, Java, SQL, JavaScript, and many more. He also is well versed with popular Data Science tools like Microsoft Power BI, Tableau, etc., and has been involved in sharing his Data Science knowledge with aspiring learners.
instructor img

Prof. Raghavshyam Ramamurthy

Industry Expert in Visualization
Raghavshyam (Shaam) Ramamurthy is a data visualization consultant with 15 years of experience across the globe. He worked in the US for 10 years across a variety of industries like manufacturing, chemical processing, and utilities. He consults on Visual analytics, KPI management, Dashboard development and Product development. He has a strong passion for teaching and visits IIT-Madras, IIM-Trichy, IIM-Ranchi, Great Lakes Institute of Management and SP Jain School of Global Management.
instructor img

Dr. Abhinanda Sarkar

Senior Faculty & Director Academics, Great Learning
  • 30+ years of experience in data science, ML, and analytics.
  • Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.
instructor img

Mr. Viplove Raj Sharma

Associate Director
Viplove Raj Sharma is Associate Director at Great Learning 11+ years of experience in analytics and data science, Consulting senior management and leadership across geographies, industries & functions. Earlier at Royal Melbourne Institute of Technology, Melbourne and Mu Sigma, Bangalore Leading Great Learning’s international delivery of programs across data vertical.
instructor img

Dr. R.L. Shankar

Professor, Finance & Analytics
Dr. R.L. Shankar is a professor of finance and analytics with over ten years of experience teaching MBA students, Ph.D. scholars and working executives. He has BTech from IIT Madras, MS in computational finance from Carnegie Mellon University, US, Ph.D. in Finance, EDHEC (Singapore), and has trained over 2,000 executives from prestigious firms. With multiple research papers published under his name, he recently received a research grant from NYU Stern School of Business and NSE for original research on Low latency trading and co-movement of asset prices.   Noteworthy achievements: Ranked 15th in the "20 Most Prominent Analytics & Data Science Academicians In India: 2018". Rated among the" Top 40 under 40" infuential teachers by the New Indian Express. Current Academic Position: Professor of Finance and Analytics, Great Lakes Institute of Management. Prominent Credentials: He has been a visiting professor at IIM Kozhikode, IIM Trichy, and IIM Ranchi. He is also a TEDx speaker. Research Interest: Algorithmic trading, market microstructure, imperfections in derivatives markets and non-parametric risk measurement techniques. Teaching Experience: More than 15 years. Ph.D. in Finance from EDHEC (Singapore).
instructor img

Dr. Bradford Tuckfield

Co-Founder & Director, Wilson Consulting
  • 10+ years of expertise in statistics, programming, and machine learning.
  • PhD. from the Wharton School, University of Pennsylvania

Frequently Asked Questions

What will I learn in these free data science courses?

These free data science courses cover essential skills in data analysis, machine learning, AI, data visualization, and more. You'll learn how to:


  • Preprocess and clean data using Python, R, and SQL
  • Apply statistical methods like hypothesis testing and probability theory
  • Build machine learning models for classification, regression, and clustering
  • Use data visualization tools like Tableau, Power BI, and Matplotlib
  • Work with databases and write SQL queries for data analysis.
These skills will help you analyze complex datasets, build predictive models, and visualize your findings.

What are the prerequisites required to learn these free Data Science courses?

There's no prior experience necessary to begin, but before you learn advanced courses, complete basic courses to have strong computer skills and develop an interest in gathering, interpreting, and presenting data.

What modules are covered in these free data science courses?

These online free data science courses include a wide range of modules to give you a comprehensive understanding of data science:


  • Introduction to Data Science: Basics of data preprocessing, statistical distributions, A/B testing, and time series analysis.

  • Data Science Foundations: Data collection, preprocessing, probability, supervised & unsupervised learning, and model evaluation.

  • Python for Data Science: Data analytics, problem-solving, business intelligence, and predictive modeling using Python libraries like Numpy and Pandas.

  • SQL for Data Science: Learning SQL for data analysis, including joins, subqueries, and integration with Python.

  • Data Visualization: Creating interactive dashboards and visualizing data with Power BI, Tableau, and Python.

  • Machine Learning: Building and evaluating models for classification, prediction, and clustering using Python and R.

These modules ensure you gain the practical knowledge needed for data-driven decision-making.



What skills will I gain from these courses?

By completing these top free data science courses, you will gain a variety of valuable skills:

  • Data Preprocessing: Handling and cleaning data using Python, R, and SQL.

  • Statistical Analysis: Applying statistical methods such as hypothesis testing, regression analysis, and probability theory.

  • Machine Learning: Building and evaluating models for both supervised and unsupervised learning.

  • Data Visualization: Creating effective charts, graphs, and dashboards with tools like Power BI and Tableau.

  • SQL: Writing and optimizing SQL queries for data retrieval and analysis.

  • Data Storytelling: Presenting data insights clearly using visualizations and reports.

These skills are essential for tackling real-world data challenges in fields like business intelligence, analytics, and machine learning.



Will I have lifetime access to these free Data Science courses with certificates?

Yes. You will have lifetime access to these courses after enrolling in them and access to certificates after completing the course.  

What kind of projects will I work on?

You will work on practical, real-world data analysis projects such as:

  • Customer Segmentation: Use clustering techniques such as K-Means and DBSCAN to segment customer data.

  • Financial Risk Analysis: Analyze credit, market, and counterparty risks, and manage counterparty risk.

  • Time Series Forecasting: Work with time-series data to predict trends, including stock market movements.

  • Data Visualization: Create interactive reports and dashboards using Power BI and Tableau.

  • Predictive Modeling: Build models to predict outcomes such as credit card fraud detection and customer churn.

These projects will allow you to apply your learning to real business problems and build a solid portfolio.



How can these courses help me become a data scientist?

These free data science courses for beginners will help you build a strong foundation. You'll learn how to analyze data, build predictive models, and visualize data insights using tools like Python, R, and SQL. The courses also cover advanced techniques such as machine learning, time series forecasting, and data visualization, which are crucial for a career in data science.

Will I get a certificate after completing these free Data Science courses?

All courses are free, A certificate is available for a nominal fee upon successful completion of the course



How much do these free Data Science courses cost?

How much do these free Data Science courses cost?  

What tools and technologies will I learn in these data science courses?

You will learn a variety of tools and technologies that are essential in data science:

  • Python: Learn data manipulation with libraries like Pandas and Numpy, and perform machine learning with Scikit Learn.

  • R: Learn data manipulation, visualization, and statistical analysis using R.

  • SQL: Master SQL for querying and analyzing data from relational databases.

  • Power BI & Tableau: Gain skills in data visualization by creating interactive dashboards and reports.

  • Machine Learning Libraries: Learn to apply Scikit Learn, TensorFlow, and other libraries for machine learning projects.

These tools are commonly used by data professionals to analyze, model, and visualize data.



How long do these best free data science courses take to complete?

Most of these free online data science courses are designed to be completed in a short time. They range from 1 to 3 hours, allowing you to learn a specific skill in a focused and efficient manner. 



How will I gain hands-on experience in these courses?

Each course includes practical projects and real-world datasets, so you can apply what you've learned. For example, you’ll work on data analysis projects using tools like Python, SQL, and Power BI, and gain experience in tasks like feature engineering, model evaluation, and data visualization.

Are these courses suitable for beginners?

Yes, these best free data science courses are designed to cater to learners at all levels. Whether you're just starting or looking to deepen your knowledge, these courses cover fundamental concepts like data preprocessing and statistical analysis. As you progress, you’ll advance to more complex topics such as machine learning, predictive modeling, and time series forecasting.

Why take free Data Science courses from Great Learning Academy?

Great Learning Academy offers a wide range of high-quality, completely free Data Science courses. From beginner to advanced level, these free courses are designed to help you improve your Data Science and programming skills and achieve your goals. All these courses come with a certificate of completion, so you can demonstrate your new skills to the world. Start learning today and discover the benefits of free Data Science courses!
 

Who are eligible to take these free Data Science courses?

These courses have no prerequisites. Anybody can learn from these courses for free online.

Can I learn advanced data science topics through these free online data science courses?

Yes, while these courses cover essential data science fundamentals, you’ll also be introduced to advanced topics like machine learning algorithms, time series forecasting, and data visualization. For those who want to go deeper into data science, Great Learning Academy offers Pro Courses with live mentorship and guided projects to further enhance your skills.

How will these courses improve my ability to analyze data?

Our free data science courses for beginners teach you the essential techniques for handling data, from preprocessing and cleaning to building models and visualizing results. By learning tools like Python, R, and SQL, you will gain the ability to analyze large datasets, make data-driven decisions, and present findings through visual storytelling. These practical skills will empower you to solve real-world problems and unlock insights from data.

Are these courses self-paced?

Yes, these free online data science courses are self-paced, allowing you to learn at your own pace and convenience. Once you enroll, you have lifetime access to the course materials, so you can revisit the lessons and exercises whenever needed.

Can I learn data visualization with these courses?

Yes, data visualization is a core aspect of these courses. You will learn to visualize data with Tableau, Power BI, and Python, enabling you to effectively communicate your findings. These tools will allow you to create interactive dashboards, charts, and graphs that are essential for business analysis and decision-making.

Can I learn machine learning through these best free data science courses online?

Yes, machine learning is a key focus of these free online data science courses. You’ll learn foundational algorithms for classification, regression, clustering, and model evaluation. Practical exercises will help you understand how to apply these techniques to real-world data, making these courses ideal for those interested in pursuing a career in machine learning or artificial intelligence.

How will these courses prepare me for data science jobs?

These online free data science courses are designed to give you the technical skills and practical experience needed for a career in data science. You'll learn how to analyze and preprocess data, build machine learning models, and visualize results. By completing hands-on projects and developing a portfolio, you'll be well-equipped for roles in data analysis, business intelligence, and data science.

What are the steps to enroll in these free Data Science courses?

To learn Data Science basics and advance concepts from these courses, you need to,

  • Go to the course page

  • Click on the "Enroll for Free" button

  • Start learning the Data Science course for free online.

Do I need any prior knowledge to take these courses?

These free data science courses are suitable for both beginners and those with some experience. If you're new to data science, you can start with foundational courses like Introduction to Data Science and Data Science Foundations. As you progress, you can dive deeper into more advanced topics like machine learning, SQL, and data visualization.