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    4.89

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    4.94

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University & Pro Programs

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Northwestern University

18 months  • Online

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Statistics for Data Science & Analytics
40 coding exercises 3 projects
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Master Python programming
51 coding exercises 3 projects
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Master Data Analytics in SQL & Excel
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39 coding exercises 4 projects
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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
Data Science Foundations
star   4.45 660.7K+ 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 Science with Python
star   4.61 115.1K+ learners 11.5 hrs

Skills: Machine Learning,Data Transformation,Python,Jupyter Notebook,Statistics,Regression Models,Data Analytics,Data Visualizations

img icon BASICS
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GIS Essentials: Data, Tools & Applications
2.5K+ learners 2 hrs

Skills: GIS, GPS, GIS tools ArcGIS and QGIS, Spatial Data Types, Coordinate Systems, Applications of GIS, Emerging GIS technologies

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Introduction to Data Science
star   4.5 73.2K+ 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
R for Data Science
star   4.54 15.3K+ learners 2 hrs

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

img icon BASICS
Basics of Data Visualization for Data Science
star   4.48 4.4K+ learners 7.5 hrs

Skills: Data Visualization, Data Science

img icon PRO
NEW
Statistics for Data Science & Analytics
40 coding exercises 3 projects
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Data Science Mathematics
star   4.34 15.9K+ learners 1 hr

Skills: Mathematics for Data Science, Case studies

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Data Science and Business Analytics - AMA
star   4.25 8.6K+ learners 1 hr
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Probability for Data Science
star   4.47 55K+ learners 1.5 hrs

Skills: Basics of Probability, Marginal Probability, Bayes Theorem

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Data Science in Hindi
star   4.43 56.1K+ learners 2 hrs

Skills: Data Science - in Hindi, Machine Learning - in Hindi, EDA - in Hindi

free icon BASICS
Data Science Foundations
star   4.45 660.7K+ 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

free icon BASICS
Data Science with Python
star   4.61 115.1K+ learners 11.5 hrs

Skills: Machine Learning,Data Transformation,Python,Jupyter Notebook,Statistics,Regression Models,Data Analytics,Data Visualizations

pro icon PRO
End-to-End NLP with Python: Build Chatbots and LLM Applications
free icon BASICS
GIS Essentials: Data, Tools & Applications
star   4.56 2.5K+ learners 2 hrs

Skills: GIS, GPS, GIS tools ArcGIS and QGIS, Spatial Data Types, Coordinate Systems, Applications of GIS, Emerging GIS technologies

free icon BASICS
Introduction to Data Science
star   4.5 73.2K+ 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

free icon BASICS
R for Data Science
star   4.54 15.3K+ learners 2 hrs

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

free icon BASICS
Basics of Data Visualization for Data Science
star   4.48 4.4K+ learners 7.5 hrs

Skills: Data Visualization, Data Science

pro icon PRO
Statistics for Data Science & Analytics
star   4.86 1.6K+ learners 3.5 hrs
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Data Science Mathematics
star   4.34 15.9K+ learners 1 hr

Skills: Mathematics for Data Science, Case studies

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Data Science and Business Analytics - AMA
star   4.25 8.6K+ learners 1 hr
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Probability for Data Science
star   4.47 55K+ learners 1.5 hrs

Skills: Basics of Probability, Marginal Probability, Bayes Theorem

free icon BASICS
Data Science in Hindi
star   4.43 56.1K+ learners 2 hrs

Skills: Data Science - in Hindi, Machine Learning - in Hindi, EDA - in Hindi

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

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NEW
GIS Essentials: Data, Tools & Applications
2.5K+ learners 2 hrs

Skills: GIS, GPS, GIS tools ArcGIS and QGIS, Spatial Data Types, Coordinate Systems, Applications of GIS, Emerging GIS technologies

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IDEs for Data Science
892 learners 3 hrs

Skills: Jupyter, Google Colab, Spyder

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Basics of Data Visualization for Data Science
star   4.48 4.4K+ learners 7.5 hrs

Skills: Data Visualization, Data Science

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Introduction to Streamlit
star   4.46 1.4K+ learners 0.5 hr

Skills: Python skills

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Exploratory Data Analysis Projects
star   4.5 2K+ learners 2.5 hrs

Skills: Data Visualisation, Analysing the Data

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Data Preprocessing
star   4.53 10.1K+ 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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Interview Preparation for Data Science
1.8K+ learners 0.5 hr

Skills: Basics of Data Science

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Data Science in FMCG
star   4.6 5.1K+ 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 12.2K+ learners 3 hrs

Skills: Linear Programming

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Popular Applications of Data Science
star   4.55 11.8K+ learners 1 hr

Skills: Data Science Architecture, Components of Data Science, Popular applications of Data Science

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R for Data Science
star   4.54 15.3K+ learners 2 hrs

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

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Autocorrelation in Data Science
star   4.49 2.9K+ learners 1 hr

Skills: Correlation, Autocorrelation, Testing for Autocorrelation, Applications of Autocorrelation, Practical Demo in Python

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Data Science and Business Analytics - AMA
star   4.25 8.6K+ learners 1 hr
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Data Science Foundations
star   4.45 660.7K+ 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
SQL for Data Science
star   4.51 185K+ 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
Data Science with Python
star   4.61 115.1K+ learners 11.5 hrs

Skills: Machine Learning,Data Transformation,Python,Jupyter Notebook,Statistics,Regression Models,Data Analytics,Data Visualizations

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Introduction to Data Science
star   4.5 73.2K+ learners 1 hr

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img icon BASICS
Data Science in Hindi
star   4.43 56.1K+ learners 2 hrs

Skills: Data Science - in Hindi, Machine Learning - in Hindi, EDA - in Hindi

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Probability for Data Science
star   4.47 55K+ learners 1.5 hrs

Skills: Basics of Probability, Marginal Probability, Bayes Theorem

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Data Science Projects
star   4.47 27.2K+ learners 1 hr

Skills: Exploratory Data Analysis, Python, Naive Bayes

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Data Science Mathematics
star   4.34 15.9K+ learners 1 hr

Skills: Mathematics for Data Science, Case studies

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GIS Essentials: Data, Tools & Applications
2.5K+ learners 2 hrs

Skills: GIS, GPS, GIS tools ArcGIS and QGIS, Spatial Data Types, Coordinate Systems, Applications of GIS, Emerging GIS technologies

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IDEs for Data Science
892 learners 3 hrs

Skills: Jupyter, Google Colab, Spyder

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Basics of Data Visualization for Data Science
star   4.48 4.4K+ learners 7.5 hrs

Skills: Data Visualization, Data Science

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Introduction to Streamlit
star   4.46 1.4K+ learners 0.5 hr

Skills: Python skills

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Exploratory Data Analysis Projects
star   4.5 2K+ learners 2.5 hrs

Skills: Data Visualisation, Analysing the Data

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Data Preprocessing
star   4.53 10.1K+ 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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Interview Preparation for Data Science
1.8K+ learners 0.5 hr

Skills: Basics of Data Science

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Data Science in FMCG
star   4.6 5.1K+ 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 12.2K+ learners 3 hrs

Skills: Linear Programming

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star   4.55 11.8K+ learners 1 hr

Skills: Data Science Architecture, Components of Data Science, Popular applications of Data Science

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R for Data Science
star   4.54 15.3K+ learners 2 hrs

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

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Autocorrelation in Data Science
star   4.49 2.9K+ learners 1 hr

Skills: Correlation, Autocorrelation, Testing for Autocorrelation, Applications of Autocorrelation, Practical Demo in Python

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Data Science and Business Analytics - AMA
star   4.25 8.6K+ learners 1 hr

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Data Science Foundations
star   4.45 660.7K+ 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
SQL for Data Science
star   4.51 185K+ 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 with Python
star   4.61 115.1K+ learners 11.5 hrs

Skills: Machine Learning,Data Transformation,Python,Jupyter Notebook,Statistics,Regression Models,Data Analytics,Data Visualizations

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Introduction to Data Science
star   4.5 73.2K+ 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 in Hindi
star   4.43 56.1K+ learners 2 hrs

Skills: Data Science - in Hindi, Machine Learning - in Hindi, EDA - in Hindi

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Probability for Data Science
star   4.47 55K+ learners 1.5 hrs

Skills: Basics of Probability, Marginal Probability, Bayes Theorem

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Data Science Projects
star   4.47 27.2K+ learners 1 hr

Skills: Exploratory Data Analysis, Python, Naive Bayes

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Data Science Mathematics
star   4.34 15.9K+ learners 1 hr

Skills: Mathematics for Data Science, Case studies

Our learners also choose

Learner reviews of the Free Data Science Courses

Our learners share their experiences of our courses

4.48
68%
23%
6%
1%
2%
Reviewer Profile

5.0

Country Flag India
“Amazing Course with Clear and Thorough Explanations”
I enjoyed this course because it explains the concepts clearly and in a very easy-to-understand manner. The explanations helped me grasp the machine-learning concepts perfectly. I appreciate that the course covers the fundamental ideas and provides a detailed and well-structured roadmap, making it easier to follow and apply in real-world scenarios. The step-by-step approach and practical examples enhanced my learning experience, and I now feel much more confident in my understanding of machine learning.
Reviewer Profile

5.0

Country Flag Indonesia
“Unveiling the Foundations of Data Science: A Journey of Discovery”
This course provided a comprehensive introduction to the fundamental concepts and techniques of data science. I gained valuable insights into data collection, cleaning, analysis, and visualization. The course equipped me with a solid foundation for further exploration in this exciting field.
Reviewer Profile

5.0

“My Journey Through the Data Science Foundation Program”
Here are some specific aspects of the Data Science Foundation program that I particularly enjoyed: Hands-on projects: The practical assignments allowed me to apply theoretical concepts to real-world data, reinforcing my understanding and building problem-solving skills. Comprehensive curriculum: The program covered a wide range of essential topics, providing a solid foundation for further study in data science. Experienced instructors: The instructors were knowledgeable and passionate.
Reviewer Profile

5.0

“Good Curriculum and Well-Organized Syllabus”
The curriculum is comprehensive and thoughtfully structured, ensuring a smooth learning journey. The syllabus is clearly organized, with each module building on the previous one, allowing for a solid understanding of the subject matter. The content is up-to-date and relevant, with a balanced mix of theoretical knowledge and practical application. The pacing is appropriate, and the resources provided are highly useful for both beginners and advanced learners. Overall, this curriculum sets a strong foundation for anyone looking to excel in the field.
Reviewer Profile
Mussadiq Abdul Rahim

5.0

“In-Depth and Comprehensive Data Science Learning Experience”
This Data Science course offers a well-rounded and structured learning path, ideal for building strong foundational skills. Its content is thorough, covering all key areas necessary for real-world application.
Reviewer Profile

5.0

“The Course Provided a Thorough Overview of Essential Data Science Concepts”
The content was well-structured and easy to follow, covering key topics like data wrangling, statistical analysis, and machine learning. The hands-on exercises and real-world examples helped reinforce the concepts. Additionally, the instructors were knowledgeable and responsive to questions, which greatly enhanced the learning experience.
Reviewer Profile

5.0

Country Flag India
“Engaging and Insightful Learning Experience”
I liked how the content was both informative and applicable to real-world scenarios. The facilitators encouraged questions, making it a collaborative and enriching environment. The use of case studies helped reinforce the concepts discussed.
Reviewer Profile

5.0

Country Flag India
“Thank You for a Great Course”
Thank you for a great course. Great presentation style with lots of opportunities to ask questions and talk about real-life examples, which all made for a really enjoyable and informative course. This has more than met my expectations. A wonderfully practical course - both personally and professionally.
Reviewer Profile

5.0

“Best Course for Starting a Career in Data Science”
I really liked the way it was presented, the depth of the topics discussed, and how easy and engaging the topics were presented.
Reviewer Profile
Ali Raza Qureshi

5.0

“I Am Now Better Equipped to Contribute to Data-Driven Decision-Making Processes”
The comprehensive training has equipped me with fundamental skills in data analysis, machine learning, and data visualization, making me more proficient and confident in tackling complex data-related tasks.

Meet your faculty

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

instructor img

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.
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. 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.
instructor img

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

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. 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.

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.