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Pro & University Programs

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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
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Northwestern University

18 months  • Online

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Free Data Science Courses

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Introduction to Data Science
star   4.5 69.9K+ 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   4.45 655.2K+ 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   4.43 118.1K+ 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 14.7K+ 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 20K+ learners 1.5 hrs

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

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Data Preprocessing
star   4.54 9.9K+ 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   4.51 173.6K+ 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 15.4K+ learners 1 hr

Skills: Mathematics for Data Science, Case studies

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Data Visualization With Power BI
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star   4.52 353.8K+ 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   4.52 114.7K+ 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   4.51 102.6K+ 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 89.9K+ learners 2 hrs

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

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Introduction to Data Science
star   4.5 69.9K+ 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   4.45 655.2K+ 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   4.43 118.1K+ 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 14.7K+ 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
star   4.49 20K+ learners 1.5 hrs

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

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Data Preprocessing
star   4.54 9.9K+ 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   4.51 173.6K+ 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 15.4K+ learners 1 hr

Skills: Mathematics for Data Science, Case studies

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Data Visualization With Power BI
star   4.52 353.8K+ 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   4.52 114.7K+ 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   4.51 102.6K+ 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 89.9K+ learners 2 hrs

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

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Predict Footballer Transfer Market Value using Data Science
star   4.63 776 learners 0.5 hr

Skills: Python,EDA

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Predicting FIFA winner using Data Analytics
star   4.38 963 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 9.9K+ 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 6K+ 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 16.2K+ 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 20K+ 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 53.4K+ 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   4.66 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 37.8K+ 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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Data Science in FMCG
star   4.61 4.9K+ learners 1 hr

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

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star   4.61 2K+ learners 2 hrs

Skills: Forecasting Hospital Blood Requirements

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star   4.59 12.1K+ learners 3 hrs

Skills: Linear Programming

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Data Science Foundations
star   4.45 655.2K+ 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   4.52 353.8K+ learners 1.5 hrs

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

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SQL for Data Science
star   4.51 173.6K+ 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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Python for Data Science
star   4.43 118.1K+ 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   4.52 114.7K+ 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   4.51 102.6K+ 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 89.9K+ learners 2 hrs

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

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Introduction to Analytics
star   4.51 84.9K+ learners 2 hrs

Skills: Spectrum of Analytics, Descriptive Analytics

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Predict Footballer Transfer Market Value using Data Science
star   4.63 776 learners 0.5 hr

Skills: Python,EDA

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Predicting FIFA winner using Data Analytics
star   4.38 963 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 9.9K+ 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 6K+ 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 16.2K+ 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 20K+ learners 1.5 hrs

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

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star   4.68 53.4K+ learners 1.5 hrs

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Apriori Algorithm
star   4.66 1.6K+ learners 2 hrs

Skills: Conjoint Analysis,Market Basket Analysis,Apriori Algorithm

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star   4.64 1K+ learners 1 hr

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star   4.62 37.8K+ learners 3 hrs

Skills: RFM Analysis, KINME

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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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star   4.61 4.9K+ learners 1 hr

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

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star   4.61 2K+ learners 2 hrs

Skills: Forecasting Hospital Blood Requirements

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star   4.59 12.1K+ learners 3 hrs

Skills: Linear Programming

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Data Science Foundations
star   4.45 655.2K+ 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   4.52 353.8K+ learners 1.5 hrs

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

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SQL for Data Science
star   4.51 173.6K+ 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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Python for Data Science
star   4.43 118.1K+ 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   4.52 114.7K+ 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   4.51 102.6K+ 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 89.9K+ learners 2 hrs

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

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Introduction to Analytics
star   4.51 84.9K+ learners 2 hrs

Skills: Spectrum of Analytics, Descriptive Analytics

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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

“Excellent Introductory Course for Data Science Enthusiasts”
I enjoyed the course structure and the way complex concepts were broken down into simpler, digestible parts. The practical examples and hands-on projects helped me apply what I learned effectively. It was a great introduction to the world of data science, and I feel much more confident now.

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5.0

“Great Platform for Career Preparation”
I came here to learn more about data science. With a background in mathematics, I knew enough about statistical analysis but lacked an understanding of the proper workings and ideas of what data science is all about. This course really helped me.

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Reviewer Profile

5.0

“It Was a Nice Experience and I Got a Great Start to the Subject”
The course was well delivered, and I am so grateful to participate.

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Reviewer Profile

5.0

“I Was Able to Get a Good Understanding of What Data Science Is All About”
I liked the course content structure and the language made it easy to understand. Topics were covered in a systematic manner, giving an overview and further insights that need to be taken into account.

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Reviewer Profile

5.0

“A Wonderfully Practical Course - Both Personally and Professionally”
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.

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5.0

“It Was a Very Quick and Engaging Course”
I loved the way the topics, which seemed to be of great depth, were explained effortlessly. As a result, the course was easy to follow and allowed me to retain whatever crucial knowledge was shared.

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Reviewer Profile

5.0

“I Gained a Solid Foundation in Data Science Fundamentals”
This course has been instrumental in laying the groundwork for my data science journey, and I look forward to continuing my growth and development in this field.

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Reviewer Profile

5.0

“Exemplary Curriculum That Is Easy to Follow and a Perfect Instructor”
The instructor was audible and clear with a good understanding of the topics. He explained the concepts and processes well enough to follow clearly. The course is also well structured.

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Reviewer Profile

5.0

“First, I Gained an In-Depth Understanding of Introduction to Data Science”
I enjoyed the structured and comprehensive approach to learning, especially how the courses break down complex topics into digestible sections. The real-world case studies and interactive learning methods also kept me engaged, making the concepts easier to grasp.

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5.0

“The Course Was Informative and Engaging”
The course provided a solid introduction to data science concepts, covering essential topics such as statistics, data manipulation, machine learning, and data visualization. The materials were well-structured and easy to follow.

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Learn Data Science For Free & Get Completion Certificates

Data Science is a subdomain of computer science and technology that utilizes scientific techniques, processes, algorithms, and systems to extract derived information and insights from structured and unstructured data. It is an interdisciplinary field that combines computer science, mathematics, statistics, and other related fields to analyze, predict, and visualize data. Data science has integrated modern businesses and has been used to improve decision-making, identify new opportunities, and solve complex problems. 

 

Data science is used in various industries, including finance, healthcare, education, and marketing. It is used to identify patterns and relationships in data, uncover hidden insights, and make accurate predictions. For example, data science can be applied to analyze customer purchasing patterns, identify potential customer segments, and develop targeted marketing campaigns. It can also detect fraud, optimize pricing, and predict future trends. 

 

Data science is also used to power Artificial Intelligence and Machine Learning. Machine Learning algorithms use data science to learn from data and make predictions. Data science is used to train and test machine learning models, identify correlations, and draw conclusions from complex data sets. 

 

Data science can also create predictive models and simulations. Data scientists can identify patterns and relationships, build models, and simulate future outcomes and scenarios by analyzing data. This can be used to make more informed decisions and create better strategies. 

 

Data science has become an increasingly important part of the modern world, and its applications are proliferating. It can revolutionize how we do business, make decisions, and interact with data. With the right strategies and techniques, data science can improve the efficiency and accuracy of data-driven decisions and enable businesses to gain deeper insights into their customers, operations, and markets.

 

Data Science Tasks

 

Data Science tasks involve the analysis of large and complex datasets to discover hidden patterns, correlations, and insights. Data Science tasks involve a combination of techniques and processes, including data mining, machine learning, predictive analytics, and visualization. Data Science tasks aim to use data to gain knowledge and insights that improve a business or other organization's operations. 

 

Data Science gathers and cleans data from multiple sources. This process includes collecting data from various sources, such as databases, websites, surveys, and other sources. After the data is collected, it must be cleaned and analyzed to identify patterns, correlations, and insights. The data must also be organized and structured to make it easier to work with. 
 

 

Data Science tasks also include 

 

  • Creating predictive models. Predictive models use data to forecast future outcomes. These models are used to make investments, business strategies, and product development decisions. 
  • Using visualization tools to represent data in an easy-to-understand format. Popular visualization tools include charts, tables, and graphs. Visualization tools help organizations make better decisions by providing clear insights into the data. 
  • Communicating the results of the data analysis. This includes creating reports and presentations that explain the findings to stakeholders and other decision-makers. 

 

Data Science tasks are an essential part of any organization's operations. Data Science professionals use their technical skills and knowledge to help organizations gain valuable insights from their data. By understanding and interpreting data, organizations can make better decisions and create strategies to help them achieve their goals. 

 

Great Learning Academy offers a variety of free Data Science courses online that can help you gain the expertise and knowledge you need to pursue a career in the field. These courses typically focus on helping you gain a better understanding of the fundamentals of Data Science, such as programming languages, algorithms, and data manipulation. No matter which type of free Data Science course you choose, you can be sure that you'll be well-equipped with the knowledge and skills necessary to pursue a successful career in the field. With various free Data Science courses, you can learn about various concepts under the subject online for free.

 

Register for the Data Science certificate course if you want to get professionally certified. 

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.
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

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

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
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

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.
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. 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

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 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.

How long does it take to complete these Data Science free courses?

These courses include 1-8 hours of video lectures. These courses are, however, self-paced, and you can complete them at your convenience.

What knowledge and skills will I gain upon completing these free Data Science courses?

Upon completing these free Data Science courses, you will gain a wide range of knowledge and skills, including an understanding of the fundamentals of data science, algorithms and machine learning, data analysis and visualization, programming languages such as Python and R, and the tools and applications used in data science. Additionally, you will gain experience with data wrangling, predictive modeling, and data-driven decision-making.

Will I obtain a formal certification after finishing these free Data Science courses?

These free Data Science courses offers a certificate of completion upon finishing, not a professional certification.

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.
 

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

Yes. After completing them successfully, you will receive a certificate of completion for each course. 

How much do these free Data Science courses cost?

These are free courses; you can enroll in them and learn for free online. 
 

Is it worth learning about Data Science?

Data scientists are in great demand right now, and it's an excellent choice to start a career in data science. Unfortunately, the majority of those who attempt to learn data science fail because their approach needs to be revised with errors that impede their advancement. You can therefore choose to learn from the Data Science course for beginners to escalate your learning in Data Science and programming from basics. 

 

Why is Data Science so popular?

Data science is a large field of study that is expanding, which means there will be plenty of chances in the future. The discipline of data science is anticipated to become increasingly specialized as employment functions get more specialized. Because it has been revealing outstanding solutions and wise decisions across numerous industries, data science is crucial for organizations.
 

What jobs demand you learn Data Science?

Jobs that are directly related to Data Science are

  • Business Intelligence Analyst
  • Data Mining Engineer
  • Data Architect
  • Data Scientist
     

Why take 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. 

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.