Most popular
Free
Self-Paced AI & Machine Learning Internship (Recorded + Practical | 6 Weeks)
What you'll learn
Build a strong foundation in Python programming for Machine Learning
Understand essential statistical concepts used in model development
Work with real-world datasets using NumPy and Pandas
Perform data cleaning and preprocessing for ML workflows
Create meaningful data visualizations to extract actionable insights
Conduct Exploratory Data Analysis (EDA) for better model understanding
Implement supervised learning algorithms such as Regression and Classification
Apply unsupervised learning techniques including clustering methods
Evaluate machine learning models using industry-standard performance metrics
Build and train deep learning models using Neural Networks, Keras, and TensorFlow
Apply NLP techniques including text preprocessing, TF-IDF, and transformer-based models.
Implement computer vision pipelines using CNNs and YOLOv8 for real-world detection tasks
Develop and deploy an end-to-end Machine Learning Capstone Project
Prepare professional project documentation aligned with industry standards
Present technical projects confidently with structured explanations
Gain practical, job-ready Machine Learning and AI skills
Receive Internship Completion Certification within 24 hours of successful completion.
-90%
Beginner
Self-Paced AI & Machine Learning Internship (Recorded + Practical | 1 Month)
₹299.00₹2,999.00
Self-Paced AI & Machine Learning Internship (Recorded + Practical | 1 Month)
What you'll learn
Build a strong foundation in Python programming for Machine Learning
Understand essential statistical concepts used in model development
Work with real-world datasets using NumPy and Pandas
Perform data cleaning and preprocessing for ML workflows
Create meaningful data visualizations to extract actionable insights
Conduct Exploratory Data Analysis (EDA) for better model understanding
Implement supervised learning algorithms such as Regression and Classification
Apply unsupervised learning techniques including clustering methods
Evaluate machine learning models using industry-standard performance metrics
Develop and deploy an end-to-end Machine Learning Capstone Project
Prepare professional project documentation aligned with industry standards
Present technical projects confidently with structured explanations
Gain practical, job-ready Machine Learning skills
Receive Internship Completion Certification within 24 hours of successful completion
Free
Self-Paced Data Analysis Internship (Recorded + Practical | 6 Weeks)
What you'll learn
By the end of this internship, you will be able to:
✓ Navigate Microsoft Excel confidently — formulas, functions, pivot tables, charts, and dashboards
✓ Write SQL queries to pull, filter, and aggregate data from real databases (SELECT, WHERE, GROUP BY, JOINs)
✓ Use advanced SQL techniques — window functions, CTEs, and performance optimisation (optional stretch content)
✓ Install and operate Tableau Public — the world's most popular data visualisation tool
✓ Build interactive dashboards with bar charts, line charts, India maps, and KPI tiles
✓ Apply calculated fields, parameters, LOD expressions, and dashboard actions
✓ Publish your work to Tableau Public to create a recruiter-ready visual portfolio
✓ Complete a capstone project from a 10-brief library — real Indian business scenarios
✓ Write a strong DA-focused resume and optimise your LinkedIn profile
✓ Practise 220+ DA interview questions covering SQL, Excel, Tableau, and behavioural rounds
✓ Understand the Indian DA job market — salary benchmarks, top hiring companies, and how to apply
✓ Earn an Internship Completion Certificate and (for top performers) a Letter of Recommendation
-90%
Self-Paced Data Science Internship (Recorded + Practical | 1 Month)
What you'll learn
Build a strong foundation in Python programming for Data Science
Understand essential statistical concepts including distributions, hypothesis testing, and correlation
Work with real-world datasets using NumPy for numerical computing and Pandas for data manipulation
Perform data cleaning, preprocessing, and feature preparation for data science workflows
Create meaningful visualisations using Matplotlib and Seaborn to extract actionable insights
Conduct structured Exploratory Data Analysis (EDA) across univariate, bivariate, and multivariate levels
Implement Regression algorithms including Linear, Ridge, Lasso, and Polynomial Regression
Implement Classification algorithms including Logistic Regression, Decision Trees, and Random Forest
Evaluate models using industry-standard metrics — RMSE, R², Accuracy, Precision, Recall, F1, and ROC-AUC
Tune and optimise models using Cross-Validation, GridSearchCV, and sklearn Pipelines
Develop an end-to-end Data Science Capstone Project on a real-world dataset
Prepare professional project documentation and a structured Jupyter Notebook
Present technical findings clearly with problem statement, methodology, and results
Gain practical, job-ready Data Science skills across the full pipeline — from raw data to trained model
Receive Internship Completion Certificate, Training Certificate, and Letter of Recommendation within 24 hours of successful completion.
-90%
Self-Paced Data Science Internship (Recorded + Practical | 6 Weeks)
What you'll learn
Build a strong foundation in Python programming for Data Science
Understand essential statistical concepts including distributions, hypothesis testing, and correlation
Work with real-world datasets using NumPy for numerical computing and Pandas for data manipulation
Perform data cleaning, preprocessing, and feature preparation for data science workflows
Create meaningful visualisations using Matplotlib and Seaborn to extract actionable insights
Conduct structured Exploratory Data Analysis (EDA) across univariate, bivariate, and multivariate levels
Implement Regression algorithms including Linear, Ridge, Lasso, and Polynomial Regression
Implement Classification algorithms including Logistic Regression, Decision Trees, and Random Forest
Evaluate models using industry-standard metrics — RMSE, R², Accuracy, Precision, Recall, F1, and ROC-AUC
Tune and optimise models using Cross-Validation, GridSearchCV, and sklearn Pipelines
Develop an end-to-end Data Science Capstone Project on a real-world dataset
Prepare professional project documentation and a structured Jupyter Notebook
Present technical findings clearly with problem statement, methodology, and results
Gain practical, job-ready Data Science skills across the full pipeline — from raw data to trained model
Receive Internship Completion Certificate, Training Certificate, and Letter of Recommendation within 24 hours of successful completion.
Trending
Free
Self-Paced AI & Machine Learning Internship (Recorded + Practical | 6 Weeks)
What you'll learn
Build a strong foundation in Python programming for Machine Learning
Understand essential statistical concepts used in model development
Work with real-world datasets using NumPy and Pandas
Perform data cleaning and preprocessing for ML workflows
Create meaningful data visualizations to extract actionable insights
Conduct Exploratory Data Analysis (EDA) for better model understanding
Implement supervised learning algorithms such as Regression and Classification
Apply unsupervised learning techniques including clustering methods
Evaluate machine learning models using industry-standard performance metrics
Build and train deep learning models using Neural Networks, Keras, and TensorFlow
Apply NLP techniques including text preprocessing, TF-IDF, and transformer-based models.
Implement computer vision pipelines using CNNs and YOLOv8 for real-world detection tasks
Develop and deploy an end-to-end Machine Learning Capstone Project
Prepare professional project documentation aligned with industry standards
Present technical projects confidently with structured explanations
Gain practical, job-ready Machine Learning and AI skills
Receive Internship Completion Certification within 24 hours of successful completion.
Free
Self-Paced Data Analysis Internship (Recorded + Practical | 6 Weeks)
What you'll learn
By the end of this internship, you will be able to:
✓ Navigate Microsoft Excel confidently — formulas, functions, pivot tables, charts, and dashboards
✓ Write SQL queries to pull, filter, and aggregate data from real databases (SELECT, WHERE, GROUP BY, JOINs)
✓ Use advanced SQL techniques — window functions, CTEs, and performance optimisation (optional stretch content)
✓ Install and operate Tableau Public — the world's most popular data visualisation tool
✓ Build interactive dashboards with bar charts, line charts, India maps, and KPI tiles
✓ Apply calculated fields, parameters, LOD expressions, and dashboard actions
✓ Publish your work to Tableau Public to create a recruiter-ready visual portfolio
✓ Complete a capstone project from a 10-brief library — real Indian business scenarios
✓ Write a strong DA-focused resume and optimise your LinkedIn profile
✓ Practise 220+ DA interview questions covering SQL, Excel, Tableau, and behavioural rounds
✓ Understand the Indian DA job market — salary benchmarks, top hiring companies, and how to apply
✓ Earn an Internship Completion Certificate and (for top performers) a Letter of Recommendation
-90%
Beginner
Self-Paced AI & Machine Learning Internship (Recorded + Practical | 1 Month)
₹299.00₹2,999.00
Self-Paced AI & Machine Learning Internship (Recorded + Practical | 1 Month)
What you'll learn
Build a strong foundation in Python programming for Machine Learning
Understand essential statistical concepts used in model development
Work with real-world datasets using NumPy and Pandas
Perform data cleaning and preprocessing for ML workflows
Create meaningful data visualizations to extract actionable insights
Conduct Exploratory Data Analysis (EDA) for better model understanding
Implement supervised learning algorithms such as Regression and Classification
Apply unsupervised learning techniques including clustering methods
Evaluate machine learning models using industry-standard performance metrics
Develop and deploy an end-to-end Machine Learning Capstone Project
Prepare professional project documentation aligned with industry standards
Present technical projects confidently with structured explanations
Gain practical, job-ready Machine Learning skills
Receive Internship Completion Certification within 24 hours of successful completion
-90%
Self-Paced Data Science Internship (Recorded + Practical | 1 Month)
What you'll learn
Build a strong foundation in Python programming for Data Science
Understand essential statistical concepts including distributions, hypothesis testing, and correlation
Work with real-world datasets using NumPy for numerical computing and Pandas for data manipulation
Perform data cleaning, preprocessing, and feature preparation for data science workflows
Create meaningful visualisations using Matplotlib and Seaborn to extract actionable insights
Conduct structured Exploratory Data Analysis (EDA) across univariate, bivariate, and multivariate levels
Implement Regression algorithms including Linear, Ridge, Lasso, and Polynomial Regression
Implement Classification algorithms including Logistic Regression, Decision Trees, and Random Forest
Evaluate models using industry-standard metrics — RMSE, R², Accuracy, Precision, Recall, F1, and ROC-AUC
Tune and optimise models using Cross-Validation, GridSearchCV, and sklearn Pipelines
Develop an end-to-end Data Science Capstone Project on a real-world dataset
Prepare professional project documentation and a structured Jupyter Notebook
Present technical findings clearly with problem statement, methodology, and results
Gain practical, job-ready Data Science skills across the full pipeline — from raw data to trained model
Receive Internship Completion Certificate, Training Certificate, and Letter of Recommendation within 24 hours of successful completion.
-90%
Self-Paced Data Science Internship (Recorded + Practical | 6 Weeks)
What you'll learn
Build a strong foundation in Python programming for Data Science
Understand essential statistical concepts including distributions, hypothesis testing, and correlation
Work with real-world datasets using NumPy for numerical computing and Pandas for data manipulation
Perform data cleaning, preprocessing, and feature preparation for data science workflows
Create meaningful visualisations using Matplotlib and Seaborn to extract actionable insights
Conduct structured Exploratory Data Analysis (EDA) across univariate, bivariate, and multivariate levels
Implement Regression algorithms including Linear, Ridge, Lasso, and Polynomial Regression
Implement Classification algorithms including Logistic Regression, Decision Trees, and Random Forest
Evaluate models using industry-standard metrics — RMSE, R², Accuracy, Precision, Recall, F1, and ROC-AUC
Tune and optimise models using Cross-Validation, GridSearchCV, and sklearn Pipelines
Develop an end-to-end Data Science Capstone Project on a real-world dataset
Prepare professional project documentation and a structured Jupyter Notebook
Present technical findings clearly with problem statement, methodology, and results
Gain practical, job-ready Data Science skills across the full pipeline — from raw data to trained model
Receive Internship Completion Certificate, Training Certificate, and Letter of Recommendation within 24 hours of successful completion.
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Free
Self-Paced Data Analysis Internship (Recorded + Practical | 6 Weeks)
💻 Best experienced on Laptop or Desktop This course includes …
What you'll learn
By the end of this internship, you will be able to:
✓ Navigate Microsoft Excel confidently — formulas, functions, pivot tables, charts, and dashboards
✓ Write SQL queries to pull, filter, and aggregate data from real databases (SELECT, WHERE, GROUP BY, JOINs)
✓ Use advanced SQL techniques — window functions, CTEs, and performance optimisation (optional stretch content)
✓ Install and operate Tableau Public — the world's most popular data visualisation tool
✓ Build interactive dashboards with bar charts, line charts, India maps, and KPI tiles
✓ Apply calculated fields, parameters, LOD expressions, and dashboard actions
✓ Publish your work to Tableau Public to create a recruiter-ready visual portfolio
✓ Complete a capstone project from a 10-brief library — real Indian business scenarios
✓ Write a strong DA-focused resume and optimise your LinkedIn profile
✓ Practise 220+ DA interview questions covering SQL, Excel, Tableau, and behavioural rounds
✓ Understand the Indian DA job market — salary benchmarks, top hiring companies, and how to apply
✓ Earn an Internship Completion Certificate and (for top performers) a Letter of Recommendation
Free
Self-Paced AI & Machine Learning Internship (Recorded + Practical | 6 Weeks)
💻 Best experienced on Laptop or DesktopThis course includes interactive …
What you'll learn
Build a strong foundation in Python programming for Machine Learning
Understand essential statistical concepts used in model development
Work with real-world datasets using NumPy and Pandas
Perform data cleaning and preprocessing for ML workflows
Create meaningful data visualizations to extract actionable insights
Conduct Exploratory Data Analysis (EDA) for better model understanding
Implement supervised learning algorithms such as Regression and Classification
Apply unsupervised learning techniques including clustering methods
Evaluate machine learning models using industry-standard performance metrics
Build and train deep learning models using Neural Networks, Keras, and TensorFlow
Apply NLP techniques including text preprocessing, TF-IDF, and transformer-based models.
Implement computer vision pipelines using CNNs and YOLOv8 for real-world detection tasks
Develop and deploy an end-to-end Machine Learning Capstone Project
Prepare professional project documentation aligned with industry standards
Present technical projects confidently with structured explanations
Gain practical, job-ready Machine Learning and AI skills
Receive Internship Completion Certification within 24 hours of successful completion.
-90%
Self-Paced Data Science Internship (Recorded + Practical | 6 Weeks)
💻 Best experienced on laptop or desktop. Interactive video lessons with …
What you'll learn
Build a strong foundation in Python programming for Data Science
Understand essential statistical concepts including distributions, hypothesis testing, and correlation
Work with real-world datasets using NumPy for numerical computing and Pandas for data manipulation
Perform data cleaning, preprocessing, and feature preparation for data science workflows
Create meaningful visualisations using Matplotlib and Seaborn to extract actionable insights
Conduct structured Exploratory Data Analysis (EDA) across univariate, bivariate, and multivariate levels
Implement Regression algorithms including Linear, Ridge, Lasso, and Polynomial Regression
Implement Classification algorithms including Logistic Regression, Decision Trees, and Random Forest
Evaluate models using industry-standard metrics — RMSE, R², Accuracy, Precision, Recall, F1, and ROC-AUC
Tune and optimise models using Cross-Validation, GridSearchCV, and sklearn Pipelines
Develop an end-to-end Data Science Capstone Project on a real-world dataset
Prepare professional project documentation and a structured Jupyter Notebook
Present technical findings clearly with problem statement, methodology, and results
Gain practical, job-ready Data Science skills across the full pipeline — from raw data to trained model
Receive Internship Completion Certificate, Training Certificate, and Letter of Recommendation within 24 hours of successful completion.
-90%
Self-Paced AI & Machine Learning Internship (Recorded + Practical | 1 Month)
💻 Best experienced on Laptop or DesktopThis course includes interactive …
What you'll learn
Build a strong foundation in Python programming for Machine Learning
Understand essential statistical concepts used in model development
Work with real-world datasets using NumPy and Pandas
Perform data cleaning and preprocessing for ML workflows
Create meaningful data visualizations to extract actionable insights
Conduct Exploratory Data Analysis (EDA) for better model understanding
Implement supervised learning algorithms such as Regression and Classification
Apply unsupervised learning techniques including clustering methods
Evaluate machine learning models using industry-standard performance metrics
Develop and deploy an end-to-end Machine Learning Capstone Project
Prepare professional project documentation aligned with industry standards
Present technical projects confidently with structured explanations
Gain practical, job-ready Machine Learning skills
Receive Internship Completion Certification within 24 hours of successful completion
-90%
Self-Paced Data Science Internship (Recorded + Practical | 1 Month)
💻 Best experienced on laptop or desktop. Interactive video lessons with …
What you'll learn
Build a strong foundation in Python programming for Data Science
Understand essential statistical concepts including distributions, hypothesis testing, and correlation
Work with real-world datasets using NumPy for numerical computing and Pandas for data manipulation
Perform data cleaning, preprocessing, and feature preparation for data science workflows
Create meaningful visualisations using Matplotlib and Seaborn to extract actionable insights
Conduct structured Exploratory Data Analysis (EDA) across univariate, bivariate, and multivariate levels
Implement Regression algorithms including Linear, Ridge, Lasso, and Polynomial Regression
Implement Classification algorithms including Logistic Regression, Decision Trees, and Random Forest
Evaluate models using industry-standard metrics — RMSE, R², Accuracy, Precision, Recall, F1, and ROC-AUC
Tune and optimise models using Cross-Validation, GridSearchCV, and sklearn Pipelines
Develop an end-to-end Data Science Capstone Project on a real-world dataset
Prepare professional project documentation and a structured Jupyter Notebook
Present technical findings clearly with problem statement, methodology, and results
Gain practical, job-ready Data Science skills across the full pipeline — from raw data to trained model
Receive Internship Completion Certificate, Training Certificate, and Letter of Recommendation within 24 hours of successful completion.
