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Reading list

Machine Learning Basics for a Newbie
6 Steps of Machine learning Lifecycle Introduction to Predictive Modeling
Introduction to Exploratory Data Analysis & Data Insights Descriptive Statistics Inferential Statistics How to Understand Population Distributions?
Reading Data Files into Python Different Variable Datatypes
Probability for Data Science Basic Concepts of Probability Axioms of Probability Conditional Probability
Central Tendencies for Continuous Variables Spread of Data KDE plots for Continuous Variable Overview of Distribution for Continuous variables Normal Distribution Skewed Distribution Skeweness and Kurtosis Distribution for Continuous Variable
Central Tendencies for Categorical Variables Understanding Discrete Distributions Performing EDA on Categorical Variables
Dealing with Missing Values Understanding Outliers Identifying Outliers in Data Outlier Detection in Python Outliers Detection Using IQR, Z-score, LOF and DBSCAN
Sample and Population Central Limit Theorem Confidence Interval and Margin of Error
Bivariate Analysis Introduction
Covariance Pearson Correlation Spearman's Correlation & Kendall's Tau Correlation versus Causation Tabular and Graphical methods for Bivariate Analysis Performing Bivariate Analysis on Continuous-Continuous Variables
Tabular and Graphical methods for Continuous-Categorical Variables Introduction to Hypothesis Testing P-value Two sample Z-test T-test T-test vs Z-test Performing Bivariate Analysis on Continuous-Catagorical variables
Chi-Squares Test Bivariate Analysis on Categorical Categorical Variables
Multivariate Analysis A Comprehensive Guide to Data Exploration The Data Science behind IPL
Supervised Learning vs Unsupervised Learning Reinforcement Learning Generative and Descriminative Models Parametric and Non Parametric model
Machine Learning Pipeline Preparing Dataset Build a Benchmark Model: Regression Build a Benchmark Model: Classification
Evaluation Metrics for Machine Learning Everyone should know Confusion Matrix Accuracy Precision and Recall AUC-ROC Log Loss R2 and Adjusted R2
Dealing with Missing Values Replacing Missing Values Imputing Missing Values in Data Working with Categorical Variables Working with Outliers Preprocessing Data for Model Building
Understanding Cost Function Understanding Gradient Descent Math Behind Gradient Descent Assumptions of Linear Regression Implement Linear Regression from Scratch Train Linear Regression in Python Implementing Linear Regression in R Diagnosing Residual Plots in Linear Regression Models Generalized Linear Models Introduction to Logistic Regression Odds Ratio Implementing Logistic Regression from Scratch Introduction to Scikit-learn in Python Train Logistic Regression in python Multiclass using Logistic Regression How to use Multinomial and Ordinal Logistic Regression in R ? Challenges with Linear Regression Introduction to Regularisation Implementing Regularisation Ridge Regression Lasso Regression
Introduction to K Nearest Neighbours Determining the Right Value of K in KNN Implement KNN from Scratch Implement KNN in Python
Bias Variance Tradeoff Introduction to Overfitting and Underfitting Visualizing Overfitting and Underfitting Selecting the Right Model What is Validation? Hold-Out Validation Understanding K Fold Cross Validation
Introduction to Feature Selection Feature Selection Algorithms Missing Value Ratio Low Variance Filter High Correlation Filter Backward Feature Elimination Forward Feature Selection Implement Feature Selection in Python Implement Feature Selection in R
Introduction to Decision Tree Purity in Decision Tree Terminologies Related to Decision Tree How to Select Best Split Point in Decision Tree? Chi-Squares Information Gain Reduction in Variance Optimizing Performance of Decision Tree Train Decision Tree using Scikit Learn Pruning of Decision Trees
Introduction to Feature Engineering Feature Transformation Feature Scaling Feature Engineering Frequency Encoding Automated Feature Engineering: Feature Tools
Introduction to Naive Bayes Conditional Probability and Bayes Theorem Introduction to Bayesian Adjustment Rating: The Incredible Concept Behind Online Ratings! Working of Naive Bayes Math behind Naive Bayes Types of Naive Bayes Implementation of Naive Bayes
Understanding how to solve Multiclass and Multilabled Classification Problem Evaluation Metrics: Multi Class Classification
Introduction to Ensemble Techniques Basic Ensemble Techniques Implementing Basic Ensemble Techniques Finding Optimal Weights of Ensemble Learner using Neural Network Why Ensemble Models Work well?
Introduction to Stacking Implementing Stacking Variants of Stacking Implementing Variants of Stacking Introduction to Blending Bootstrap Sampling Introduction to Random Sampling Hyper-parameters of Random Forest Implementing Random Forest Out-of-Bag (OOB) Score in the Random Forest IPL Team Win Prediction Project Using Machine Learning Introduction to Boosting Gradient Boosting Algorithm Math behind GBM Implementing GBM in python Regularized Greedy Forests Extreme Gradient Boosting Implementing XGBM in python Tuning Hyperparameters of XGBoost in Python Implement XGBM in R/H2O Adaptive Boosting Implementing Adaptive Boosing LightGBM Implementing LightGBM in Python Catboost Implementing Catboost in Python
Different Hyperparameter Tuning methods Implementing Different Hyperparameter Tuning methods GridsearchCV RandomizedsearchCV Bayesian Optimization for Hyperparameter Tuning Hyperopt
Understanding SVM Algorithm SVM Kernels In-depth Intuition and Practical Implementation SVM Kernel Tricks Kernels and Hyperparameters in SVM Implementing SVM from Scratch in Python and R
Introduction to Principal Component Analysis Steps to Perform Principal Compound Analysis Computation of Covariance Matrix Finding Eigenvectors and Eigenvalues Implementing PCA in python Visualizing PCA A Brief Introduction to Linear Discriminant Analysis Introduction to Factor Analysis
Introduction to Clustering Applications of Clustering Evaluation Metrics for Clustering Understanding K-Means Implementation of K-Means in Python Implementation of K-Means in R Choosing Right Value for K Profiling Market Segments using K-Means Clustering Hierarchical Clustering Implementation of Hierarchial Clustering DBSCAN Defining Similarity between clusters Build Better and Accurate Clusters with Gaussian Mixture Models
Understand Basics of Recommendation Engine with Case Study
8 Ways to Improve Accuracy of Machine Learning Models
Introduction to Dask Working with CuML
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to AutoML Implementation of MLBox Introduction to PyCaret TPOT Auto-Sklearn EvalML
Pickle and Joblib Introduction to Model Deployment
Deploying Machine Learning Model using Streamlit Deploying ML Models in Docker Deploy Using Streamlit Deploy on Heroku Deploy Using Netlify Introduction to Amazon Sagemaker Setting up Amazon SageMaker Using SageMaker Endpoint to Generate Inference Deploy on Microsoft Azure Cloud Introduction to Flask for Model Deploying ML model using Flask
Model Deployment in Android Model Deployment in Iphone

Top 11 Data Science Internships in India (2025)

Yana Khare
Yana Khare Last Updated : 03 Dec, 2024
8 min read

Introduction

In today’s data-driven world, data science skills are more crucial than ever. However, bridging the gap between textbook knowledge and real-world application is essential. Data science internships provide the perfect solution. These internships allow you to sharpen your skills by applying your programming prowess and analytical thinking to solve impactful problems. You’ll gain invaluable mentorship from experienced data scientists, learning industry best practices firsthand. The opportunity to network and build your brand with professionals creates a strong foundation for your future career.

Whether you’re a recent graduate or a career changer, an internship can be your gateway to success. Get ready to dive into the most exciting data science internships we’ve curated for you! This article discusses data science internships for freshers and students who want to start their careers in data science.

Top 11 Data Science Internships in India

Table of contents

Top Data Science Internships

Let’s take a look at the top 10 data science internships offered by various companies:

Urban NXT

Urban NXT is a digital platform that offers an immersive luxury experience, showcasing content related to cars, bikes, technology, real estate, travel, food and beverages, events, experiences, and fashion. Founded by Romin Ganatra, it began as a YouTube channel for luxury house tours and has grown into a marketing platform for luxury brands, with over 300 satisfied clients.

  • Internship Duration: 3 Months
  • Stipend: ₹3,000/month plus additional incentives
  • Location: Mumbai, India
  • Job Responsibilities: Urban NXT interns are expected to conduct thorough research on urban trends, technologies, and best practices to support innovation initiatives. They assist in analyzing data and preparing reports to identify opportunities for improvement and innovation.
  • Perks: Interns can expect to receive a certificate, letter of recommendation, flexible work hours, an informal dress code, and free snacks & beverages.

Check out the latest Data Science internships by Urban NXT here.

Blackcoffer

Blackcoffer is an enterprise software and analytics consulting firm founded by IIT alumni in India and the European Union (Malta). The company provides professional statistical advice, technological solutions, consulting, information management, and analysis for enterprises globally. It focuses on big data and analytics, data-driven dashboards, application development, and consulting.

  • Internship Duration: 6 months
  • Stipend: ₹10,000-12,000/month
  • Location: Remote
  • Job Responsibilities: Blackcoffer data science interns work on data science projects and analytics, data models, AI, ML, deep learning, and NLP. They also handle data pipelines, ETL, ELT, and data warehouses and work with Python, its libraries, and advanced programming tasks.
  • Perks: The perks include a certificate, letter of recommendation, flexible work hours, and a potential job offer upon completing the internship.

Check out the latest Data Science intern by Blackcoffer here.

Analytics Vidhya

Analytics Vidhya is a top community for professionals with analytics, data science, and AI expertise. It offers news, blogs, tutorials, data science, machine learning, AI courses, and tools to create the next generation of AI specialists.

  • Internship Duration: 6 months
  • Stipend: ₹20,000/month
  • Location: Gurugram, Haryana
  • Job Responsibilities: Interns learn Python/R, tools, and techniques used in data science. They research these tools and techniques to solve business problems and share their solutions through Analytics Vidhya. The role involves continuous learning and helping the community.
  • Perks: The perks include a certificate letter of recommendation, and exceptional interns may be considered for a full-time role

Check out the latest Data Science internships by Analytics Vidhya here.

Buddha Education Association Incorporation

Buddha Education Association Incorporation, also known as BuddhaNet, is committed to Buddha’s teachings and lifestyle. It is an online cyber sangha that links people worldwide with a shared interest in Buddhism. The association offers various educational and training opportunities.

  • Internship Duration: 1 to 2 months.
  • Stipend: ₹18,000/month.
  • Location: Remote
  • Job Responsibilities: Interns work closely with business and corporate stakeholders to understand use cases, define and analyze metrics for decision-making, analyze data, and provide technical leadership in machine learning techniques.
  • Perks: Interns are offered health insurance, and upon successful completion, they receive a certificate, letter of recommendation, and flexible work hours.

Check out the latest Data Science intern by Buddha Education Association Incorporation here.

MentorBoxx

MentorBoxx is an online platform that aims to bridge the gap between universities and industries. It selects students to interact with industry experts, work on live projects, and gain industry knowledge. The company offers multi-disciplinary courses focusing on practical skills and placement assistance.

  • Internship Duration: 2 months
  • Stipend: ₹25,000/month.
  • Location: Remote
  • Job Responsibilities: MentorBoxx interns design, develop, and debug web applications using Python and MySQL, integrate back-end services and manage multiple web applications.
  • Perks: Interns receive a certificate and letter of recommendation and benefit from flexible work hours and a 5-day work week.

Check out the latest Data Science internships by MentorBoxx here.

Xcaliber Infotech

Xcaliber Infotech is a technology consulting firm focused on mobile solutions, business intelligence, custom applications, and product development. They aim to deliver solutions that help clients grow through business-IT knowledge, thoughtful innovation, and global scale.

  • Internship Duration: 4 months
  • Stipend: ₹10,000/month.
  • Location: Pune, Maharashtra
  • Job Responsibilities: Interns analyze data to identify trends and patterns, work with advanced Excel, SQL, and data analytics tools, and collaborate on projects with industry experts.
  • Perks: Xcaliber Infotech interns receive a certificate, enjoy flexible work hours, and work a 5-day week.

Check out the latest Data Science internships by Xcaliber Infotech here.

Vayuz Technologies Private Limited

Vayuz was founded to build global and scalable technology products. They bring together world-class engineers and designers passionate for technology, focusing on areas like Data Analytics, Mobile Apps, Wearable Technology, and the Internet of Everything.

  • Internship Duration: 6 months
  • Stipend: ₹8,000/month.
  • Location: Noida, Uttar Pradesh
  • Job Responsibilities: Interns are involved in gathering requirements, managing stakeholders, product research, competitor analysis, prototyping products, project planning, and maintaining project dashboards.
  • Perks: Interns receive a certificate and letter of recommendation and benefit from an informal dress code, free snacks, a 5-day work week, and flexible work hours.

Check out the latest Data Science internships by Vayuz Technologies Private Limited here.

AI Lab Solutions

AI Lab Solutions is a digital hub that provides industry training and consulting services. It seeks to promote advancements in data analytics, faster computing, and AI. Leading the way in cutting-edge technology, AI Lab Solutions specializes in real-time facial recognition, AI, and computer vision.

  • Internship Duration: 6 Months
  • Stipend: ₹5,500/month.
  • Location: Remote
  • Job Responsibilities: AI Lab Solutions interns may work on business analytics, product management, proofreading, talent acquisition, customer service/support, content writing, and artificial intelligence.
  • Perks: Interns will receive a certificate, a letter of recommendation, and flexible work hours, with a 5-day work week.

Check out the latest Data Science internships by AI Lab Solutions here.

Business Quant

Business Quant is an investing research company established in 2014. Its emphasis is on US equities. Previously exclusive to institutional investors, it offers a wealth of data, analytics, and tools to assist individual investors in making wise investment decisions.

  • Internship Duration: 4 Months
  • Stipend: ₹3,000/month
  • Location: Remote
  • Job Responsibilities: The search results did not detail the specific job responsibilities for Business Quant data science interns. However, data science interns typically work on data analysis, building and maintaining data pipelines, and developing machine learning models.
  • Perks: Interns will also receive a certificate and a letter of recommendation and will have flexible work hours.

Check out the latest Data Science internships by Business Quant here.

Hunt Digital Media

Hunt Digital Media is a performance marketing agency that collaborates with advertisers to execute their campaigns. They focus on data analytics and have a strong presence in online marketing with their own websites and gaming apps.

  • Internship Duration: 6 months.
  • Stipend: ₹5,000/month.
  • Location: Remote
  • Job Responsibilities: Interns are responsible for downloading data, creating reports per business requirements, sharing them with the client servicing team, creating new reports as needed, and coordinating with the tech team to ensure these reports are live in the system.
  • Perks: Interns will receive a certificate and a letter of recommendation and will benefit from flexible work hours.

Check out the latest Data Science internships by Hunt Digital Media here.

Avaari

Avaari is a community platform that empowers women by providing job opportunities, gigs, and freelancing options nationwide. They are dedicated to bringing women into the workforce and helping them become potential earning members of their families.

  • Internship Duration: 1 month.
  • Stipend: ₹15,000/month.
  • Location: Remote
  • Job Responsibilities: Avaari interns analyze complex datasets to extract insights, develop advanced machine learning models using techniques like deep learning and NLP, work on data pipelines, and collaborate with cross-functional teams to improve products and services.
  • Perks: Interns will gain a certificate and a letter of recommendation, work five days a week, and have health insurance.

Check out the latest Data Science internships by Avaari here.

Eligibility Criteria for a Data Science Internship

  • Educational Background: Candidates who have completed or are seeking a degree in mathematics, computer science, engineering, or a similar discipline are usually given preference.
  • Programming Skills: Proficiency in programming languages like Python, Java, or C++ is frequently necessary.
  • Knowledge of AI Concepts: It’s crucial to comprehend deep learning, neural networks, machine learning algorithms, and other ideas.
  • Relevant Experience: It might be helpful to have completed projects, internships, or courses in artificial intelligence or machine learning in the past.
  • Strong Analytical Skills: Capacity to examine data, spot trends, and use AI to solve issues.
  • Communication Skills: Effective communication is necessary for teamwork, research presentations, and explaining difficult ideas.

Roles and Responsibilities of a Data Science Intern

  • Data Analysis: Interns are often tasked with collecting, cleaning, and analyzing large data sets to drive optimization and improvement of product development.
  • Model Development: Another key responsibility is building custom data models and algorithms to apply to data sets.
  • Collaboration: Working with different functional teams to implement models and monitor outcomes is crucial.
  • Research: Conducting research, such as A/B testing analysis, and evaluating and suggesting improvements for data management procedures.
  • Visualization: Designing interactive visualizations and developing algorithms for data extraction and manipulation.
  • Machine Learning: Implementing machine learning algorithms to identify anomalies and trends in data.
  • Communication: Presenting results and recommending intelligent solutions to solve problems and address business challenges.

Skills Required for a Data Science Internship

Technical Skills

  • Programming Languages: Proficiency in languages like Python, R, or SQL is essential for data manipulation and analysis tasks.
  • Data Visualization Tools: Knowledge of tools like Tableau and PowerBI to visualize data insights.
  • Machine Learning: Understanding of machine learning techniques to develop predictive models.
  • Big Data Frameworks: Familiarity with frameworks like Hadoop for processing large datasets.

Soft Skills

  • Analytical Thinking: Ability to analyze complex data and extract meaningful insights.
  • Communication: Strong verbal and written communication skills to present findings.
  • Time Management: Efficiently managing time to meet project deadlines.
  • Teamwork: Collaborating effectively with cross-functional teams.

Sharpen your data science skills with our AI/ML Blackbelt Plus program!

How to Find a Data Science Internship?

  • Job Posting Sites: For AI internship positions, check out some popular job posting websites among students, such as Indeed, Glassdoor, LinkedIn, and internships.com.
  • Company Websites: Start with companies’ career pages in artificial intelligence, machine learning, and data science.
  • University Career Services: Use university career services that will provide you with internship vacancies and resources.
  • Networking: Stay abreast of cutting-edge AI trends via Linkedin, AI-related events, and industry conferences.
  • Online Platforms: You can also look into AI-specific platforms such as Kaggle, GitHub, and AI-oriented forums, where AI companies usually post about internships.
  • Professional organizations: Several professional groups have been founded around intercourse AI, for example, but they are not restricted to the Association for the Progress of Artificial Intelligence (AAAI) and the Institute of Electrical and Electronics Engineers (IEEE). Non-profit organizations mostly do this; they post internship opportunities on their websites.
  • Cold Outreach: Directly email the companies by sending your employer inquiry. Send the inquiry even if the company has not yet advertised for the internship opportunity.

Tips to Get into a Data Science Internship

  • Build a Strong Foundation: First, learn data science principles and techniques through online courses, videos, and projects.
  • Work on Projects: Complete data science-related projects as a student or a project leader to demonstrate your management skills.
  • Networking: Workshops, seminars, and data science-related events offer excellent networking opportunities with professionals from your area of specialization.
  • Tailor Your Resume: Set your resume according to the specific coursework, projects, and data science skills that are crucial.
  • Prepare for Interviews: Brush up on popular Data Science interview questions to include concepts of algorithms and projects you have done.
  • Showcase Your Skills: Develop a portfolio that showcases your data science projects, code repositories, and publications or presentations.

What is the average salary for freshers in data science internships?

Depending on the source you consult, the typical pay for data science internships for freshers in India for recent graduate students can change. This is an explanation:

Higher Range: According to certain sources, the average annual salary could reach ₹18 lakhs .
Mid Range: The most typical annual values fall between ₹3 lakhs and ₹7 lakhs.
Remember that these are only averages and that your real pay will vary depending on a number of circumstances, such as:

  • Location: Salary levels in metropolitan areas are generally greater than in smaller places.
  • Company Size and Reputation: Established, larger businesses typically offer higher salaries than start-ups.
  • Industry: Pay for data science interns may be more competitive in some sectors, such as technology or finance.
  • Your qualifications and background: interns possessing robust programming skills,relevant coursework, or prior projects might command a higher stipend.

Conclusion

A job in data science requires more than just academic knowledge to get started; it also involves adaptability, lifelong learning, and practical experience. Securing an internship is only the beginning. It’s a launching pad that might lead to exciting career options and equip you with the skills, knowledge, and confidence to improve data science greatly. Seize the opportunity, submit an application to the internship program that best fits your objectives, and begin your rewarding career as a data science professional.So, We hope at the end of this article you get the best data science internships that will help for your future and make it good, these data science internships for freshers and also for the students also.

Explore out AI/ML Blackbelt Plus program to sharpen your skills!

Yana Khare
Yana Khare

A 23-year-old, pursuing her Master's in English, an avid reader, and a melophile. My all-time favorite quote is by Albus Dumbledore - "Happiness can be found even in the darkest of times if one remembers to turn on the light."

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