Data Analytics
Turn Data Into Decision that Matter
Learn how to extract meaning from complex datasets, solve real-world problems with
insights, and build a career grounded in data-led impact.
insights, and build a career grounded in data-led impact.
Our Program Aims To
01
Train students in evidence-based decision making
02
Democratize access to analytics education through hands-on learning
03
Build a workforce that applies data to drive change in society and industry
What you’ll Learn
Writing code to solve problems and automate solutions is a crucial skill for anyone in IT. This module teaches Python programming and its applications in system administration, automation, and cloud computing. Learners will gain hands-on experience with Git and GitHub, troubleshooting, debugging, and best practices in software development.
Applied Learning Project – Learners will complete a capstone project where they will automate system administration tasks using Python.
Prerequisites and Eligibility
This course is open to learners from all educational and professional backgrounds. No prior programming experience is required — beginners and experienced learners alike can benefit.
This module introduces learners to SQL and its applications in database management. SQL is a fundamental tool for querying, analyzing, and manipulating data in relational databases.
Applied Learning Project – Learners will design and query a relational database to solve real-world data problems.
Prerequisites and Eligibility
Basic understanding of data structures and programming concepts is helpful but not required.
This module provides hands-on experience with machine learning techniques and their applications.
Applied Learning Project – Learners will develop and fine-tune an ML model using real-world data.
Prerequisites and Eligibility
Python and statistics knowledge is recommended.
This module covers business intelligence and data visualization using Power BI, a leading analytics tool.
Applied Learning Project – Learners will build an interactive business intelligence dashboard using real-world datasets.
Prerequisites and Eligibility
Basic knowledge of Excel or databases is recommended.
This module focuses on big data processing and distributed computing using PySpark.
Applied Learning Project – Learners will process and analyze large datasets using PySpark.
Prerequisites and Eligibility
Familiarity with Python and SQL is recommended.
This module introduces Dataiku, a collaborative data science platform, allowing users to build machine learning models and automate workflows.
Applied Learning Project – Learners will use Dataiku to build an end-to-end machine learning pipeline.
Prerequisites and Eligibility
Basic knowledge of data analysis and Python is recommended.
This module explores the applications of Large Language Models (LLMs) in NLP and AI-driven analytics.
Applied Learning Project – Learners will fine-tune an LLM for a specific NLP task.
Prerequisites and Eligibility
Familiarity with Python and machine learning concepts is recommended.
Students will complete a real-world analytics project, using SQL and Dataiku for data collection, Python and PySpark for processing, and Power BI for visualization. They’ll build predictive models, apply LLM tools for text analysis, and automate workflows. The project ends with a dashboard and presentation showcasing end-to-end analytical and business insights.
Prerequisites and Eligibility
Those completing all core modules—including Python, SQL, Dataiku, PySpark, Applied Machine Learning, Applied LLM and Power BI—will be eligible to undertake the capstone. This ensures a solid foundation for delivering a complete, end-to-end analytics solution.
Program Highlights
Unlock the core experiences that turn enthusiasts into Data Analyst
Hands on Learning
Work directly with datasets from the field. Use industry-standard tools to clean, explore, and present data with confidence.Expert Mentorship
30+ leading data professionals will guide your learning journey, helping you frame problems, ask better questions, and grow your analytical mind.Technical Excellence
Build a strong foundation in both analytical tools and problem-solving approaches. Explore real-world case studies and applied exercises to develop practical skills.Real world Projects
Solve challenges that go beyond dashboards and make a tangible impact on communities and institutions.FAQs
- Does registration mean we are enrolled in the internship?
No, registration does not confirm your enrollment in the internship. The applicant must have to clear the aptitude test and successfully clear the interview round.
- When will the internship start?
The internship will commence in the first week of July for July-Dec batch and in the first week of Jan for Jan-June batch. Selected candidates will receive onboarding emails detailing the exact start date via their registered email addresses.
- Is the internship paid?
No, the internship is not paid. The interns will not receive financial compensation for their work during the internship.
- What will be the fee for the internship?
This internship involves no fees; it is fully funded by Sabudh Foundation.
- Is the internship online or offline?
The internship is conducted online.
- Is there placement support after the internship?
While we do not offer direct placement after the internship, we actively support our interns by guiding them toward relevant job opportunities and organizing expert sessions to enhance their interview readiness.
- What will be the medium of communication throughout the program?
The medium of communication will primarily be through email.
- How many seats are available for the program?
We can accommodate approximately 200 full-time interns in the Data Science program, 30 interns in the AIoT program, and around 60 interns in the Data Analytics program. However, the final selection depends on the applicant’s performance in the aptitude test and interview. Please note that candidates unable to commit sufficient time on weekdays are generally not considered for full-time internship programs.
- How do I choose between a full-time and part-time internship in Data Science?
A full-time internship in data science requires dedicated time to attend live sessions, complete courseworks/assignments, and work on projects with strict deadlines. On the other hand, part-time interns are exempt from attending live sessions and are not assigned a project until all modules of the internship are successfully completed. We recommend carefully choosing the type of internship based on your availability and commitment, as switching between full-time and part-time options after final selection is not permitted.
- Can I switch from Data Science to AIoT or Data Analytics (or vice versa) if I develop an interest in the other field during the internship?
No, switching between Data Science, AIoT, and Data Analytics is not permitted once the internship has begun. Your selection is based on an aptitude test and interview tailored to the course you chose. This process ensures the internship matches your skills and interests from the beginning.
- How do I distinguish between Data Science and Data Analytics?
Data Science focuses on developing models and algorithms using statistics and machine learning. Data Analytics is more application-oriented, emphasizing the use of existing tools to interpret data and derive actionable business insights. We encourage you to review the detailed curriculum of each program for better clarity and alignment with your interests.
- I can see the course but I am not able to access the content?
Yes, you can change your Educollab password by clicking on “forgot my password,” providing your email, and following the instructions provided on the user interface.
- I am not able to navigate to the aptitude test tab. What should I do?
Steps to navigate:
- Login to your educollab account
- Search for Sabudh Workshop (Jan – Jun 2026)
- Navigate to the assessments tab
- I can see the course but I am not able to access the content?
Make sure you have subscribed to the course.
- I don’t have the educollab credentials. How should I attempt the aptitude test?
If you have just registered for the internship, please wait at least 48 hours to receive your login credentials. If it has been more than 48 hours, try searching for “Educollab” in your inbox or spam folder—the credentials email should be there. If you still haven’t received it, please write to admin.info@sabudh.org for assistance.
- I applied for the Data Science internship. Should I attend the Awareness Workshop?
Attending the Awareness Workshop is not mandatory, but it is highly recommended as it can help you prepare better for the aptitude test. Any applicant, regardless of the program they have applied for, is welcome to attend. During the workshop, Sabudh will conduct sessions on key topics including Python, Data Science, Large Language Models, and Generative AI, among others.
- I missed the aptitude test, will I get a second chance?
No, there is no second chance if you miss the aptitude test. It is advised to regularly check your registered email for important updates. Along with that, please make sure to join the official WhatsApp group for timely notifications and announcements.
- Are the assignments shared after the workshops mandatory to attempt?
Assignments shared after the workshops are not mandatory, but it’s recommended to attempt and submit them as practice.
- What is the next step after the aptitude test?
The next step after the aptitude test is the final interview.
- What are the passing marks for the aptitude test?
The passing marks for the aptitude will be determined after evaluating the responses. We will set a cut-off based on the total number of candidates who participated in the aptitude and their performance.
- Where can I find the course content of the workshop?
Registered participants of the internship and/or workshop will receive login credentials to access the learning platform; Educollab, where the workshop content is hosted. These credentials will be sent to their registered email addresses directly by Educollab.
- Is the workshop conducted offline or online?
The workshop will be held online over the weekend (two days).
- How can I best prepare for the aptitude test? Which topics should I prioritize to ensure success?
To prepare effectively for the aptitude test, focus on basic programming, logical reasoning, critical thinking, basic mathematics, and statistics.
- Will the aptitude test be offline or online?
The aptitude test will be conducted online and hosted on our learning platform, Educollab. Applicants will be notified via their registered email addresses about the date and time of the test to ensure they can easily attempt it.
- Who is eligible for this program?
Individuals who have a 6-month training period as part of their college curriculum or can dedicate full-time availability for six months are best suited for this program.
- What is the prerequisite for this program?
For Data Science and Data Analytics, a basic understanding of programming and mathematics is required. For the AIoT Program, basic knowledge of C programming and a fundamental understanding of electronics concepts are prerequisites.
- Will academic performance be taken into account during the selection process?
We do not directly consider academic marks for the internship selection process. However, candidates with very poor academic records or pending supplementary exams may not be considered for the internship.
- How are interns selected after registration?
After registration, applicants will receive an automated email containing important dates and a link to our official WhatsApp group. An awareness workshop will be conducted on topics relevant to the internship programs, which registered/non-registered candidates can join to gain insights into the six-month learning journey. Following the workshop, we will roll out an aptitude test. Applicants who score above the cut-off in aptitude test will be invited for interviews. Those who successfully clear the interview will receive onboarding letters.
- What will be the basis of the interview assessment?
The interview will primarily assess your fundamental understanding of programming and mathematics. However, candidates who also possess basic domain-specific knowledge will have an advantage.
- Is attendance compulsory during the live sessions?
Yes, attendance is compulsory during live sessions for full-time interns.
- If I miss the session, will I get lecture resources?
Yes, all the live sessions are recorded and uploaded to our learning platform, Educollab, for easy access.
- What is the expected time commitment for the program?
Learners are expected to commit a minimum of 48 hours per week, which includes teaching sessions, lab work, project activities, and self-learning hours to successfully complete the program.
- Can I enroll in just one course, such as Machine Learning or Python?
Yes, if you are enrolling in the Data Science program, you may opt for individual modules, provided you meet the necessary prerequisites. Please refer to the program brochure for detailed learning paths and course requirements. However, enrollment in individual modules is not available for the Data Analytics or AIoT programs.
- What are the timings of live sessions?
Our live sessions typically commence at 8:00 am, with 2-3 classes scheduled each day, each lasting around 1-1:30 hours.
- Besides live classes, what other commitments are there during the course?
In addition to live classes, interns must actively participate in passion project meetings with their mentors, as these are a key part of the program. They are also required to attend weekly catch-up sessions with the program coordination team, join expert sessions, and ensure the timely completion of coursework and assignments for successful completion of the internship.
- What will be the duration of the project in the Data Science Program?
The project component of the internship requires a solid understanding of Python and a foundational knowledge of Machine Learning. As both Python and Machine Learning are introduced from Day 1 of the internship, the theoretical groundwork necessary for the project is gradually built during the initial phase. While the project is designed as a six-month module, students typically begin active work on their project around 1.5 months after the internship commences.
- Will the project in Data Science be a live project?
Yes, the project will be a live project
- What is the duration and structure of the project in the Data Analytics program?
The capstone project in the Data Analytics program spans approximately 1.5 months. Students will complete a real-world project using SQL, Python, Dataiku, ML, PySpark, Power BI, and LLM tools, ending with an automated dashboard and insights presentation.
- What is the duration and structure of the project in the AIoT program?
The AIoT project will span 2 months. During this time, interns will apply the knowledge gained throughout the modules in a hands-on internship setting.
- Will I get the option to choose a project of my interest, or will it be allocated by you?
Data Science Program: Projects will be allocated based on your interests and availability. Data Analytics Program: A predefined capstone project will be shared with you to complete. AIoT Program: Students can suggest project ideas. Mentors will review them and may modify them based on feasibility.
- Will the project be teamwork or individual?
For the Data Science program, projects will be completed in teams. However, in the Data Analytics and AIoT programs, projects will be done individually.
- Will I be allocated a guide/mentor for the projects?
Yes, you will be assigned a mentor to provide guidance throughout the project.
- I am doing this internship to submit a project in college, can I submit the same project?
Yes, you may submit the same project results for your college requirements. However, please note that project codes involving proprietary or sensitive data are copyrighted by Sabudh Foundation, while projects using open-source data are fine to submit. Additionally, if you are part of the Data Science program, please acknowledge that the project was completed as part of a team effort.
- Will I receive a certificate after completing the internship?
Yes, you will receive a certificate of completion for the full-time internship. For the Data Science part-time internship, a separate module-wise certificate will be provided.
- Will the certificate be recognized by organizations?
Yes, the certificate is an official proof of completion and features the logos of Sabudh Foundation and STPI, making it credible and valuable for professional purposes.
Still have Questions?
Reach out to our team or check the detailed curriculum to see if this path aligns with your goals
