Learn Future Skills Early
India's Most Advanced Artificial Intelligence & Data Science Program for Kids. The world is entering the age of Artificial Intelligence. From ChatGPT, Self-Driving Cars, Smart Assistants, Robots, Medical AI, Space Technology, and Future Startups, Artificial Intelligence is shaping the future of every industry. Unfortunately, most students only learn these technologies after college. Skillonit's AI Young Data Scientist Program changes that. This revolutionary 15-month program is specially designed for students from Class 2nd to 10th, helping them learn Artificial Intelligence, Machine Learning, Data Science, Coding, Problem Solving, Innovation, Robotics, Entrepreneurship, and Future Technologies from an early age.
Instead of just using technology, students learn how to build technology. By the end of the program, students can create AI-powered applications, intelligent systems, automation projects, data-driven solutions, websites, software applications, and innovation projects. This is not just a course. This is a Future Technology Transformation Program.
Learners who want face-to-face teaching, fixed batches, and local classroom guidance.
Included in this mode
Learning flow
Unlike traditional computer courses, our program follows a practical, innovation-first approach. Students don't just learn theory. They build. They experiment. They innovate. They create.
Artificial Intelligence (AI) is the ability of machines and computers to think, learn, solve problems, and make decisions similar to humans. Today AI is used in Google Search, ChatGPT, YouTube Recommendations, Netflix, Amazon, Self-Driving Cars, Smart Robots, Healthcare, Banking, Space Technology, Cyber Security, and Education. Students who understand AI today will lead tomorrow's world. Data Science is the science of collecting, analyzing, and understanding data to make better decisions. Every company in the world uses Data Science to understand customers, predict future trends, improve products, make smart business decisions, and develop AI systems. Students will learn how data becomes intelligence and how intelligence becomes innovation.
15-Month Structured Learning Path
Artificial Intelligence Training
Machine Learning Training
Data Science Training
Active module
1Phase 1: Digital Foundation - Computer Fundamentals, Internet Fundamentals, Digital Literacy, Safe Internet Usage, Typing Skills, Computer Operations, File Management, Operating Systems, Google Workspace, Digital Productivity
2Phase 2: Coding Foundation - Logic Building, Problem Solving, Algorithms, Flowcharts, Programming Concepts, Introduction to Coding, Computational Thinking
3Phase 3: Programming with Python - Python Basics, Variables, Data Types, Conditions, Loops, Functions, Lists, Dictionaries, Projects, Games, Applications
Selected batch
Start DateUpcoming
TimingsWeekday & Weekend
Duration15 Months
ModeClassroom
Lead Trainer
AI/ML & Data Science Instructor
6+
Years Experience
LAB
Practice Support
Supports learners with AI, machine learning, data science concepts, applied projects, and analytical thinking.
Prathamesh Pathak focuses on practical AI Young Data Scientist training with a learner-first approach. Sessions combine clear concept explanation, demonstrations, lab-based practice, and interview-oriented guidance so students understand how the skill is applied in real work.
Real Industry Experience
Child-Friendly Teaching Methods
Practical Learning Approach
Innovation Mentorship
AI Project Guidance
Startup & Entrepreneurship Mentoring
Personalized Student Attention
Career Development Support
Upon successful completion, students receive the prestigious Skillonit Certified Young AI Data Scientist Certificate. This certification validates skills in Artificial Intelligence, Machine Learning, Data Science, Python Programming, Problem Solving, Innovation, Technology Development, and Project Creation.
Industry Recognition
Student Portfolio
College Admission Advantage
Competition Participation
Technology Skill Validation
Innovation Recognition
Future Career Preparation
Global Technology Exposure
Certificate ID
SKL-AI--2026
Certificate of Completion
This certifies that the student has completed Skillonit’s AI Young Data Scientist training with practical tasks, quizzes, and project assessment.
Presented to
Student Name
For successful completion of AI Young Data Scientist Course
Completion Date
18 Jun 2026
Authorized Signature
Verification-ready certificate preview for LMS completion.
15-Month Structured Learning Path
Artificial Intelligence Training
Machine Learning Training
Data Science Training
Coding & Programming
Python Development
Real AI Projects
Portfolio Development
National-Level Certification
Online & Offline Learning
Recorded Sessions
Dedicated LMS Access
Innovation Challenges
Hackathons
Project Showcases
Parent Progress Reports
Career Guidance
Entrepreneurship Training
Leadership Development
Future Technology Exposure
Tools students practice
This course blends clear concepts, practical training, guided projects, quizzes, and career-focused assessment to help learners build confidence and move toward real opportunities.
Students will build a strong foundation for future careers such as Artificial Intelligence Engineer, Machine Learning Engineer, Data Scientist, Software Developer, Cyber Security Specialist, Robotics Engineer, Automation Expert, App Developer, Web Developer, Blockchain Developer, Startup Founder, Technology Entrepreneur, Research Scientist, Innovation Consultant, Digital Creator, and Future Technology Leader.
Most students spend 15-20 years in education but graduate without future-ready skills. The AI revolution is already here. Parents who prepare their children today will give them a significant advantage tomorrow. Skillonit's AI Young Data Scientist Program helps students learn future skills early, build confidence, become technology creators, think like innovators, develop leadership skills, improve problem solving, understand Artificial Intelligence, create real projects, become startup ready, become career ready, and prepare for the future.
Computer Fundamentals
Coding & Programming
Python Programming
Data Science Fundamentals
Artificial Intelligence
Machine Learning
Data Analytics
Robotics Concepts
Computer Vision
AI Chatbots
Prompt Engineering
Automation
Mobile App Development Basics
Website Development
Innovation Thinking
Entrepreneurship
Startup Fundamentals
Public Speaking
Leadership Skills
Real AI Projects
Portfolio Development
Admission enquiry
Share your details and our team will help you choose the right AI Young Data Scientist batch, learning mode, syllabus, fee plan, and career path.
Most children use smartphones, apps, games, and AI tools every day. Very few know how they are built. This program helps students move beyond consumption and become creators of technology. By the end of 15 months, students will have built projects, explored Artificial Intelligence, developed problem-solving abilities, and gained exposure to future technologies that many students only encounter during engineering or college education. The goal is simple: Create the next generation of AI Innovators, Data Scientists, Startup Founders, and Technology Leaders from India.
Build strong foundation skills in AI Young Data Scientist
Apply concepts through guided practical projects
Use portfolio work to start client-ready practice
Prepare for internships, jobs, or higher learning
AI Engineers
Data Scientists
Software Developers
Startup Founders
Technology Innovators
Researchers
Robotics Experts
Problem Solvers
Digital Creators
Global Technology Leaders
Internship Program
Skillonit’s AI Young Data Scientist Internship Program in India is a mentor-guided practical pathway available in 1-month, 3-month and 6-month formats. Participants learn how to help young learners progress from computer basics and logic to coding, Python, data stories, machine learning, responsible AI and their own supervised AI applications. The program combines structured training, assignments, project reviews, documentation, portfolio support and a completion certificate subject to published requirements.
The internship is designed for learners aged 6–16, grouped into age-appropriate foundation, explorer and innovator pathways with parent or guardian involvement. It turns course knowledge into structured practice through mentor-led onboarding, guided tasks, project milestones, review meetings, documentation and a final presentation. Participants are expected to build, test, explain and improve their work instead of only watching demonstrations.
Available durations
1 month, 3 months and 6 months
Delivery modes
Live online, classroom or hybrid—subject to the selected batch and location
Learning model
Training + mentor-guided tasks + project reviews + portfolio evidence
Projects
Mini project, guided projects and capstone according to duration
Support
Onboarding, doubt clearing, task planning, review feedback and presentation guidance
Certificate
Issued after required attendance, submissions, evaluation and final presentation
About Program
Skillonit’s AI Young Data Scientist internship is designed as a bridge between learning and practical delivery. Interns begin with a baseline assessment and a clear task plan, then progress through demonstrations, guided exercises, independent work and review. The focus is on understanding why a solution works, how to communicate decisions and how to improve quality after feedback.
The work is aligned with digital literacy, logic, block coding and safe technology use, Python applications, data analysis and visual stories and advanced Python, model evaluation and responsible AI. Longer pathways include more complex requirements, collaboration, documentation, testing and presentation. Interns maintain a task log or project board so that progress can be reviewed objectively rather than judged only by the final output.
The internship does not guarantee employment, freelance income, client allocation or a stipend. It provides practical exposure, evidence of completed work and career-readiness support. Any employment or paid internship opportunity is published separately with its own eligibility, application deadline, compensation and selection process.
Duration Options
The one-month pathway is a focused four-week experience for learners who want an introduction to professional AI, coding and data science for young learners practice. It prioritizes orientation, essential tools, one clear workflow and a mentor-reviewed mini project. It is most suitable for beginners, students testing the domain, or course learners who need a short practical component.
Week 1 – Orientation and foundation: skill assessment, program rules, tool setup, task tracking, digital literacy, logic, block coding and safe technology use and a short guided exercise.
Week 2 – Core practice: beginner Python and data representation, mentor demonstration, individual practice and a quality checklist.
Week 3 – Mini project build: apply creative problem-solving and project communication to a scoped project with milestone review and corrections.
Week 4 – Finalization: testing or quality review, documentation, presentation, mentor feedback and next-learning roadmap.
Expected 1-month evidence: One completed mini project, task log, project summary, mentor feedback record and final presentation. Example project: Interactive coding story or game.
The three-month pathway is the recommended option for learners who want meaningful portfolio evidence. It combines a foundation phase, an applied phase and a capstone phase. Interns work on at least two guided assignments and one larger project, with regular reviews that focus on quality, documentation and problem-solving.
Month 1 – Foundation and workflow: digital literacy, logic, block coding and safe technology use, beginner Python and data representation, creative problem-solving and project communication; tool setup; guided exercises; communication and documentation standards.
Month 2 – Applied delivery: Python applications, data analysis and visual stories, age-appropriate machine-learning concepts, chatbot, image or recommendation prototypes; first project review; debugging, critique or analysis; iteration after feedback.
Month 3 – Capstone and portfolio: build Python utility or quiz application or another approved project; complete testing, documentation, presentation and portfolio packaging.
Expected 3-month evidence: Two guided projects, one capstone, weekly progress records, review notes, final presentation and a portfolio-ready case study. Suggested project options include Data-story dashboard, Python utility or quiz application and Image or text classifier with safe data.
The six-month pathway is intended for learners seeking deeper, sustained practical experience. It includes specialization, team workflow, quality assurance and a production-style capstone. Interns gradually take greater ownership while remaining accountable to scope, security, ethics and mentor review.
Month 1 – Foundation: digital literacy, logic, block coding and safe technology use and beginner Python and data representation, baseline tasks and work standards.
Month 2 – Core build: creative problem-solving and project communication plus the first guided project and review cycle.
Month 3 – Applied specialization: Python applications, data analysis and visual stories and age-appropriate machine-learning concepts with an intermediate project.
Month 4 – Integration: chatbot, image or recommendation prototypes and cross-functional workflow, documentation and quality checks.
Expected 6-month evidence: A structured portfolio containing three or more projects, an advanced capstone, documented iterations, mentor reviews, a presentation and a skills matrix. Suggested advanced projects include Image or text classifier with safe data, Supervised AI assistant prototype and Young innovator capstone and demo day.
Skills and Tools
Working Environment
The exact stack may vary by batch and project. Typical tools include Scratch or MakeCode where appropriate, Python, Jupyter or approved notebook, pandas, beginner-friendly visualization tools, scikit-learn with guided templates, safe generative AI tools, GitHub or supervised portfolio platform. Skillonit should publish only the tools that are actually supported in the selected batch and provide setup guidance, access requirements and alternatives where paid licences are involved.
Project Practice
Real client projects are included only when an approved project, permission and review process are available; otherwise learners work on realistic industry simulations or mentor-designed capstones.
Training Support
Workflow
Eligibility
No prior coding is required. Age, reading level, device access and confidence are considered during pathway placement.
Assessment
Evaluation should be transparent and based on evidence rather than vague participation. Recommended criteria include attendance, timely task completion, understanding of the work, quality of implementation, response to feedback, documentation, ethics and final presentation. The certificate should state the program title, duration, completion date and credential ID only when those fields are actually maintained by Skillonit.
Certification and Career
The internship can support preparation for roles such as Young AI Innovator Participant, Student Data Explorer, Junior Coding Project Participant, AI Application Project Learner, School Innovation Portfolio Participant, Supervised Young Researcher. It may also help learners demonstrate practical work for further study, entry-level applications, freelance proposals, startup prototypes or internal role transitions. Outcomes depend on the learner’s starting level, effort, project quality and the requirements of each opportunity; no job, income, client or admission result is guaranteed.
Program Features
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Apply Now
Apply for the AI Young Data Scientist Internship Program and choose the duration that matches your goals. Complete the application form with accurate information so the admissions and mentor team can recommend the appropriate pathway.
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Internship FAQs
Skillonit’s AI Young Data Scientist Internship Program in India is a mentor-guided practical pathway available in 1-month, 3-month and 6-month formats. Participants learn how to help young learners progress from computer basics and logic to coding, Python, data stories, machine learning, responsible AI and their own supervised AI applications. The program combines structured training, assignments, project reviews, documentation, portfolio support and a completion certificate subject to published requirements.
Learners can choose 1 month, 3 months or 6 months. The one-month track is introductory, the three-month track is portfolio-focused, and the six-month track provides deeper project and production-style experience.
Yes, the foundation pathway is designed for learners who meet the basic device and participation requirements. No prior coding is required. Age, reading level, device access and confidence are considered during pathway placement.
Projects may include Interactive coding story or game, Data-story dashboard, Python utility or quiz application, Image or text classifier with safe data. Final projects are selected according to duration, learner level, mentor capacity and available project briefs.
Yes. The program combines concept refreshers, guided exercises and tool setup before independent tasks. Training depth depends on the selected duration and baseline assessment.
The program includes mentor-guided projects. A real client or production project is offered only when a suitable approved opportunity is available; otherwise, the learner completes a realistic industry simulation or internal capstone.
A completion certificate may be issued after the learner meets the published attendance, task, project, evaluation and final-presentation requirements.
A stipend is not automatic. Stipend status must be displayed for each approved opening. A training internship may have a program fee, while a genuine employment internship must be published separately with its own terms.
Online, classroom and hybrid options may be available. The exact mode, schedule and mentor availability should be confirmed for the selected batch.
Yes, subject to eligibility, schedule and mentor capacity. Weekend or evening options may be offered when listed in the active batch information.
No. The program provides practical learning, portfolio evidence and career-readiness support, but employment, freelance income, client allocation and interview results depend on external selection processes.
Select Apply Now, choose the duration and mode, submit accurate education and skill details, and complete any baseline task requested by the internship team.
Yes. No coding knowledge is required.
Students from Class 2nd to 10th.
A laptop is recommended for practical learning.
Yes. Students build multiple AI, Data Science, and Coding projects.
Yes. Python is one of the core technologies taught.
Yes. Students are introduced to Machine Learning concepts and practical applications.
Yes. Students receive the Skillonit Young AI Data Scientist Certification.
Yes. Both Online and Offline learning options are available.
15 Months.
It combines Coding, AI, Machine Learning, Data Science, Innovation, Entrepreneurship, Leadership, and Project-Based Learning into one comprehensive program designed specifically for school students.