National Education Technology Board Recruitment 2026: 150 Data & AI in Education Specialist Vacancies Open – Apply Now! Syllabus Breakdown Available here !
Are you passionate about leveraging cutting-edge technology to transform India’s education landscape? The National Education Technology Board (NETB) has announced the Latest Job Notification for 150 positions of Data & AI in Education Specialist.
This Govt Jobs 2026 opening is aligned with the revolution of data-driven education, offering you a chance to shape the future of learning while securing a prestigious Sarkari Naukri Result.
Quick Info: NETB Recruitment 2026
| Organization | Post Name | Total Vacancy | Last Date | Official Website |
| National Education Technology Board | Data & AI in Education Specialist | 150 | October 15, 2026 | www.netb.gov.in |
Eligibility & Selection Criteria
To be part of this technological leap in Indian classrooms, candidates must meet the following benchmarks:
I. Eligibility Requirements
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Educational Qualification: Bachelor’s or Master’s degree in Computer Science, Data Science, Education Technology, or Statistics.
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Core Skills: Strong grasp of Data Analytics, Machine Learning, and AI applications in the education sector.
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Age Limit: 21 to 30 years (as of Jan 1, 2026). Relaxations apply for SC/ST/OBC and other reserved categories per Govt norms.
II. Selection Process
The recruitment follows a rigorous two-stage process:
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Written Examination: Assessing General Aptitude, Reasoning, English, and specialized technical knowledge in AI & Data Science.
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Personal Interview: A deep dive into technical expertise, problem-solving skills, and your vision for integrating AI into India’s educational framework.
How to Apply Online: Step-by-Step
Candidates must apply before the Last Date (October 15, 2026). Follow these steps:
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Official Portal: Visit www.netb.gov.in and go to the ‘Career’ section.
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Registration: Click the application link and register with a valid email and mobile number.
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Form Filling: Enter accurate personal, educational, and experience details.
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Uploads: Provide scanned copies of your photograph, signature, and certificates per specifications.
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Payment: Remit the application fee through the online payment gateway.
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Final Review: Double-check all information before clicking Submit.
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Documentation: Download and print the confirmation page for your records.
Preparation Tip
Here is a sample syllabus breakdown for the Data & AI in Education Specialist exam.
Module 1: Data Science & Analytics in Education
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Learning Analytics: Tracking student progress using Predictive Modeling; identifying “at-risk” students; analyzing engagement metrics in Virtual Learning Environments (VLEs).
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Big Data in Education: Handling large-scale datasets from platforms like DIKSHA and SWAYAM; data cleaning, normalization, and handling missing values.
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Data Visualization: Principles of creating intuitive dashboards for teachers and administrators using tools like Tableau, PowerBI, or Python libraries (Matplotlib, Seaborn).
Module 2: Artificial Intelligence & Machine Learning (Core)
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Supervised Learning: Regression and Classification models for predicting student performance.
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Unsupervised Learning: Clustering algorithms (K-Means) for segmenting students based on learning styles or pace.
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Natural Language Processing (NLP): Automated essay grading; sentiment analysis of student feedback; multilingual translation bots for regional languages.
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Recommender Systems: Content-based and collaborative filtering for suggesting personalized study material.
Module 3: Adaptive Learning & EdTech Frameworks
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Intelligent Tutoring Systems (ITS): Knowledge tracing models (Bayesian Knowledge Tracing); scaffolding techniques in AI.
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Personalized Learning Paths: Algorithms that adjust content difficulty in real-time based on learner responses.
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Gamification Tech: Using AI to manage rewards, badges, and competitive leaderboards in educational apps.
Module 4: Ethics, Privacy & Governance
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Data Privacy: Understanding DPDP (Digital Personal Data Protection) Act 2023; protecting student identity (Anonymization/Pseudonymization).
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AI Ethics: Addressing algorithmic bias (ensuring AI doesn’t discriminate based on gender, caste, or geography).
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National Education Policy (NEP) 2020: Foundational knowledge of digital initiatives mentioned in the NEP (NETF – National Educational Technology Forum).
Exam Weightage Distribution (Estimated)
| Topic Area | Weightage (%) |
| Data Science & Statistics | 30% |
| Machine Learning & NLP | 35% |
| Adaptive Learning Tech | 20% |
| Ethics & Policy (NEP 2020) | 15% |
Recommended Quick-Start Topics
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Python for Data Science: Libraries like Pandas, NumPy, and Scikit-learn.
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SQL for Data Retrieval: Ability to query educational databases.
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Basic Statistics: Probability distributions, Hypothesis testing (p-values, T-tests).
