Free AI Courses from the Education Ministry: What Educators Need to Know
The Ministry of Education is offering a set of free AI and data science courses on the SWAYAM portal. They're built for real classrooms and labs-hands-on tasks, case studies, and projects you can use with students right away. Certification is provided on completion.
Whether you teach science, commerce, or run a school, this is a practical way to upskill without budget friction. You'll learn how to apply AI tools responsibly, improve assessment, and use data to drive better learning outcomes.
Course lineup at a glance
- AI/ML Using Python - Core AI and machine learning concepts using Python, with data visualization, linear algebra, statistics, and optimization.
- Cricket Analytics with AI - Sports analytics using Python: data collection, preparation, strike rates, BASRA index, and visualizing player and match performance.
- AI for Educators - Practical ways to integrate AI into pedagogy, assessment, personalization, and classroom productivity.
- AI in Physics - Apply machine learning and neural networks to experimental physics problems and simulations.
- AI in Chemistry - Use AI for molecular prediction, reaction modeling, and early-stage drug design with real datasets.
- AI in Accounting - Automation, fraud detection, forecasting, and data-driven decisions in finance and accounting.
Who should take what
- AI for Educators - Teachers, instructional designers, school leaders. Outcome: stronger lesson design, faster feedback loops, and smarter grading workflows.
- AI/ML Using Python - CS teachers, senior students, and edtech teams. Outcome: solid Python-based ML basics you can turn into capstone projects.
- AI in Physics - Physics faculty and lab instructors. Outcome: model real experiments, analyze signals, and simulate systems with ML.
- AI in Chemistry - Chemistry faculty and UG students. Outcome: work with datasets for prediction and reaction pathways.
- AI in Accounting - Commerce faculty and finance instructors. Outcome: build simple pipelines for anomaly checks and forecasts.
- Cricket Analytics with AI - Sports teachers, club coaches, and data clubs. Outcome: real sports datasets that keep students engaged while learning Python.
What you'll learn across courses
- Data handling: collection, cleaning, visualization, and basic statistics.
- Machine learning foundations: supervised/unsupervised methods and evaluation.
- Python workflows: notebooks, libraries, and reproducible analysis.
- Domain-specific modeling: physics signals, chemical structures, financial ledgers, and sports metrics.
- Responsible use: bias awareness, privacy basics, and transparent reporting.
How to enroll
- Visit the SWAYAM portal.
- Search the course title (e.g., "AI for Educators" or "AI/ML Using Python").
- Check prerequisites (basic Python helps for the technical tracks) and review the schedule.
- Enroll, block time on your calendar, and plan one applied activity per week for your class.
Tips to make it stick in your classroom
- Start small: one dataset, one model, one reflective discussion.
- Co-teach: pair a subject teacher with a CS teacher for stronger outcomes.
- Document as you go: build a shared folder of prompts, rubrics, and datasets for your department.
- Assess with evidence: require a short report with visuals and model limits clearly stated.
Certification and workload
Each course is free and offers a certificate on completion. Expect weekly video lessons, readings, and practical exercises you can adapt for your learners. If you're new to Python, begin with "AI for Educators," then move into the technical tracks with short practice sessions twice a week.
This initiative supports the government's push to build AI fluency across sectors including education, science, sports, and finance. For official details and updates, check the Ministry of Education and enroll on the SWAYAM portal.
Bonus resource
If you're mapping AI learning to job roles in your institution, explore curated picks by role here: AI courses by job.
Your membership also unlocks:
