AI for Educators: From Fundamentals to Generative AI
Type: FDP
AI for Educators
From Fundamentals to Generative AI
Specially designed to empower educators with practical, future-ready Artificial Intelligence skills.
About the FDP
Artificial Intelligence is rapidly transforming education, research, content creation, productivity, and professional workflows. This International Level Faculty Development Program is designed to introduce educators to AI in a simple, practical, and structured manner.
Starting from foundational AI concepts, participants will gradually explore Python, Data Analytics, Machine Learning, Computer Vision, Deep Learning, Generative AI, Large Language Models, RAG, and Agentic Intelligence.
Programme Details
Dates
7th September – 11th September 2026
Daily Sessions
1 Hour Per Day
Live Interactive Sessions
Mode
Online
Faculty-Friendly Learning
Programme Highlights
Python Foundations
Build a foundation in Python programming and understand how it supports AI and Data Science.
Data Analytics
Learn how data can be cleaned, analysed, visualised, and converted into useful insights.
Machine Learning
Understand predictive intelligence, supervised learning, models, and evaluation.
Computer Vision
Explore image processing and understand how computers analyse visual information.
Deep Learning
Discover neural networks and their role in modern intelligent applications.
Generative & Agentic AI
Explore LLMs, RAG, Generative AI, and the future of AI-powered agents.
Course Objectives
- Introduce Artificial Intelligence from the fundamentals.
- Develop basic Python programming skills for AI applications.
- Understand data analytics and data-driven decision making.
- Introduce Machine Learning concepts and predictive intelligence.
- Explore Computer Vision and Deep Learning fundamentals.
- Understand Generative AI and Large Language Models.
- Introduce Retrieval-Augmented Generation and Agentic AI.
- Demonstrate practical AI applications relevant to education.
Why Learn AI as an Educator?
- Use AI tools to improve teaching and classroom productivity.
- Create educational content more efficiently.
- Explore AI-assisted research and academic workflows.
- Understand emerging technologies students are expected to learn.
- Discover practical AI applications across academic disciplines.
- Stay updated with Generative AI and emerging AI trends.
- Develop confidence to introduce AI concepts into teaching.
- Identify opportunities for AI-based projects and research.
Day-wise Syllabus
Day 1 — Python Foundations for AI & Data Science
- Introduction to Python and why Python is widely used in AI and Data Science
- Python variables, data types, operators, and basic syntax
- Working with strings, numbers, lists, tuples, dictionaries, and sets
- Conditional statements and decision-making in Python
- Loops and repetitive operations using practical examples
- Functions and reusable blocks of Python code
- Introduction to Python libraries and packages
- Introduction to NumPy and its role in data processing
- Understanding Python notebooks and interactive coding
- Hands-on Python exercises related to AI and education
Day 2 — Data Analytics: From Data to Insights
- Understanding data, datasets, features, records, and variables
- Introduction to data collection and different data types
- Introduction to Pandas and DataFrame operations
- Loading CSV and structured datasets
- Exploring datasets using head, tail, info, describe, and related operations
- Identifying and handling missing data
- Data cleaning and basic preprocessing
- Introduction to data visualisation using charts
- Understanding patterns and extracting meaningful insights
- Hands-on dataset analysis using Python
Day 3 — Machine Learning Essentials
- What is Machine Learning and why it matters
- Difference between Artificial Intelligence, Machine Learning, and Deep Learning
- Supervised and Unsupervised Learning concepts
- Understanding features, labels, training data, and testing data
- Introduction to Linear Regression
- Introduction to Classification and Logistic Regression
- Basic model training workflow
- Understanding prediction and model evaluation
- Real-world Machine Learning applications
- Hands-on Machine Learning project demonstration
Day 4 — Computer Vision & Deep Learning Foundations
- Understanding images as data
- Introduction to Computer Vision
- Image properties, pixels, channels, and image formats
- Introduction to Image Processing techniques
- Image reading, resizing, conversion, and basic transformations
- Introduction to OpenCV and practical image operations
- What is Deep Learning and how it differs from traditional Machine Learning
- Neural networks, neurons, layers, and activation concepts
- Introduction to CNNs and image classification
- Mini Computer Vision / Deep Learning demonstration
Day 5 — Deep Learning, Generative AI & Agentic Intelligence
- Deep Learning concepts and practical applications
- Introduction to Generative Artificial Intelligence
- Understanding Large Language Models and their applications
- Introduction to prompt engineering and effective AI interaction
- Understanding Retrieval-Augmented Generation (RAG)
- How AI systems can search information and generate contextual responses
- Introduction to Agentic AI and intelligent task automation
- Understanding AI agents, tools, memory, and workflows
- Educational and research applications of Generative and Agentic AI
- Guided practical demonstration of modern AI applications
Hands-on Activities
Tools & Technologies
Learning Outcomes
Strong AI Foundation
Understand AI, Machine Learning, Deep Learning, Generative AI, and emerging intelligent technologies.
Practical Python Skills
Gain foundational Python skills for AI, Data Analytics, and practical experimentation.
AI for Teaching
Identify ways AI tools can support classroom teaching, content development, and academic productivity.
AI for Research
Explore opportunities for AI-assisted research, data analysis, experimentation, and innovation.
Generative AI Awareness
Understand LLMs, prompting, RAG, and modern Generative AI workflows.
Future-Ready Skills
Develop the confidence to continue exploring advanced AI and intelligent systems.
Who Can Attend?
- Faculty Members
- Academicians
- Research Scholars
- Industry Professionals
- Educators from Any Discipline
- Anyone Interested in AI
No Prior AI Experience Required
No prerequisites are required. The FDP is designed to begin from the fundamentals, making it suitable even for participants who are completely new to Artificial Intelligence. Basic computer familiarity may be helpful, but prior knowledge of AI, Machine Learning, Deep Learning, or Generative AI is not required.
E-Certificate Requirements
Participants must fulfil the FDP participation requirements to receive the certificate.
5-Day Attendance is Compulsory
Participants must attend all five FDP sessions to be eligible for the certificate.
Daily Quiz Participation is Compulsory
Participants are required to attend and complete the scheduled daily quizzes.
Empower Your Teaching with AI
Learn the technology. Explore the possibilities. Bring AI into your teaching, research, and academic journey.
5 Days • 5 Power-Packed Sessions • Zero Registration Fee
Join the FDPLet's Empower Educators with AI
AI is not replacing educators — it is giving educators new ways to teach, create, research, and inspire.