“This mission is for the benefit of children with curious minds to whom the future belongs.” It is part of the mission of “ Coming of Age in the 4th Industrial Age”.
The purpose of this program is twofold: one to introduce the young to the emerging field of Artificial Intelligence and Machine Learning and the other to guide them to become more aware self-learners who can continue to learn more about the field. The teaching-learning model is a combination of Flipped Learning and heutagogy with the goal of ‘playful exploration’ of the field.
We have developed a list of 24 modules, structured as 6 groups/clusters) with 4 modules each; and one week devoted to each module. In all a 6 months program delivered several times a year, with the first cohort from July 2019 to December 2019 and then a fresh cohort every month from August 2019 onwards.
This is an intensive academic program that a student covers in 24 weeks and is meant for high ability and highly motivated learners. Not meant for the faint hearted struggling with the regular mandated course load.
Teaching coding ( in Python) is not included here as there is already a course dedicated to this in the CBSE curriculum.
Course: Learning to Learn AI
This course consists of 6 clusters , each comprising 4 modules . Each module is further divided into 5 units, each unit being structured as 5 topics. A nested decimal system is followed in coding the content.
Cluster 1: Foundations:
Module 1.1: Why Learn AI
Module 1.2: Smart Learning
Module 1.3: Computational Thinking
Module 1.4: AI and the future of work in the Gig economy
Cluster 2: The Landscape of AI
Module 2.1: The Turing test: Meaning of narrow AI and AGI
Module 2.2: Swarm Intelligence
Module 2.3: Rule based expert systems
Module 2.4: Other technologies: IoT, 3D Printing, Blockchain, AR and VR
Cluster 3: Mathematics for AI/ML:
Module 3.1: Mathematical Modelling
Module 3.2: Linear Algebra
Module 3.3: Calculus for Machine Learning
Module 3.4: Bayesian Machine Learning
Cluster 4: Machine Learning Basics:
Module 4.1: Learning algorithms
Module 4.2: Decision Tree Learning
Module 4.3: Classification
Module 4.4: Regression
Cluster 5: Deep Learning:
Module 5.1: Neural Networks
Module 5.2: Basics of Neuroscience
Module 5.3: Artificial Neural Networks
Module 5.4: A survey of current applications of Deep Learning and future trends
Cluster 6: AI applications:
Module 6.1: Image and Object recognition and manipulation
Module 6.2: Speech generation and recognition : chatbots
Module 6.3: Recommendation Engines and Predictive Models : fake news
Module 6.4: AI and ethics