AI4All:

AI4All:

A one month program for all:

Fee: Rs 2500/- + taxes

This course will be made  free for women on Women’s day ( 8th March 2019) /18th March 2019. Free for 250 women every month.

Like what the PM said for many other subsidies, we will hope that those who can afford this modest fee should join courses as fee paying students. Thus more women who are challenged in affording this fee can become AI aware.

Every month we will offer the program to 1000 students, in 4 concurrent Whatsapp groups. Those who have fee-waiver will not be identifiable within the groups. 

Everyone who reads/ or views all the posts and performs and submits the tasks assigned ( there will be 5 such tasks, one for each module and one Capstone Project that may draw upon the learning of all the 4 modules) will be given a certificate from LMP Education Trust. 

There are 4 modules in this program :

Module 1: What is all the excitement about AI?

Module 2: How does it work? 

Module 3: The nuts and bolts of AI

Module 4: AI for human well being 

Each module is transacted over a week ( 5 days)

There are 5 posts every day

Each post can be perused in about 15 to 18 minutes; it is therefore a 25  to 30  hour program 

Module 1: What is all the excitement about AI?

Unit 1: Why Learn AI? 

Topic 1.1.1: A fast forward of the history of AI 

Topic 1.1.2: School students 

Topic 1.1.3: College and University students 

Topic 1.1.4: Lifelong Learners

Topic 1.1.5: The future of work 

Unit 2: What can AI do today? 

Topic 1.2.1: Classification

Topic 1.2.2: Prediction

Topic 1.2.3: Pattern Recognition 

Topic 1.2.4: Anomaly Detection 

Topic 1.2.5: AI can teach itself 

Unit 3: The AI Landscape

Topic 1.3.1: The Turing Machine

Topic 1.3.2: Rule Based Expert Systems 

Topic 1.3.3: Swarm Intelligence

Topic 1.3.4: Relationships between sub-fields of AI

Topic 1.3.5: Narrow Intelligence and Artificial General Intelligence 

Unit 4: Other allied Technologies 

Topic 1.4.1: Sensor Technologies

Topic 1.4.2: 3 D Printing

Topic 1.4.3: Internet of Things 

Topic 1.4.4: Blockchain

Topic 1.4.5: Augmented and Virtual Reality

Unit 5: Mathematics for Artificial Intelligence and Machine Learning 

Topic 1.5.1: A survey of Maths needed for AI/ML 

Topic 1.5.2: Linear Algebra

Topic 1.5.3: Calculus

Topic 1.5.4: Statistics/ Probability 

Topic 1.5.5: Optimisation

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Module 2: How does it work? 

Unit 1: What are Learning Algorithms? 

Topic 2.1.1: What is a traditional algorithm? 

Topic 2.1.2: Features of an algorithm 

Topic 2.1.3: What is a learning algorithm? 

Topic 2.1.4: Types of learning algorithms 

Topic 2.1.5: Examples of learning algorithms 

Unit 2: Machine Learning 

Topic 2.2.1: What is Machine Learning?

Topic 2.2.2: How does it work?

Topic 2.2.3: Machine Learning Examples

Topic 2.2.4: How will you do it? What do you need?

Topic 2.2.5: Bayesian Machine Learning 

Unit  3: Deep Learning 

Topic 2.3.1: What is Deep Learning?

Topic 2.3.2: Multilayer Perceptron Networks

Topic 2.3.3: Supervised, Unsupervised, reinforcement and transfer learning

Topic 2.3.4: Long Short-term memory

Topic 2.3.5: Recurrent Neural Networks

Unit 4: Artificial Neural Networks 

Topic 2.4.1: The Single Perceptron

Topic 2.4.2: What is a Neural Network?

Topic 2.4.3: Types of Neural Networks 

Topic 2.4.4: Training of Neural Networks 

Topic 2.4.5: Convolutional Neural Networks 

Unit 5: Challenges to and Limitations of Machine Learning 

Topic 2.5.1: Quality issues

Topic 2.5.2: Wrong models

Topic 2.5.3: Overfitting the training data

Topic 2.5.4: When Machine learnung algorithms fall short?

Topic 2.5.5: Interpretability of Machine Learning Results 

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Module 3: The nuts and bolts of AI

Unit 1: Classifiers

Topic 3.1.1: What are classifiers?

Topic 3.1.2: Who uses them?

Topic 3.1.3: How do they work? 

Topic 3.1.4: Spam filters 

Topic 3.1.5: Identifying fake news 

Unit 2: Predictor Systems

Topic 3.2.1: How do they work? Stages 

Topic 3.2.2: Data collection ( data mining) and data analysis

Topic 3.2.3: Statistical analysis and predictive modelling

Topic 3.2.4: Predictive model deployment

Topic 3.2.5: AI powered predictive systems : examples

Unit 3: Speech Recognition 

Topic 3.3.1: Challenges to Speech recognition 

Topic 3.3.2: Speaker identification 

Topic 3.3.3: Leading providers of voice based technology 

Topic 3.3.4: Benefits of voice-based mobile Apps

Topic 3.3.5: Challenges faced in integrating voice capabilities 

Unit 4: Image Recognition 

Topic 3.4.1: What is image recognition?

Topic 3.4.2: The challenges to image recognition 

Topic 3.4.3: Face recognition

Topic 3.4.4: Other Applications 

Topic 3.4.5: Privacy concerns

Unit 5: Chatbots

Topic 3.5.1: What are chatbots?

Topic 3.5.2: A Taxonomy of Chatbots 

Topic 3.5.3: Tools for developing chatbots 

Topic 3.5.4: Challenges 

Topic 3.5.5: Deployment

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Module 4: AI for human well being 

Unit 1: AI for healthcare

Topic 4.1.1: MYCIN: an early use example of AI in medicine 

Topic 4.1.2: Drivers of AI in healthcare

Topic 4.1.3: AI and Medical Imaging

Topic 4.1.4: Health Monitoring 

Topic 4.1.5: Precision Medicine 

Unit 2: AI in agriculture 

Topic 4.2.1: The potential of AI applications in Agriculture 

Topic 4.2.2: Drivers of AI in agriculture 

Topic 4.2.3: Drone based solutions in agriculture 

Topic 4.2.4: Indian AgriTech Startups

Topic 4.2.5: Precision Agriculture : more crop per drop

Unit 3: AI in School Education

Topic 4.3.1: The challenges of School Education 

Topic 4.3.2: What do teachers and learners do in class

Topic 4.3.3: How can AI empower teachers 

Topic 4.3.4: How can Al empower learners 

Topic 4.3.5: The impact of AI on examinations

Unit 4: AI in research and higher education

Topic 4.4.1: How does AI empower research? 

Topic 4.4.2: How to be a self-learner? 

Topic 4.4.3: The self-Learning journey for Machine Learning 

Topic 4.4.4: MOOCs for learning AI and Machine Learning 

Topic 4.4.5: Resources for the self learners pursuing AI/ML

Unit 5: AI in human happiness  

Topic 4.5.1: Human dystopia created by AI

Topic 4.5.2: Woebot for mindfulness thru CBT

Topic 4.5.3: Robots for the elderly 

Topic 4.5.4: Social Companion Robots

Topic 4.5.5: AI and ethics