Artificial Intelligence

SUMMARY: We are confident that the prospective children will empower themselves in the future to come and will understand key concepts underlying this new technology- AI. What is AI? This unit will lay down the foundations of AI by discussing its history and setting ground for forthcoming units.

SUMMARY: This unit will take you through the cognitive computing aspect of AI by introducing you to terms like Computer Vision, speech, reasoning, etc. Which otherwise is considered to be the attributes of humans.

SUMMARY: Artificial Intelligence (AI) and Machine Learning (ML) are built on mathematics like Calculus, Linear Algebra, Probability, Statistics, Algorithms and Complex Optimizations. This unit aims to help students learn the foundation concepts of mathematics which will be utilized in AI and ML.

SUMMARY: The current advances in research and development in the space of AI have given rise also to challenges of various kinds – ethical challenges, jobs being taken by robots, the value system of robots, privacy in the age of AI etc.

SUMMARY: Students get to learn about the significance of storytelling which has been used as a medium to pass on knowledge, experience, and information for ages. It also builds intercultural understanding and commonalities thereof. This session will also equip students with a vital skill to tell back their stories with numbers or proof points by blending the two worlds of hard data and human communication. Data visualization is now a key to interpreting and tell an impactful story.

SUMMARY: We are living in a rapidly changing complex world characterized by learning, unlearning , and relearning which happens to be the new normal. 85% of the future jobs have either not been visualized or invented yet. So, how can we prepare our children for a future full of uncertainty and dramatic changes? Of the 10 skills expected to be in high demand in the future, World Economic The forum lists complex problem solving, critical thinking, and creativity as the top three skills for future employment.

SUMMARY: In the AI age, where data is the new electricity, students need to know how to use, analyze and communicate data effectively. Data Analysis should not be limited to mathematics, statistics or economics, but should be a cross-curriculum concept. Institutions like the World Bank to entities like the local government, and organizations are becoming increasingly open about the information that they gather and are ready to share the same with the public. Those who know how to analyse and interpret data, can crunch those numbers to make predictions, identify patterns, explain historical trends, or find fault in arguments. Students who become data literate are better equipped to make sense of the information that’s all around them so that they can support their arguments with reliable evidence. Statistics is the science of data and its interpretation. In other words, statistics is a way to understand the data that is collected about us and the world; therefore, a basic understanding of statistics is important. There are statistics all around us – news, scientific observations, sports, medicine, populations, and demographics. Understanding statistics is essential to understanding research in the social sciences, science, medicine and behavioral sciences. In this unit you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This module will also prepare you for the next unit of this Level-II.

SUMMARY: Building machine learning (ML) models has traditionally required a binary choice. On one hand, you could manually prepare the features, select the algorithm, and optimize the model parameters in order to have full control over the model design and understand all the thought that went into creating it. However, this approach requires deep understanding of many ML concepts / algorithms and classification is one of them.

SUMMARY: AI is progressing towards a stage where eventually it will replicate human general intelligence. The possibility of making a thinking machine raises a host of ethical issues. These ethical questions ensure that such machines do not harm humans and the society at large. To harness the potential of AI in the right way, guidelines and ethical standards are therefore required. As a result, ethical guidelines have been developed in recent years and developers are expected to adhere to these principles. In spite of the standards, collectively as a society we have to face the challenges arising from current AI techniques and implementations, in the form of a systematic decrease in privacy; increasing reliance on AI for our safety, and the ongoing job losses due to mechanization and automatic control of work processes.