Course Description

The abbreviation Artificial Intelligence (AI) has been named the Collins Word of the Year for 2023, the dictionary publisher said on 31st October 2023. "AI for All" is a meticulously crafted educational program tailored for individuals new to the field of AI but passionate about learning. This comprehensive course provides beginner-friendly training, introducing learners to fundamental concepts and terminology in Artificial Intelligence, Machine Learning, Data Science, Deep Learning, and AI Tools.

Objectives

The program addresses important considerations like avoiding pitfalls and guides participants on their journey to undertaking AI projects and fostering effective team building.

Audience

AI is no longer limited to just engineers. The course "AI for All" offers a non-technical approach, focusing on enabling individuals to comprehend AI technologies and identify opportunities to apply AI within their own organizations. The course illustrates real-life examples to showcase the current capabilities and limitations of AI. Furthermore, participants will gain insights into the impact of AI on society and learn how to navigate through this technological revolution.
For non-technical business professionals, "AI for All" helps in devising a sustainable AI strategy. On the other hand, if you are a machine learning engineer or data scientist, this course is designed specifically for you to encourage your manager, VP, or CEO to gain a comprehensive understanding of what you can achieve (and what you cannot) with AI.

Prerequisites

This program is not only engineers but for anyone from diverse backgrounds who aspire to develop their careers in AI or enhance their organization's utilization of AI technologies.

Content

1. Introduction to AI
a. What is Artificial Intelligence
b. Brief History of AI
c. Types of AI
d. Applications of AI

2. Major Components of AI
a. Machine Learning
a.1. What is Learning
a.2. Why do we need Machine Learning?
a.3. Types of learning
a.4. Relations to other fields
b. What machine learning can and cannot do

3. Principles of AI
a. The Data
b. The Algorithms

4. Fields of AI
b. NLP
c. Robotics
d. Computer Vision

5. Neural Networks and Deep Learning
a. Artificial Neural Networks
b. What’s Deep Learning all about
c. Understanding images
d. non-technical explanation of Deep Learning

6. The Projects of AI
a. Recognise Machine Learning Project
b. Workflow of Data Science
c. Example of an AI project

7. Where you will Fit
a. Framing an AI team
b. Example role of an AI team
b. Tools useful for AI teams

8. AI and It’s Culture
a. Partnering with AI
b. AI pitfalls to avoid
c. Fear of AI

9. AI and It’s Community
a. Civilization view of AI
b. Discrimination/Bias
c. Our Role in Different stage of AI

10. AI momentum
a. Success Stories of AI in India and other parts of the world
b. Jobs you can look out for