Ai Ml & Chatgpt For Cxos & Sr.Managers (With No Code Automl)

Assess maturity for AI readiness | Demystify Artificial Intelligence | 8 Case Studies | Google's No Code Auto ML

What you'll learn

You will get conceptual clarity on AI and its applications including pattern recognition

You will understand the technology behind AI through various concepts and case studies.

You will gain insights on technologies stacking up against AI

You will gain a foothold on machine learning and deep learning, different types of machine learning with examples of machine learning

You will get clarity on Industry 4.0, Smart factory & Predictive maintenance

You will understand the several applications of Artificial Intelligence for Business Leaders (CxOs, Managers, Team Leaders, MBA Students, Entrepreneurs)

You will gain insights on disruption happening in several domains and industries because of Artificial Intelligence and Machine learning

You can apply Artificial Intelligence and Machine Learning in your areas of functions post this course

You will understand Robotic Process Automation(RPA), RPA Applications, Chatbot & you will have a demo on a RPA Solution

You will learn how to use ChatGPT for your business

You will master the art and science of prompt engineering

Requirements

This course does not assume any prior knowledge of Artificial Intelligence or it’s associated terms. Bring your business and managerial experience - the course will help you do the rest !

Description

Updates:. Jan - May 2023: Any discussion on AI now involves a discussion on ChatGPT as well. We have added content related to ChatGPT, prompt engineering, data privacy issues and how to prepare for the ChatGPT era. . Oct 2022: Updated the course with the recent trend in AI - Auto ML (no code machine learning) - How to build machine learning model without writing a single line of codeDemystifying Artificial Intelligence including ML, DL, NLP, Industry 4.0, IoT & RPA with Caselets for CxOs and Senior Managers.AI, AI, AI Everywhere! If you don’t do something about AI, you will be left behind or disrupted into extinction – this is a message that executives, Managers, Team Leaders and CXOs often hear, especially in the last year or so from consultants, vendors, industry experts or the IT organization. But why now? Today, companies are faced with some compelling new choices, like robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), blockchain and Industrial Internet of Things (IIoT), to name a few. Corporate Leaders have the daunting task of deciphering what these buzzwords mean, understanding what is relevant to their business and determining which technology to invest. It’s important that Leaders have a foundational knowledge of digital transformation because they will rely on digital business to make their numbers. It will be hard for Leaders to lead digital initiatives if they don’t understand digital clearly. A lack of understanding can result in misdirection of efforts and painful experiences, and ultimately place the organizational transformation goals in jeopardy.This course presents the concepts and technologies behind AI in a simple manner through examples and case studies. The course begins with an explanation of what is AI and uncovers the technology behind AI. A comparison of AI with other technologies like Big Data, RPA, Cloud and Industry 4.0 is also provided.We will cover the following in this course:What is AI and how it relates to other advanced technologiesWhat is AITypes of AIGoals of AIApplications of AIPattern RecognitionTechnology behind AI:What are machine learning and deep learning?Different types of machine learningExamples of machine learningWhat is driving the rise of AI?Technologies driving the rise of AIWhat is driving the rise of AIStructured Vs Unstructured DataCloudIoTIndustry 4.0IoT and IndustrySmart factoryPredictive maintenanceRobotics Process Automation:What is RPAIs RPA really AIIntelligent AutomationTask Vs Workflow AutomationCase Studies:Fraud DetectionImproving the Forecasting ProcessFace Detection and Social Distancing ManagementIntelligent AutomationAutoMLWhat is Auto ML (No code machine learning)How to predict churn using AutoMLIn general terms, digital transformation can be thought of as integration of digital technology into all areas of a business resulting in fundamental changes to how businesses operate and how they deliver value to their stakeholders (employees, vendors, customers, etc.) to help the organizations compete effectively in an increasingly digital world.In many ways, digital transformation is a misnomer, because digital is not all about technology. Digital transformation is about solving a business problem or developing a new approach where the technology is an enabler and never the driver. It is about how a technology can help a company rethink the way in which it conducts business and change the stakeholders' (customers, vendors, employees) experience, and it’s about adaptation. This sometimes means walking away from longstanding business processes that companies were built upon in favor of relatively new practices that are still being defined. Think Uber, Lyft, Netflix, Airbnb.Another key point to note with digital transformation is that it is not a one and done exercise; rather, it is a mindset, a paradigm shift that allows the organizations to continually improve and ultimately develop a level of digital maturity in order to keep up with the rapidly evolving technological advances.Testimonials:The course was well explained by the instructor. All the concepts were taught in an easily understandable way!~ PriyaGreat course. Gave me a solid foundation and helped to clear up some of my confusion. ~ SPVery Well Explained with real examples !!! ~ SelvapriyaVery informative course and shows reality of science to human life. ~ Reston Kaibela NgosaThe distinction between technologies was explained clearly. Liked the examples. ~ Ravi ShankarBefore this course, I thought AI, RPA and Industry 4.0 are all same. This course clarified these jargon to me. Overall good course. ~ Anupama Sharma

Overview

Section 1: Introduction

Lecture 1 Context Setting

Section 2: Framework to assess Organization's Maturity For Artificial Intelligence

Lecture 2 Framework to assess Organization's Maturity For Artificial Intelligence

Section 3: What is AI?

Lecture 3 Introduction to AI

Section 4: Technology behind AI

Lecture 4 Technology behind AI

Section 5: Technologies driving the rise of AI

Lecture 5 Technologies driving the rise of AI

Section 6: Case Study 1: Insurance Fraud Detection

Lecture 6 Case Study 1: Insurance Fraud Detection

Section 7: Case Study 2: Sales & Supply Chain Demand Planning Analytics

Lecture 7 Case Study 2: Sales & Supply Chain Demand Planning Analytics

Section 8: Case Study 3: Image/Video Analytics & Social Distance Management

Lecture 8 Case Study 3: Image/Video Analytics & Social Distance Management

Section 9: Case Study 4: Outlier or Anomaly Detection

Lecture 9 Case Study 4: Outlier or Anomaly Detection

Section 10: Case Study 5: Customer Segmentation

Lecture 10 Case Study 5: Customer Segmentation

Section 11: Industry 4.0

Lecture 11 Industry 4.0

Section 12: Case Study 6: Predictive Maintenance

Lecture 12 Case Study 6: Predictive Maintenance

Section 13: NLP (Natural Language Processing)

Lecture 13 NLP (Natural Language Processing)

Section 14: Case Study 7: Speech to Text

Lecture 14 Case Study 7: Speech to Text

Section 15: RPA

Lecture 15 RPA

Lecture 16 Intelligent Automation

Lecture 17 Task Vs Workflow Automation

Section 16: Case Study 8: Intelligent Automation

Lecture 18 Case Study 8: Intelligent Automation

Section 17: Challenges in AI and RPA deployments

Lecture 19 Challenges in AI and RPA deployments

Section 18: Machine Learning Concepts and AutoML

Lecture 20 What is AutoML

Lecture 21 Introduction to Google Cloud's Vertex AI

Lecture 22 Dependent Vs Independent Variable

Lecture 23 Regression and Classification Concepts

Lecture 24 Accuracy in Classification and Regression

Lecture 25 Developing and deploying churn prediction model in Vertex AI

Section 19: ChatGPT

Lecture 26 Understanding ChatGPT

Lecture 27 What are LLM's and Generative AI?

Lecture 28 Creating An Elevator Speech

Lecture 29 Build An ML Model Using ChatGPT

Lecture 30 Prompt Engineering

Lecture 31 Prompt Engineering in Action

Lecture 32 Did you notice?

Lecture 33 Preparing for a world with ChatGPT

Lecture 34 Data Privacy for the ChatGPT World

Section 20: Conclusion

Lecture 35 Conclusion

Section 21: Quiz

Section 22: Bonus Lecture

Lecture 36 Bonus Lecture

Executives, CXOs, Managers, Technologists and Students,Any one interested in understanding and applying these technologies for business use