Assess your organization maturity for AI readiness | Demystifying Artificial Intelligence | Eight Case Studies
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<This course covers concepts & case studies for executives and senior managers to better understand AI. This course doesn't cover programming aspects of AI>
Demystifying 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 technologies
What is AI
Types of AI
Goals of AI
Applications of AI
Pattern Recognition
Technology behind AI:
What are machine learning and deep learning?
Different types of machine learning
Examples of machine learning
What is driving the rise of AI?
Technologies driving the rise of AI
What is driving the rise of AI
Structured Vs Unstructured Data
Cloud
IoT
Industry 4.0
IoT and Industry
Smart factory
Predictive maintenance
Robotics Process Automation:
What is RPA
Is RPA really AI
Intelligent Automation
Task Vs Workflow Automation
Case Studies:
Fraud Detection
Improving the Forecasting Process
Face Detection and Social Distancing Management
Intelligent Automation
In 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.
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