There is a lot of excitement around AI, but what is it and how could it be relevant to your career? Watch these videos to learn the basics of AI and Machine Learning.

Artificial Intelligence

In this video we will outline the AI life cycle and its elements. The AI lifecycle can be thought of in three stages - project scope, building the model, and deploying it to production. The six steps in the typical data science and AI process are explained, including asking the right questions, conducting research, choosing appropriate methods, validating assumptions, testing, and interpreting conclusions. Deployment of machine learning models is discussed, including considerations for when to deploy and different methods of deployment such as on-call systems, on-demand systems, and on-edge systems.

Artificial Intelligence (AI) Lifecycle

In this video, we'll explain how artificial intelligence works and identify the types of data that are used with AI. AI works by using large amounts of data, processing it iteratively with intelligent algorithms to learn from patterns or features in the data. It's important to use valid data and correct biases. Data can be classified into four major groups: structured, semi-structured, quasi-structured, and unstructured. Structured data is organized in tables, like in Microsoft Excel, and is easy to manipulate. Semi-structured data is labeled but not in table format, allowing for more versatility. Quasi-structured data has some patterns but lacks clear labels or structure, requiring more formatting. Unstructured data, like videos, podcasts, and pictures, lacks any pre-defined format. Big data is characterized by high volume (in terabytes, petabytes, or exabytes), high velocity (flowing rapidly from sources), and high variety (coming from different formats and sources).

How Does Artificial Intelligence (AI) Work?

In this video, we identify use cases for AI and how AI can be used in your industry. What AI can do can be broken up into six broad categories - Finding a needle in a haystack, prioritizing work to maximize impact, providing early warnings or detection against imminent threats, speeding up decisions and the decision-making process, optimizing the resources that you have available to you and enabling experiments to determine the best course of action.

What Can Artificial Intelligence (AI) Do?

In this video, we will identify the concepts and use cases for artificial intelligence (AI). Artificial intelligence (AI) provides cutting-edge tools to help organizations predict behaviors, identify key patterns, and drive decision-making in a world that is increasingly made up of data. It is the science of creating intelligent systems that can learn and solve tasks that typically require human intelligence. 

Examples of widely used AI-powered products include Netflix's recommendation engine, Google's search engine, and voice assistants like Siri and Alexa. The use of AI has increased significantly in recent years due to the collection of more data and increased computing power. Many business leaders believe AI will be the key to optimizing efficiency, improving productivity, and fostering innovation. However, it's important to understand that AI is not alive, sentient, creative, or ambitious. Its purpose and existence are defined by humans, and it requires human interpretation to provide the right context for its calculations.

What is Artificial Intelligence?

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