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What is Artificial Intelligence? by Simplilearn is an introduction to artificial intelligence that deals with the fundamentals of artificial intelligence and its critical technicalities. Artificial Intelligence In five Minutes tutorial video will help you enhance your knowledge of Artificial Intelligence. This video on AI Explained by Simplilearn covers the most Critical AI Concepts in the simplest ways.
00:00:00 Introduction to What is AI? This video segment on what is AI? will cover the briefing on Artificial Intelligence.
00:00:30 What is AI? This section of the What is AI? video will give the technical definition of AI.
00:00:57 Types of AI This section of the What is AI? video will cover the types of AI available in the industry.
00:01:46 Machine learning and Deep learning This section of the What is AI? video will cover the aspects of machine learning and deep learning in detail.
00:02:30 Deep Learning and NLP This section of the What is AI? video will cover the aspects of Deep Learning and NLP in detail.
00:02:45 AI in different fields This section of the What is AI? video will cover the various fields where AI is currently operational.
00:03:30 Salary of AI engineer This section of the What is AI? video will cover the salary details of AI engineers.
00:03:48 Quiz on What is AI? This section of the What is AI? video will have a quick and simple quiz question on AI.
✅ About Artificial Intelligence Engineer Master's Program:
✅ What skills are covered in this Artificial Intelligence course?
You will be able to demonstrate the following ability after completing this Artificial Intelligence certification training:
- Learn Artificial Intelligence's concept, purpose, domain breadth, phases, implementations, and impacts. - Create real-world projects, games, prediction models, logic constraint satisfaction concerns, experience and understanding systems, probabilistic models, and agent decision-making skills using your artificial intelligent machines and models. - Learn how to develop your Python programs and use the Jupyter notebook to analyze fundamental data. - Learn about data wrangling, data exploration, data visualization, hypothesis creation, and testing procedures in Data Science. - Use the NumPy and SciPy packages for high-level mathematical and technical computing and the Pandas package for data analysis. - Learn about supervised and unsupervised learning methods such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipeline, recommendation engines, and time series modeling. - Understand TensorFlow's core principles, functions, operations, and execution pipeline. - CNN, artificial neural networks, training deep RNN networks, and high-level NLP interfaces are among the advanced issues in AI.
