Artificial Intelligence for Beginners

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About the Artificial Intelligence for Beginners Course

The Artificial Intelligence for beginners course will give you an overview of AI concepts and workflows, machine learning, deep learning, and performance metrics. Also, you will learn the difference between supervised, unsupervised, and reinforcement learning, So be exposed to use cases and see how clustering and classification algorithms help identify AI business applications.

What is Artificial Intelligence?

In simple words, Artificial intelligence (AI) is the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term applied to any machine that exhibits traits associated with a human mind, such as learning and problem-solving.

Artificial intelligence’s ideal characteristic is its ability to rationalize and take actions that have the best chance of achieving a specific goal.

“Everything we love about civilization is a product of intelligence, so amplifying our human intelligence with artificial intelligence has the potential of helping civilization flourish like never before – as long as we manage to keep the technology beneficial”.

–Max Tegmark, President of the Future of Life Institute

Applications of Artificial Intelligence

Artificial intelligence has endless applications in many different sectors and industries. AI is being tested and used in the healthcare industry for dosing drugs and additional treatment methods in patients and for surgical procedures in the operating room.

Other examples of machines with artificial intelligence include computers that play chess and self-driving cars. In chess, the end result is winning the game. For self-driving cars, the computer system must account for all external data and compute it to act in a way that prevents a collision.

Artificial intelligence also has applications in the financial industry. It detects and flags banking and finance activity, such as unusual debit card usage and large account deposits, all of which helps in a bank’s fraud department. AI is also being used to help streamline and make trading more manageable by making the supply, demand, and pricing of securities easier to estimate.

What you will learn from this course

When you complete this Artificial Intelligence for Beginners course, you will be able to accomplish the following:

The meaning, purpose, scope, stages, applications, and effects of AI Fundamental concepts of machine learning and deep learning. The difference between supervised, semi-supervised, and unsupervised learning. Machine Learning workflow and how to implement the steps effectively. The role of performance metrics and how to identify their key methods:

• Purpose of artificial intelligence technology
• Concepts of deep learning and machine learning workflow
• Supervised learning
• Semi-supervised learning
• Unsupervised learning

Simplilearn is a digital skills training leader, focused on the emerging technologies that are transforming our world. Their blended learning approach drives learner engagement backed by the industry’s highest completion rates. Partnering with professionals and companies, They identify their unique needs and provide outcome-centric solutions to help them achieve their professional goals.

Syllabus

Lesson 01 – Decoding Artificial Intelligence

• Decoding Artificial Intelligence
• Meaning, Scope, and Stages Of Artificial Intelligence
• Three Stages of Artificial Intelligence and Applications of Artificial Intelligence
• Image Recognition and Applications of Artificial Intelligence with Examples
• Effects of Artificial Intelligence on Society and Supervises Learning for Telemedicine
• Benefits Multiple Industries

Lesson 02 – Fundamentals of Machine Learning and Deep Learning

• Fundamentals Of Machine Learning and Deep Learning
• Meaning of Machine Learning & Relationship between Machine Learning and Statistical Analysis
• Process of Machine Learning & Types of Machine Learning
• Meaning of Unsupervised Learning & Semi-supervised Learning
• Algorithms of Machine Learning, Regression, and Naive Bayes Classification
• Artificial Neural Network Definition and Definition of Perceptron

Lesson 03 – Machine Learning Workflow

• Machine Learning Workflow and Transform Features

Lesson 04 – Performance Metrics

• Performance Metrics Need For Performance Metrics and Key Methods
• Confusion Matrix Example and Terms Of Confusion Matrix
• Minimize False Cases and False Positive Example
• Accuracy, Precision, Recall Or Sensitivity, Specificity, and F1 Score

Pre-requisites

There are no prerequisites for opting for this Artificial Intelligence for Beginners course. It does not require programming or IT background, making it ideal for professionals from all walks of corporate life.

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