Video Training →Artificial Intelligence (Ai) Tutorial For Beginners

What you'll learn
Get a clear understanding about Artificial Intelligence.
How a computer can take a decision on its own.
Various types of Artificial Intelligence available.
Understanding Agents and Environments.
Understanding about the issues with Artificial Intelligence.
Requirements
Curiosity to know how a computer can think.
Nothing else! It's just you, your phone and your hunger to get started today
Description
What Will I Learn?Get a clear understanding about Artificial Intelligence.How a computer can take a decision on its own.Various types of Artificial Intelligence available.Understanding Agents and Environments.Understanding about the issues with Artificial Intelligence.Who is the target audience?Who is curious to know how the basics functionality of Google now, Siri, Cortana or other AI.Those who want to start their career in AI, this course can give you a clear idea about the basics of AI.BenefitsAI can be applied to any industry, to solve problems, Hence the demand of engineers having a good knowledge of AI is increasing day by day.Automobile companies are moving towards driverless cars to avoid any human error while driving a car.Weather predictions are getting accurate thus helping people to plan their day.SalaryArtificial Intelligence engineer' salary based on their experience is listed below: Entry-level (0-2 years of experience) - Entry Level JobMid-level (2-5 years of experience) - Mid level SalaryExperienced (5-10 years of experience) - Experienced JobSenior-level (10+ years of experience)RequirementsCuriosity to know how a computer can think.Nothing else! It's just you, your phone and your hunger to get started today
Overview
Section 1: Introduction to AI
Lecture 1 Introduction of AI
Lecture 2 Mapping human functions to AI technologies
Section 2: Branches of AI
Lecture 3 AI - Branches of Machine Learning Algorithms
Lecture 4 AI - Supervised Machine Learning Algorithms and Applications
Lecture 5 AI - Unsupervised Machine Learning Algorithms and Applications
Lecture 6 AI - Natural Language Processing and Applications
Lecture 7 AI - Computer Vision and Applications
Lecture 8 AI - IOT and Applications
Section 3: Neural Networks
Lecture 9 What are Neural Networks
Lecture 10 Neural Networks - Perceptron
Lecture 11 What are Deep Neural Networks
Section 4: Feed Forward Neural Network (FFNN)
Lecture 12 Feed Forward Neural Networks (FFNN) Structure and Forward pass
Lecture 13 Input - Feed Forward Neural Networks (FFNN)
Lecture 14 Learning Phase - Feed Forward Neural Networks (FFNN)
Lecture 15 Back propagation and learning step -Feed Forward Neural Networks (FFNN)
Lecture 16 Applications and Limitations of Feed Forward Neural Networks( FFNN)
Section 5: Convolutional Neural Network (CNN)
Lecture 17 CNN Introduction
Lecture 18 CNN - Convolution and Relu Layer
Lecture 19 CNN - Max Pooling Layer
Lecture 20 CNN - Example end to end
Section 6: Recurrent Neural Network (RNN)
Lecture 21 Recurrent Neural Network (RNN)
Lecture 22 RNN Architecture
Section 7: Generative Adversarial Network (GAN)
Lecture 23 Generative Adversarial Networks (GAN)
Section 8: Reinforcement Learning
Lecture 24 Reinforcement Learning
Section 9: Transfer Learning
Lecture 25 Transfer Learning
Section 10: Conclusion
Lecture 26 Market Potential of AI
Lecture 27 Who will loose to AI
Lecture 28 Need for retraining and reskilling
Lecture 29 How to take advantage and benefit from AI
Who is curious to know how the basics functionality of Google now, Siri, Cortana or other AI.,Those who want to start their career in AI, this course can give you a clear idea about the basics of AI.
Homepage

https://www.udemy.com/course/artificial-intelligence-ai-tutorial-for-beginners/