Generative AI For Beginners

About Course

Discover our AI courses designed to equip you with essential skills in machine learning, deep learning, and data science. Learn from industry professionals, advance your career in artificial intelligence, and earn certificates upon course completion

Course Content

Machine Learning Fundamentals
This topic covers the basics of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. It could delve into linear regression, decision trees, clustering techniques, and neural networks.

Draft Lesson

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Natural Language Processing (NLP)
NLP focuses on enabling computers to understand, interpret, and generate human language. Topics within NLP could include sentiment analysis, text classification, named entity recognition, and language generation.

Computer Vision
Computer vision involves teaching machines to interpret and understand the visual world. This topic could cover image classification, object detection, image segmentation, and facial recognition techniques.

Deep Learning
Deep learning is a subset of machine learning that deals with neural networks containing many layers. Topics within deep learning could include convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and transfer learning.

Ethical and Social Implications of AI
This topic explores the ethical considerations and societal impacts of AI technologies. It could cover issues such as bias in algorithms, privacy concerns, job displacement, and the responsibility of AI developers.

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Generative AI For Beginners

About Course

What Will You Learn?

Course Content

Machine Learning Fundamentals
This topic covers the basics of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. It could delve into linear regression, decision trees, clustering techniques, and neural networks.

Draft Lesson

Natural Language Processing (NLP)
NLP focuses on enabling computers to understand, interpret, and generate human language. Topics within NLP could include sentiment analysis, text classification, named entity recognition, and language generation.

Draft Lesson

Computer Vision
Computer vision involves teaching machines to interpret and understand the visual world. This topic could cover image classification, object detection, image segmentation, and facial recognition techniques.

Draft Lesson

Deep Learning
Deep learning is a subset of machine learning that deals with neural networks containing many layers. Topics within deep learning could include convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and transfer learning.

Ethical and Social Implications of AI
This topic explores the ethical considerations and societal impacts of AI technologies. It could cover issues such as bias in algorithms, privacy concerns, job displacement, and the responsibility of AI developers.

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About Course

What Will You Learn?

Course Content

Machine Learning Fundamentals This topic covers the basics of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. It could delve into linear regression, decision trees, clustering techniques, and neural networks.

Draft Lesson

Natural Language Processing (NLP) NLP focuses on enabling computers to understand, interpret, and generate human language. Topics within NLP could include sentiment analysis, text classification, named entity recognition, and language generation.

Draft Lesson

Computer Vision Computer vision involves teaching machines to interpret and understand the visual world. This topic could cover image classification, object detection, image segmentation, and facial recognition techniques.

Draft Lesson

Deep Learning Deep learning is a subset of machine learning that deals with neural networks containing many layers. Topics within deep learning could include convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and transfer learning.

Ethical and Social Implications of AI This topic explores the ethical considerations and societal impacts of AI technologies. It could cover issues such as bias in algorithms, privacy concerns, job displacement, and the responsibility of AI developers.

Student Ratings & Reviews

Contact

Explore

Quick Links

Subscribe to get latest update & news

Machine Learning Fundamentals
This topic covers the basics of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. It could delve into linear regression, decision trees, clustering techniques, and neural networks.

Natural Language Processing (NLP)
NLP focuses on enabling computers to understand, interpret, and generate human language. Topics within NLP could include sentiment analysis, text classification, named entity recognition, and language generation.

Computer Vision
Computer vision involves teaching machines to interpret and understand the visual world. This topic could cover image classification, object detection, image segmentation, and facial recognition techniques.

Deep Learning
Deep learning is a subset of machine learning that deals with neural networks containing many layers. Topics within deep learning could include convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and transfer learning.

Ethical and Social Implications of AI
This topic explores the ethical considerations and societal impacts of AI technologies. It could cover issues such as bias in algorithms, privacy concerns, job displacement, and the responsibility of AI developers.