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Generative AI Models and Transformer Networks Certification Specialization

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Generative AI Models and Transformer Networks Certification Specialization

Build VAEs GANs and Transformers with AI

Priyanka Mehta

Instructor: Priyanka Mehta

Included with Coursera Plus

Get in-depth knowledge of a subject
Beginner level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Beginner level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Build VAEs, GANs, and Autoencoders to generate realistic synthetic data

  • Apply attention mechanisms and Transformer models like GPT and BERT

  • Use Retrieval Augmented Generation (RAG) to enhance GenAI output accuracy

  • Deploy GenAI solutions to solve real-world business problems

Details to know

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Taught in English
Recently updated!

June 2025

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Specialization - 3 course series

What you'll learn

  • Train and evaluate generative AI models using real-world techniques

  • Apply Retrieval Augmented Generation (RAG) to improve output accuracy

  • Understand emerging trends in GenAI architecture and deployment

  • Translate GenAI advancements into practical, industry-ready solutions

Skills you'll gain

Category: Generative AI
Category: Real Time Data
Category: Prompt Engineering
Category: Large Language Modeling
Category: OpenAI
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: ChatGPT
Category: Innovation
Category: Scalability
Category: Emerging Technologies
Category: Data Ethics
Category: Deep Learning
Category: PyTorch (Machine Learning Library)
Category: Tensorflow
Category: Natural Language Processing

What you'll learn

  • Build and train Autoencoders and VAEs using TensorFlow

  • Use VAEs for generating synthetic data like images

  • Understand and apply GAN architecture and training techniques

  • Create realistic outputs with GANs for real-world use cases

Skills you'll gain

Category: Generative AI
Category: Unsupervised Learning
Category: Deep Learning
Category: Computer Vision
Category: Image Analysis
Category: Tensorflow
Category: Artificial Neural Networks
Category: Applied Machine Learning

What you'll learn

  • Apply self-attention and multi-head attention in deep learning models

  • Understand transformer architecture and its key components

  • Explore the role of attention in powering models like GPT and BERT

  • Analyze real-world GenAI applications in NLP and image generation

Skills you'll gain

Category: Deep Learning
Category: Large Language Modeling
Category: Natural Language Processing
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Machine Learning Methods
Category: PyTorch (Machine Learning Library)
Category: ChatGPT
Category: Artificial Neural Networks
Category: Tensorflow
Category: Generative AI
Category: OpenAI

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Instructor

Priyanka Mehta
Simplilearn
26 Courses3,162 learners

Offered by

Simplilearn

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