Generative AI with LLM
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Follow on Instagram for UpdatesGenerative AI with LLM Syllabus — Unit-wise Content
The official GTU curriculum for Generative AI with LLM (subject code ME03000131) as prescribed for ITAC · Semester 3 divides the course into 4 units, covering 5 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (ME03000131)Unit 2 Fundamental concepts
- Probability distribution Neural networks w. e. f
- Academic Year: 2024-25 Semester: 3 Category of the Course: MOPEC Program Name: Master of Engineering Level: PG Subject Code: ME03000131 Subject Name : Generative AI with LLM Generative Adversarial Networks(GANs) Variational Autoencoders(VAEs) Transfer Learning Transformer architecture
Unit 3 Algorithms used in Generative Models
- Recurrent Neural Networks(RNNs) Long Short Term Memory(LSTM) and Gated Recurrent Unit(GRU) Bidirectional RNNs(BRNNs) Power of convolution neural network(CNNs) Activation Functions used in Generative Models Optimization Techniques for Generative Modeling
Unit 4 Text Generation
- Pretraining and Fine tuning of LLM Models Impact of Generative AI and LLM Applications of LLM Natural Language Understanding(NLU) Text Generation and creative writing Language Translation Text summarization Dialog system Content generation and personalization Medical and scientific research
Unit 5 Challenges and Limitation
- Bias and Fairness Ethical Use Privacy concerns Computational Resources Environmental Impact\ Interpretability and transparency Data Quality and diversity
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