Learn Generative AI Full Course Free 2026 | Intellipaat
๐ฅ๐๐จ๐จ๐ค ๐ฒ๐จ๐ฎ๐ซ ๐
๐ซ๐๐ ๐๐๐ฌ๐ญ๐๐ซ๐๐ฅ๐๐ฌ๐ฌ: https://forms.gle/g5tExa7e54xpYZW97
๐ฅEnroll for Generative AI Course: https://intellipaat.com/generative-ai-course/
This complete Generative AI full course covers essential deep learning and NLP concepts including Recurrent Neural Networks (RNN), LSTM, EncoderโDecoder architecture, Seq2Seq models, and BERT embeddings with step-by-step explanations and practical implementation. Youโll understand key topics like vanishing and exploding gradients, gated mechanisms in LSTM, tokenization, padding, regex preprocessing, and model training workflows used in real-world AI applications.
The tutorial also includes hands-on projects such as Amazon customer sentiment analysis using RNN & LSTM and a Seq2Seq English-to-Hindi machine translation model, helping you build strong practical skills in natural language processing. Youโll learn data sampling, preprocessing pipelines, hyperparameter tuning, exporting trained models, and testing AI systems, making this course ideal for beginners and intermediate learners building an NLP portfolio.
Whether you are preparing for AI, Machine Learning, Data Science, or Generative AI roles, this video provides a structured learning path from fundamentals to advanced sequence models. Itโs perfect for students, developers, and professionals who want to master deep learning for NLP, sequence-to-sequence models, sentiment analysis projects, and translation models using Python, TensorFlow, and Keras.
๐ Below are the concepts covered in the video on 'Generative AI Full Course ':
00:00:00 - Introduction to Gen AI Course
00:00:58 - Flow of Gen AI
00:03:33 - What are RNNs?
00:04:39 - Vanishing Gradient and Exploding Gradient
00:08:33 - Gated Mechanism & What is LSTM
00:52:21 - Encoder (BERT Embeddings)
01:02:08 - Decoder
01:22:30 - Encoder & Decoder (Seq2Seq)
01:32:52 - RNN and LSTM Revision
01:50:01 - Amazon Customer Sentiment Analysis Project (RNN)
02:36:06 - Project Data Sampling
02:54:19 -
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Chapters (11)
Introduction to Gen AI Course
0:58
Flow of Gen AI
3:33
What are RNNs?
4:39
Vanishing Gradient and Exploding Gradient
8:33
Gated Mechanism & What is LSTM
52:21
Encoder (BERT Embeddings)
1:02:08
Decoder
1:22:30
Encoder & Decoder (Seq2Seq)
1:32:52
RNN and LSTM Revision
1:50:01
Amazon Customer Sentiment Analysis Project (RNN)
2:36:06
Project Data Sampling
๐
Tutor Explanation
DeepCamp AI