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🔥Enroll for Generative AI Course: https://intellipaat.com/generative-ai-course/ 🔥𝐁𝐨𝐨𝐤 𝐲𝐨𝐮𝐫 𝐅𝐫𝐞𝐞 𝐌𝐚𝐬𝐭𝐞𝐫𝐜𝐥𝐚𝐬𝐬: https://forms.gle/g5tExa7e54xpYZW97 This complete Generative AI full course covers essential deep learning and NLP concepts including Recurrent Neural Networks (RNN), LSTM, Encoder–Decoder architecture, Seq2Seq models, and BERT embeddings with step-by-step explanations and practical implementation. You’ll 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. You’ll 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. It’s 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. 📖 Below are the concepts covered in the video on 'Generative AI Full Course ': 00:00:00 - Introduction to Gen AI Course 00:01:14 - Flow of Gen AI 00:03:49 - What are RNNs? 00:04:55 - Vanishing Gradient and Exploding Gradient 00:08:49 - Gated Mechanism & What is LSTM 00:52:37 - Encoder (BERT Embeddings) 01:02:24 - Decoder 01:22:46 - Encoder & Decoder (Seq2Seq) 01:33:08 - RNN and LSTM Revision 01:50:17 - Amazon Customer Sentiment Analysis Project (RNN) 02:36:22 - Project Data Sampling 02:54:35 - Regex Implementation 03:17:06 - Tokenization and Padding 03:54:37 - Data Splitting and Model Training (RNN & LSTM) 04:19:38 - Hyperparameter Tuning 05:12:09 - Exporting Model 05:37:10 - Testing Model 06:05:02 - Encoder–Decoder (Seq2Seq) 07:06:29 - Seq2Seq Project – English to Hindi Translation 08:12:57 - Encoder and Decoder Code 08:45:49 - Merging Encoder & Decoder to Build Seq2Seq 09:32:59 - Training Seq2Seq Model 10:41:35 - Testing Seq2Seq Model #generativeaifullcourse #generativeaicourse #generativeaiinoneshot #generativeaicoursefree #intellipaat ➡️ About the Course The Generative AI Course by Intellipaat is designed to help learners master modern Generative AI concepts such as prompt engineering, large language models (LLMs), transformers, and Retrieval-Augmented Generation (RAG) through hands-on projects and live training sessions. The program includes about 96+ hours of learning with real-world applications like chatbots, AI agents, and content generators, and provides certification from Microsoft and iHUB IIT Roorkee. It also covers tools like OpenAI APIs, Hugging Face, LangChain, and deployment techniques, preparing learners for roles such as Prompt Engineer, AI Developer, and Generative AI Specialist. 📌 Do subscribe to Intellipaat channel & come across more relevant Tech content: https://goo.gl/hhsGWb 📚For more information, please write back to us at [email protected] or call us at IND: +91-7022374614 / US : 1-800-216-8930
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