Learn Generative AI Full Course Free 2026 | Intellipaat

🔥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
00:00:58 – 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 – Regex Implementation
03:16:50 – Tokenization and Padding
03:54:21 – Data Splitting and Model Training (RNN & LSTM)
04:19:22 – Hyperparameter Tuning
05:11:53 – Exporting Model
05:36:54 – Testing Model
06:04:46 – Encoder–Decoder (Seq2Seq)
07:06:13 – Seq2Seq Project – English to Hindi Translation
08:12:41 – Encoder and Decoder Code
08:45:33 – Merging Encoder & Decoder to Build Seq2Seq
09:32:43 – Training Seq2Seq Model
10:41:19 – Testing Seq2Seq Model

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➡️ 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.

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