GENERATIVE AI TRAINING IN HYDERABAD

Generative AI Training in Hyderabad offered by Brolly Academy is a comprehensive program designed to equip learners with the necessary knowledge and skills to excel in the field of artificial intelligence. This training covers a wide range of topics from foundational concepts in AI and machine learning to advanced deep learning techniques ensuring a well-rounded learning experience. The curriculum is structured to provide both theoretical understanding and hands-on practical implementation making it suitable for beginners as well as experienced professionals looking to upskill in the domain of Generative AI.

The course begins with an Introduction to Generative AI and its applications across various industries. Participants will learn about the fundamental principles of AI machine learning deep learning and natural language processing (NLP). The training delves into different machine learning techniques including supervised unsupervised semi-supervised and reinforcement learning providing a strong foundation in the concepts that drive AI systems. Ethical considerations in AI deployment are also discussed to help learners understand the responsibilities that come with working in this field.

Natural Language Processing (NLP) and deep learning form a crucial part of the course. Participants will gain insights into text classification methods including frequency-based approaches like Bag of Words TF-IDF and N-grams as well as distributional models like Word2Vec GloVe and Continuous Bag of Words (CBOW). The course also covers traditional machine learning models such as Naïve Bayes Support Vector Machines (SVM) Decision Trees and Logistic Regression. Deep learning techniques including Convolutional Neural Networks (CNNs) Recurrent Neural Networks (RNNs) Long Short-Term Memory (LSTM) and Transformers are explored in detail to help learners build state-of-the-art AI applications.

A major highlight of the training is the in-depth exploration of Generative AI models. Participants will learn about Autoencoders and their applications Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs). Different types of GANs and their real-world applications are examined to provide a practical understanding of how these models generate high-quality synthetic data. This module also includes insights into Transformer-based models such as BERT RoBERTa and various versions of GPT which are widely used in natural language generation and processing tasks.

Prompt engineering is another key component of the training where learners will understand how to craft effective prompts for AI models. The course covers different prompt engineering techniques such as Priming Prompts and Prompt Decomposition which are essential for optimizing AI-generated responses. This is particularly useful in applications involving chatbots virtual assistants and AI-driven content generation.

The training also includes a dedicated module on Large Language Models (LLMs) where participants will explore the lifecycle of Generative AI Reinforcement Learning from Human Feedback (RLHF) and various techniques for fine-tuning LLMs. Learners will understand the importance of scaling and pre-training LLMs to enhance their performance in real-world applications. Additionally the course covers LLM embeddings which play a crucial role in understanding word sentence and contextual embeddings. Techniques such as Word2Vec GloVe FastText BERT GPT and Universal Sentence Encoder are explored along with their practical applications in AI models.

Advanced chunking techniques are also included in the training which helps in processing large text documents efficiently. Traditional chunking methods and their limitations are discussed followed by advanced methods such as Character Splitting Recursive Character Splitting Document-based Chunking Semantic Chunking and Agentic Chunking. These techniques are particularly useful in document processing search engines and AI-driven text analysis.

Another important topic covered in the course is Retrieval-Augmented Generation (RAG) and its implementation with Langchain. Learners will understand the architecture of RAG systems and how they can be built using external data sources to improve the performance of AI models. Advanced RAG techniques and their real-world applications are also explored helping learners build efficient AI-driven search and retrieval systems.

The training also includes a deep dive into Langchain for Large Language Models (LLMs). Participants will learn about Langchain's core concepts components and the effective use of Langchain agents in AI applications. This knowledge is valuable for those looking to integrate LLMs into production environments for various AI-driven solutions.

Lastly the course covers Vector Databases which are essential for managing and retrieving high-dimensional data efficiently. Learners will understand the advantages of Vector Databases over traditional databases explore different types of Vector Databases and learn their applications in AI-powered search and recommendation systems.

Overall Brolly Academy’s Generative AI Training in Hyderabad provides a well-structured and comprehensive learning experience. The course covers all essential aspects of Generative AI from foundational concepts to advanced techniques making it an ideal choice for anyone looking to build expertise in this rapidly growing field. With practical hands-on sessions real-world case studies and expert guidance this training equips participants with the skills needed to create and deploy AI-powered solutions effectively.

Host or Publisher Brolly Academy