About
Course Duration : 3 Weeks ( 12 Hours) Course Fee : Rs. 2000/- This course provides a structured introduction to Generative AI and its practical use within the AWS ecosystem. It begins with core concepts such as foundation models, large language models, creative AI techniques, and the differences between generative and traditional machine learning approaches. Students explore Amazon Bedrock as the primary service for accessing and deploying foundation models from providers such as Anthropic, Meta, Cohere, and Amazon. Key topics include prompt engineering, model customization, evaluation, and the use of Bedrock APIs to build intelligent applications. The course also covers Amazon SageMaker, focusing on training, fine-tuning, hosting, and monitoring models, along with using SageMaker JumpStart to accelerate development. Learners study essential generative workflows such as text generation, image creation, audio processing, embeddings, vector search, and Retrieval-Augmented Generation using OpenSearch. Practical modules demonstrate how to build chatbots, summarization engines, creative content tools, and domain-specific assistants by integrating services like Lambda, API Gateway, DynamoDB, S3, and Step Functions. Data preparation is addressed through AWS Glue, which supports transformation, cleaning, and pipeline automation. Security, governance, responsible AI, and cost-optimization practices are emphasized to ensure that solutions are both ethical and efficient. Hands-on labs guide learners through creating Bedrock-based applications, implementing RAG pipelines, deploying serverless GenAI APIs, and experimenting with image-generation models. The course concludes with a capstone project that allows participants to design, implement, and present a full generative AI solution built entirely on AWS, reinforcing their technical understanding and preparing them for real-world applications.