Mastering RAG: 10 Projects in Retrieval-Augmented Generation

Unlock the Power of RAG: 10 Hands-On Projects to Master Retrieval-Augmented Generation


What you'll learn
Building RAG Applications from Scratch using Vector Databases and CustomGPT Systems
Applying RAG Applications on Real Life Examples and Domains such as Transport, Housing, Healthcare, Leisure and Energy
Vector Databases and Embeddings
Structured Methods in Collecting, Testing Data for RAG systems
Fundamentals of Retrieval-Augmented Generation (RAG)
Engage in hands-on projects that encompass a range of real-world applications, RAG, PINECONE & GPT.
Embrace the ethical considerations and challenges in deploying RAG technology

Requirements
Python : Beginner Level
Background on Generative AI

Description
This course focuses on building your skills in the development of Custom GPT systems and RAG technology, the course focuses on the utilization of RAG technology on various sectors. The course touches on a step by step approach on how to build a RAG sector through Custom GPTs, Vector Embeddings, Vector databases and API deployment on the 2nd Chapter the course provide 10 different practical projects on how to create a GPT System.
In the ever-evolving landscape of artificial intelligence, the demand for personalized and highly efficient AI models has never been more critical. This comprehensive course is meticulously designed to equip you with profound knowledge and practical skills in developing Custom Generative Pre-trained Transformer (GPT) systems, with a special focus on the integration of Retrieval-Augmented Generation (RAG) technology. As we delve into the realms of AI customization, this course will guide you through the intricacies of tailoring GPT models to specific sectors, leveraging the cutting-edge capabilities of RAG technology to enhance the functionality, relevance, and efficiency of AI applications.
Sector-Specific GPT Systems – Project-Based Learning
Expert Knowledge GPT System (Education, Research & Development):
Designing AI to augment academic research and facilitate educational processes.
Car Pooling GPT System (Transport):
Creating sustainable transport solutions through AI-driven carpooling services.
Domestic Car Charging & Rental GPT System (Transport):
Innovating the transport sector with AI-powered car rental and charging systems.
Community Motorbikes and Bicycle Renting Services (Transport):
Enhancing urban mobility with AI-enabled bike-sharing ecosystems.
Group Sports (Leisure & Sports):
Fostering community sports engagement through intelligent AI coordination.
Group Activities & Team Building System (Leisure & Self Development):
Leveraging AI to organize and optimize group activities and team-building events.
Housemate GPT System (Housing):
Streamlining the search for compatible housemates using AI-driven matching algorithms.
Energy Application – Energy Credit/Debit Market (Energy):
Revolutionizing the energy sector with AI-managed credit/debit systems.
Health Help GPT (Healthcare):
Transforming healthcare assistance with AI-powered advisory systems.
Doctors GPT (Testimonials & Ratings) (Healthcare):
Enhancing healthcare transparency through AI-curated doctor reviews and ratings.
Learning Outcomes:
Upon completing this course, you will:
Have an advanced understanding of Custom GPT systems and RAG technology.
Be proficient in designing, implementing, and deploying sector-specific AI solutions.
Gain practical experience through hands-on projects, enhancing your portfolio.
Develop the skills to innovate and lead AI projects in various industries.
Who Should Enroll:
This course is ideal for AI enthusiasts, data scientists, software engineers, and industry professionals keen on mastering advanced AI technologies, specifically in the customization of GPT systems and the application of RAG technology. Whether you're looking to advance your career, spearhead AI initiatives in your organization, or innovate in the AI space, this course will provide you with the knowledge and skills to achieve your goals
Who this course is for:
Data Scientists and AI Researchers
Machine Learning Engineers
Software Developers with an Interest in AI
AI Enthusiasts and Hobbyists
Academics and Students
Tech Industry Professionals
Smart City Engineering
Transportation Professionals and Engineers

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