// RAG TRAINING
Retrieval Augmented Generation (RAG) training
Retrieval Augmented Generation (RAG) is a groundbreaking approach that revolutionizes how we interact with information. Imagine a powerful tool that seamlessly blends the ability to understand your questions with the capacity to retrieve and generate precise answers. RAG enhances comprehension and response accuracy, making it a game-changer in tasks ranging from research to customer support. Its benefits include rapid access to relevant up-to-date data and improved contextual understanding, ultimately elevating how we harness language models’ potential.
Private
ask for quote
If you are looking for intensive sessions tailored to your (or your team’s) experience, then private training is your perfect choice!
- In presence or Online
- Tailored Training
- Top Expert Trainers
- Certificate of Attendance
Recorded
coming soon
If you are not able to attend public training, this is the best option for you. You will be able to take the course at your own pace and rhythm and learn whenever it fits your schedule and mood.
- Top expert trainers
- Q&A by e-mail
- Certificate of Attendance
Public classroom
£ 120,00
Due to the high demand, we have decided to schedule another session of training about Retrieval Augmented Generation.
SCHEDULE
16th May 2024
3:00 – 7:00 PM GMT+1
- Live on Zoom
- Top expert trainers
- Certificate of Attendance
Private
ask for quote
If you are looking for intensive sessions tailored to your (or your team’s) experience, then private training is your perfect choice!
- In presence or Online
- Tailored Training
- Top Expert Trainers
- Certificate of Attendance
Choose our services like the world’s most innovative companies do
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PREREQUISITES
• Basic knowledge of Search Engines and Machine Learning
• Basic knowledge of Vector Search and Large Language Models
WHAT YOU WILL LEARN
• You will have a complete overview of Retrieval Augmented Generation from its strengths to its differences with a fine-tuning approach
• You will learn about different RAG architectures and optimization techniques with an additional focus on prompt engineering
• You will have the opportunity to see a real RAG implementation with snippets of code
• You will learn RAG best practices, applications, and challenges
INTENDED AUDIENCE
• Technical Managers
• Data scientists
• Software Engineers
• Developers
• Machine Learning passionates
Your Trainers
Alessandro Benedetti
APACHE LUCENE/SOLR COMMITTER
APACHE SOLR PMC MEMBER
Alessandro has been involved in designing and developing search-relevant solutions from 2010.
Over the years he has worked on various projects, with various open source technologies aiming to build search solutions able to satisfy the user information needs, often integrating such solutions with machine learning and artificial intelligence technologies.
Anna Ruggero
R&D Search Software Engineer, her focus is on the integration of Information Retrieval systems with advanced Machine Learning, Natural Language Processing and Data Mining algorithms. She likes to find new solutions that integrate her work as a Search Consultant with the latest Academia studies.
The schedule
The training session is meticulously structured for optimal comprehension and retention.
It commences with a comprehensive 1-hour theory session, followed by a brief 15-minute test to assess understanding. Subsequently, participants engage in a 45-minute Q&A segment, fostering interactive learning and clarification of concepts. The training then resumes with another 1-hour theory module, another 15-minute evaluation test, and concludes with a final 45-minute Q&A session to consolidate knowledge and address any remaining queries.
3:00-4:00 theory session
4:00-4:15 test
4:15-5:00 Q&A segment
5:00-6:00 theory session
6:00-6:15 test
6:15-7:00 Q&A segment
The Topics
1. Introduction to Retrieval Augmented Generation
The train begins by providing participants with a foundational understanding of Retrieval Augmented Generation (RAG). This introductory module offers insights into significance and strengths, setting the stage for deeper exploration. A part is also dedicated to explaining the distinction between the RAG and fine-tuning, in which scenario they are desirable, and which are their pros and cons. The participant will be therefore able to make conscious decisions in choosing the best approach for his/her use-case.
2. RAG shortcomings
An entire section explores the critical points of a RAG pipeline. Here participants are warned about possible problems that could arise when setting up RAG, with a highlight on causes and consequences.
3. RAG solutions
RAG is not a static invariable approach. There are many different ways in which it can be implemented, combining different steps and strategies to solve the shortcomings above. In this module, the pros and cons of all the approaches are given, allowing the learners to choose and define the best RAG pipeline that meets his/her use-case requirements.
4. RAG optimization
RAG optimization is a key step to ensure ideal performance. Depending on the pipeline, different quality of results and different consumption of resources can be achieved. In this module, resource requirements will be analyzed, giving valuable insights into how to manage the RAG pipeline to obtain the best trade-off between accuracy and costs.
5. Prompt engineering techniques
A focus is given to prompt engineering techniques. Their design and testing are a fundamental step to ensure a good quality of RAG results. In this module, several approaches are presented; the participants will understand their strengths and weaknesses, and in which use case they perform the best.
6. A code example of a RAG implementation
A pivotal component of training involves hands-on experience in setting up a RAG pipeline. Participants learn how to design and implement RAG with Python code examples exploiting state-of-the-art libraries.
7. Applications
There are many application scenarios in which RAG can make a difference in the retrieval task. To culminate the training, an overview of RAG applications and critical steps will be given to participants which will benefit from novel ideas and awareness of actual challenges.
FAQ
The training session is conducted online via Zoom for live participation. However, for those who may not be able to attend in real-time or prefer to learn at their own pace, we are working on a recorded version. This allows participants to access the content online and review it at their convenience.
Absolutely! Everyone is welcome to participate in this training.
The ‘Retrieval Augmented Generation (RAG)’ training session has a duration of 4 hours.
Yes, absolutely! You will have the opportunity to ask any questions at the end of the training.
Your teacher will be:
– Alessandro Benedetti, Apache Lucene/Solr committer and Apache Solr PMC member.
Yes, indeed! At the conclusion of the training, you will receive a certificate of attendance via email.
If you need it, you can consult our Training’s Terms and Conditions.
Yes, we do offer corporate training sessions. Feel free to reach out to us, and we’ll be happy to discuss the best options tailored for you and your team!