Generative AI Model Training and Integration

 

Instructor: Dr. David Ostrowski

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Prerequisites: Basic knowledge of software development, familiarity with programming (Python preferred but not mandatory), and an interest in AI applications.

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Hours: 12 

 

Overview: Generative AI (GenAI) has gained a substantial amount of traction in the last year. This presented as many challenges as opportunities. This course will present an executed overview of generative AI, how their models are structured, trained and integrated with existing applications. This course will provide a number of hands-on exercises that will allow for the means of integrating generative AI an existing data pipeline. This workshop will also allow for a pragmatic implementation and perspective of GenAI where large models are implemented at a local level allowing for the maintenance of private data.

 

Topics Covered: There are twelve modules, each designed to be covered in one hour lecture. Each module comes with exercises. Those are mandatory to enhance learning and to test your understanding of the material.

 

Module 1:  Introduction to Generative AI​

• Overview of fundamentals of Generative AI

• Detailing of the most popular applications and determination of efficiency

 

Module 2: Generative AI API integration

• Hands on implementation of generative AI APIs

• Presentation of possible models

 

Module 3: Large Language Model LLM implementation

• Overview of LLMs and their application in industry

• Hands-on implementation of LLMs via (local) cloud based servers

 

Module 4: Google CoLab

• Introduction to Google CoLab

• Basic Integration into current architectures ( including data architecture )

 

Module 5: Training of LLMs locally

• Overview of (tiny) LLMs and training

• Hands-on Implementation of the training of a model

 

Module 6: GenAI applications and architecture integration

• Best applications for GenAI

• Challenges of integration

 

Target Audience: The course is designed for researchers, practitioners, and students interested in understanding and apply generative AI in current applications or constructing completely new applications around this topic. Participants should have a basic understanding of software development and artificial intelligence concepts.

 

Format: The course will include lectures, hands-on exercises with programming (using Python or similar tools), and interactive discussions.

 

Outcome: By the end of the course, participants will gain:

• A solid understanding of generative AI models

• Practical skills in applying generative AI to solve real-world problems.

• Insights into the training of generative AI models.