GPT and Other LLMs
Fast Track Workshop

Learn how to build Generative AI Large Language Models into your solution

Workshop agenda

Part 1

Learn the LLM technology stack

First, we help you understand what LLMs are, how they work and key factors in their use, approaches to using your own data and ways to get started with experimentation and prototypes.
  • Why LLMs are a major breakthrough
  • How LLMs work
  • GPT, ChatGPT and other foundational LLMs
  • How and where to use LLMs
    • Hosted models and APIs
    • OSS models
    • Training your own model
  • Security considerations
  • Zero-shot and few-shot prompting
  • Model fine tuning
  • New toolchains for working with multiple agents and data sources
  • Ethics, risks and liabilities

Part 2

Understand new LLM use cases

Then we help you get inspired by reviewing new LLM use cases that are pioneering new business solutions.
  • Horizontal use cases including:
    • Improving customer support
    • Improving customer information discovery
    • Analyzing customer feedback
  • Example use cases in other industries including Telco data generation, Retail store assistant, Financial fraud detection, Teacher-like experience for edu-tech
  • Example use cases in your industry and their applicability to your business

Part 3

Define use cases for your business

Then we help you define implementable LLM use cases for your business.
  • Evaluate use case options for your business using your data with the new LLM technology stack
  • Create an effort/impact matrix including feasibility and business impact assessment
  • Identify benefits, risks and concerns including data privacy
  • Outline your implementation steps including fast-start experiments, prototypes and deployment considerations

More Generative AI resources

Insight from our experts

LLMs, Natural Language and Text Generation

Guide: The diverse landscape of large language models. From the original Transformer to GPT-4 and beyond

Read more Guide: The diverse landscape of large language models. From the original Transformer to GPT-4 and beyond

How to train a large language model using limited hardware?

Read more How to train a large language model using limited hardware?

How can we improve language models using reinforcement learning? ChatGPT case study

Read more How can we improve language models using reinforcement learning? ChatGPT case study

Image Generation

Diffusion models in practice. Part 1: The tools of the trade

Read more Diffusion models in practice. Part 1: The tools of the trade

Diffusion models in practice. Part 2: How good is your model?

Read more Diffusion models in practice. Part 2: How good is your model?

Data generation with diffusion models – part 1

Read more Data generation with diffusion models – part 1

Why work with us?

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I really like how deepsense.ai’s workshop gave me a good overview of machine learning techniques and showed me how businesses use big data in general. It is a completely new way of thinking and the workshop introduces that very well.


Robert Wei, Software Engineer

Kyrus

deepsense.ai’s workshop provided us with a good introduction to data science. It was evident that the instructors are not only expert in the subject matter but also experienced in the practical application of the techniques discussed. We found the structured but still open-ended format of the workshop very effective in promoting engagement.


Jose Castillo, Research and Development Engineer

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We were very happy with the workshop. The format was good and deepsense.ai’s instructors were excellent as trainers: experts in the subject matter, obviously, but also good at conveying the knowledge. The participants very much enjoyed it.


Lambert Hogenhout, Chief Analytics, Partnerships and Innovation

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My overall impression from the workshop was positive, the instructors were knowledgeable and also were able to draw on their experiences to give relevant examples during the discussions.


Nitin Navare, AVP Engineering

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About deepsense.ai

deepsense.ai helps companies gain competitive advantage by providing customized  AI-powered end-to-end solutions, with the main focus on AI software, team augmentation and AI advisory.

Our commitment and know-how have been appreciated by global clients including Nielsen, L’Oréal, Intel, Nvidia, United Nations, BNP Paribas, Santander, Hitachi and Brainly. 

Our technology capabilities combine computer vision, predictive analytics and natural language processing. We also deliver large language models and diffusion models training programs to support companies in building AI capabilities in-house.

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