Low-Code Data Scientist: Low-Code AI Apps including LLMs and ChatGPT (online)

Themes covered by the course include:  

• Machine learning and deep learning concepts  

• Building blocks of low-code ecosystems   

• Using low-code and large language models (LLMs), including ChatGPT 

• Implementing the machine learning pipeline in low-code systems    

• Prompt engineering 

• Design and development of AI applications in the three low-code platforms:  

  • AWS

  • Azure 

  • GCP (e.g., Microsoft Power platforms, Amazon SageMaker, and Google Vertex AI platform)  

• Deploying low-code AI services in cloud-native MLOps environments   

• Implementing generative technologies in low-code platforms such as chatGPT  

• UX and integration for low-code   

• Use of pre-built models and templates for creating AI applications  

• Comparing and contrasting capabilities of low-code and full-code AI solutions   

• Scaling low-code AI solutions  

• Security and access for low-code applications  

• Using tools like GitHub Copilot 

• Using generative tools in the creative space like DALL-E 

• Examples of low-code applications including: 

  • image recognition 

  • business-based applications (e.g., invoice processing)  

  • sentiment analysis 

  • time series 

  • regression analysis.  

• Creating and managing datasets for low-code applications:  

  • labeling data 

  • dataset creation 

  • annotation, etc.  

• Workflow and process automation for low-code applications  

• Ethical AI and Responsible AI considerations for low-code and generative applications  

Themes covering the integration of low-code and generative AI applications include:   

• Introduction to large language models   

• Building AI applications using large language models  

• Understanding OpenAI, GPT and chatGPT  

• Introducing GPT-3 and the OpenAI API  

• Strategies for designing prompts  

• Understanding OpenAI models:  

  • Davinci 

  • Babbage 

  • Curie 

  • Ada   

• Working with the OpenAI Playground.

The above may be subject to minor changes and adjustments

Participants who attend the full course will receive a University of Oxford electronic certificate of attendance. 

The certificate will show your name, the course title and the dates of the course you attended.

You will be required to attend all of the live sessions on the course in order to be considered for an attendance certificate.

Fees include electronic copies of course materials.

All courses are VAT exempt.

For this course, no prior coding experience is needed but some technical industry background (non coding) or domain knowledge in a tech field is advisable. Our aim is to keep the course inclusive for people who do not have coding/low-code experience. However, if you are still unsure about the suitability of this course, please email us and we will answer any questions you have. We are also happy to arrange to speak to you.