[SOLD OUT] AI Engineering - Building Generative AI Apps That Overcome Enterprise Barriers and Create Real Value

Product teams are scrambling to figure out what they will be doing with this latest wave of AI technologies, and engineering organizations are struggling to bring generative AI into enterprise environments. Beyond anecdotal ChatGPT interactions and intriguing demos, teams need to know how to validate inconsistent model outputs, mitigate the risk of hallucinations, structure text completions, maintain data privacy, integrate private data, establish competitive advantages, plan development activities, and understand the landscape of tooling.

Leaving this workshop, you will be equipped with processes and knowledge to overcome each of these barriers, and you will have gained the practical, hands-on expertise to start integrating generative AI in your domain.

Key Takeaways

1 Learn the essential AI engineering skills of prompting, data augmentation, chaining, developing agents, validating/filtering model inputs and outputs, and fine-tuning.

2 Get hands-on with the latest generative AI models (i.e., Falcon, MPT, Stable Diffusion, Zeroscope, WizardCoder, etc.)

3 Gain a better understanding of how transformative AI applications are being architected via a new generative AI stack of tools/infra.


Daniel Whitenack

Founder & Data Scientist @Prediction Guard, Co-Host of the Practical AI podcast, Previously Built Data Teams at Two Startups and an International NGO

Daniel Whitenack (aka Data Dan) is a Ph.D. trained data scientist and founder of Prediction Guard. He has more than twelve years of experience developing and deploying machine learning models at scale, and he has built data teams at two startups and an international NGO with 4000+ staff. Daniel co-hosts the Practical AI podcast, has spoken at conferences around the world (QCon, ODSC, Applied Machine Learning Days, O’Reilly AI, GopherCon, KubeCon, and more), and occasionally teaches data science/analytics at Purdue University.

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Find Daniel Whitenack at:


Thursday Oct 5 / 09:00AM PDT ( 7 hours )


Seacliff AB


Level intermediate



  • General exposure to the latest wave of generative AI models (e.g., some experience running basic prompts in ChatGPT or a familiarity with generative AI functionalities via fancy demos online)
  • A computer with Internet access
  • A Google/Gmail account (to use Google Colab)
  • Basic Python programming skills
  • Basic command line/ bash skills
  • (Optional) A free SerpAPI key (to run all the agent examples)