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A 16-hour intensive, hands-on workshop designed to give developers a practical understanding of GenAI and the exact frameworks needed to build real-world analytics applications.
Acko needed to move their internal development teams beyond theoretical AI knowledge. The goal was to provide a highly practical understanding of Generative AI focused specifically on building applications[cite: 86]. More importantly, they needed to solve a key business use case: building a reliable "text to insights" application capable of translating natural language into SQL queries[cite: 87].
Baig Academy designed a rigorous 16-hour workshop broken into four intensive modules[cite: 91]. Each module focused on teaching key concepts through immediate, hands-on building exercises tailored for solution builders[cite: 89, 92].
The engagement started by demystifying LLM architectures, embeddings, and the real-world limitations of GenAI[cite: 97, 98]. Participants were then guided through setting up OpenAI and Gemini API access, manipulating tokens and temperature, and successfully coding their first basic chatbot[cite: 105, 106, 107, 115].
Moving past basic chat interfaces, we introduced the architecture of AI Agents[cite: 119]. Teams evaluated the promises and pitfalls of agentic workflows[cite: 122, 123] and gained hands-on experience coding agents using frameworks like CrewAI, Autogen, and PhiData to execute sequential actions[cite: 126, 130].
Focusing on Acko's primary use case, this module tackled the high-level challenges of Text-to-SQL[cite: 131, 134]. Participants engaged in a hands-on lab where they created databases, provided schema information securely to LLMs, and built a functional Text-to-SQL prototype from scratch[cite: 138, 139, 140].
The workshop culminated in a collaborative group activity where teams applied their new frameworks directly to the specific internal case study[cite: 142]. We concluded by equipping the team with advanced fine-tuning guidelines and actionable next steps to improve model performance post-workshop[cite: 145, 146].
"The biggest shift wasn't learning another AI tool,it was learning a practical framework for building production-ready AI applications. By the end of the workshop, our teams had moved from concepts to confidently creating a working Text-to-SQL solution they could continue evolving internally."
~ Analytics Engineering Team -ACKOEmpower your developers to build reliable, scalable AI agents.
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