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8 Lectures + 8 Homework Support Sessions + Credly Certification Predictive AI and Generative AI are increasingly used together, yet many teams struggle to build reliable, end-to-end AI solutions. This course bridges that gap by teaching how to design and develop full-stack AI systems that integrate predictive models, large language models (LLMs), and knowledge-driven frameworks. Participants will build scalable AI solutions using a combination of low-code/no-code tools (Langflow, Microsoft Copilot Studio) and advanced coding frameworks (Agno, LangChain, LangGraph). The program introduces Agent Harness design patterns for building reusable, enterprise-grade agentic systems, along with RAG (Retrieval-Augmented Generation) and TAG (Taxonomy-Augmented Generation) for knowledge integration. Learners progress from foundational concepts to advanced architectures, covering multi-agent orchestration, AI copilots, vector databases, embeddings, and enterprise integration patterns. The course emphasizes hands-on learning through real-world use cases and culminates in a capstone project focused on building scalable, production-ready AI solutions with strong emphasis on testing, evaluation, and governance. 🛠️ Key Topics: • AI foundations and business problem framing • Structured & unstructured data pipelines • Predictive AI model development and evaluation • Generative AI and advanced prompt engineering • RAG, TAG, embeddings, and vector databases • Agent Harness design and multi-agent architectures • Low-code agent development (Langflow, Copilot Studio) • Code-first agent frameworks (Agno, LangChain, LangGraph) • End-to-end orchestration and enterprise integration • AI system testing, evaluation, and governance • Capstone project for real-world implementation 🔹 Hands-On Learning – Build real-world AI solutions using both low-code and code-first approaches 🎓 Earn Full Stack Credly Certification upon successful completion of all assignments and the final capstone project
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