Build Low-Code Autonomous AI Agent Systems Course for Engineers and Developers Launched – Interview Kickstart Adds Live Projects And Agentic AI Workflows

Interview Kickstart, a U.S.-based provider of technical upskilling programs for software and data professionals, has announced the launch of its Applied Agentic AI Pathway, a seven-week training program developed to help engineers gain practical experience in designing and deploying agent-based artificial intelligence systems. Visit the Interview Kickstart website to learn more about the Low-Code Autonomous AI Agent Systems Course.

Agentic AI involves autonomous systems capable of independently performing tasks, collaborating with other agents, and optimizing actions based on real-time conditions. As organizations across finance, operations, logistics, and software engineering integrate multi-agent systems into existing workflows, the need for professionals who can build and support these systems continues to increase. Interview Kickstart’s new course aims to address this demand by offering a structured and applied learning pathway.

The program provides participants with live instruction from engineers and AI practitioners at FAANG and Tier-1 technology companies. These instructors bring direct experience from projects involving generative models, multi-agent frameworks, and large-scale automation pipelines. Their sessions cover practical considerations such as system coordination, agent communication protocols, performance scaling, and model optimization strategies.

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The Applied Agentic AI Pathway includes two live guided projects and a capstone project, which allow participants to build functioning agentic workflows using real tools and datasets. These projects simulate scenarios where autonomous agents must collaborate to complete tasks, retrieve data, or support automated decision-making within enterprise environments. Through these hands-on assignments, learners gain practical exposure to the challenges associated with deploying agent-based systems at scale.

The curriculum covers several core themes, including Foundations of Agentic AI, Multi-Agent Financial Systems, Optimization Strategies for AI Agents, and an end-to-end capstone that requires participants to apply their learning to a real-world problem. Instruction emphasizes both conceptual clarity and practical implementation, enabling learners to understand how autonomous agents operate within broader AI ecosystems.

A spokesperson for Interview Kickstart said, “Agentic AI represents an important shift in how automated systems are designed and managed. This program gives engineers a structured environment to learn how autonomous agents function and how these systems can be applied to solve real operational challenges.”

The seven-week structure combines live classes, self-paced learning modules, and project-based execution. Each week introduces new concepts that expand on earlier sessions, allowing participants to progress from foundational knowledge to more advanced applications. The design of the program makes it accessible for working professionals who want to strengthen their AI capabilities while balancing full-time roles.

According to Interview Kickstart, the Applied Agentic AI Pathway is intended for engineers who want to transition into AI-oriented roles or expand their understanding of how agent-based models are used in automation and intelligent system design. The curriculum provides a baseline understanding of how agents communicate, coordinate tasks, and contribute to production-level AI applications, which can assist learners in applying these skills in workplace environments.

The launch of the Applied Agentic AI Pathway aligns with Interview Kickstart’s ongoing focus on applied AI education. The organization continues to introduce programs that reflect changes in industry practices and advancements in automation technologies. This new course joins a portfolio of specialized pathways designed to help professionals build skills in machine learning, generative AI, cloud architecture, data science, and system design.

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