AI Agentic Design Patterns with AutoGen

DeepLearning.AI is a specialist online education platform founded in 2017 that focuses on practical, industry-relevant training in artificial intelligence and machine learning. Designed for learners at multiple levels, its courses emphasize hands-on projects, clear conceptual foundations and tools commonly used in industry. The platform’s flexible online format makes it accessible to professionals and students worldwide who want to build skills without relocating.

Courses and specializations are structured to help learners develop applied portfolios, with real-world assignments, code notebooks and community review. Collaboration with leading practitioners ensures content remains current with industry practice, and certificate programs help demonstrate competencies to employers. The platform also supports career transitions, offering guidance on interviewing for technical roles and connecting learners with opportunities to showcase their work.

For international learners seeking concentrated, practice-oriented AI education, DeepLearning.AI provides a clear route to upskill quickly and build demonstrable expertise. Its global learner community, modular course design and emphasis on project-based learning make it a pragmatic choice for those aiming to enter research, product or engineering roles in the AI ecosystem.

The AI Agentic Design Patterns with AutoGen program is a non-degree course for students who want to learn how to build and customize multi-agent systems. It's taught in English and lasts several weeks. The main advantage of this program is that it helps students gain hands-on experience with AutoGen's core components.

The curriculum focuses on specific subjects like multi-agent conversations, collaboration design patterns, and tool use design patterns. Students will develop skills in areas like conversational AI, agent reflection, and coding. The program includes hands-on components where students create their own projects, such as a two-agent chat, a conversational chess game, and a coding agent capable of generating code for financial analysis.

After completing this program, students can pursue careers as AI Engineers, Conversational AI Designers, Software Developers, Data Analysts, or Financial Analysts. They can work in industries like technology, finance, or healthcare, and can be employed by companies that use AI and machine learning to drive their business.