This Specialization is designed for software developers, junior machine learning engineers, and computer science students who want to apply Generative AI in software development. Across four courses, learners progress from understanding generative AI fundamentals and developing effective prompts to using AI in coding workflows and building applications with DeepSeek, LangChain, Streamlit, and related tools. The curriculum emphasizes practical development skills, including code generation, debugging, test writing, and AI application prototyping.
Applied Learning Project
Learners will apply Generative AI concepts to software development challenges, progressing from prompt design to working AI application prototypes. They will practice using AI for code generation, debugging, test writing, retrieval-augmented generation (RAG), and workflow automation. In the culminating application-building stage, learners will explore DeepSeek models and tools such as Jupyter, LangChain, Streamlit, and DSPy to develop prototypes such as question-answering bots, chatbots, and code generators. These activities connect AI concepts with practical engineering workflows and application development.
