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Go from coder to AI engineer: deep learning, computer vision, NLP with transformers, RAG, fine tuning, and AI agents.
8 modules · 47 lessons
Advanced machine learning engineering, deep learning foundations with PyTorch, computer vision and CNNs, NLP and transformers, applied Generative AI with RAG and vector search, fine tuning and AI agents, serving AI with FastAPI and MLOps, and a capstone end to end AI product.
Level up from writing ML code to engineering real AI systems. This intermediate program from Ucanly takes developers with working knowledge of Python, Pandas, and basic machine learning into professional AI engineering: advanced feature engineering and ensemble methods, deep learning with PyTorch, computer vision with convolutional networks, and natural language processing with transformers and Hugging Face. On the Generative AI side, you will go deep into embeddings and vector search, building RAG systems, fine tuning with LoRA, and orchestrating AI agents with LangChain. You will serve models properly with FastAPI and Docker, apply real MLOps discipline, and graduate having shipped an end to end deep learning and Generative AI application with a trained model, a RAG powered feature, and a live API.
Complete this course to earn a verified Ucanly certificate you can add to your profile, share on LinkedIn, and showcase to employers as proof of the skills you've built.
It is recommended, but working knowledge of Python, Pandas, and basic machine learning is sufficient to start.
Yes, you will build neural networks in PyTorch, computer vision systems with CNNs, and NLP systems using transformers and Hugging Face.
You will design production RAG systems, fine tune models with LoRA, and build AI agents and multi agent workflows with LangChain.
An end to end deep learning and Generative AI application with a trained model, a RAG powered feature, and a live API, mentored by Ucanly.