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IntermediateArtificial Intelligence8 weeks
Certificate IncludedCertificate EligibleUcanly certificate

Artificial Intelligence (AI): Intermediate

Go from coder to AI engineer: deep learning, computer vision, NLP with transformers, RAG, fine tuning, and AI agents.

Duration
8 weeks
Level
Intermediate
Content
47 lessons
8 modules · 15 h 31 min
Certificate
Included
On completion
Access
Fee by email
Or take the free aptitude test

What you'll learn

Apply advanced feature engineering, ensemble methods, and reproducible ML pipelines
Understand neural networks, backpropagation, and training dynamics deeply enough to build them from scratch in PyTorch
Build computer vision systems using CNNs, transfer learning, and object detection
Build NLP systems using tokenization, embeddings, and the transformer architecture with Hugging Face
Design production RAG systems with embeddings, vector search, chunking, and reranking
Fine tune models with LoRA and prepare high quality training datasets
Build AI agents and multi agent workflows with LangChain
Serve AI models as production APIs with FastAPI and Docker, with real MLOps discipline
Ship an end to end deep learning and Generative AI application with a trained model, a RAG feature, and a live API

Who this course is for

  • Beginner level graduates ready to move into professional AI engineering
  • Self taught practitioners who know basic ML and want structured, production level skills
  • Junior data scientists and ML engineers preparing for mid level interviews
  • Anyone who wants hands on experience building deep learning and Generative AI systems

Skills you'll gain

AI EngineerDeep LearningPyTorchTensorFlowComputer VisionCNNNLPTransformersHugging FaceEmbeddingsVector DatabasesRAGFine TuningLoRALangChainAI AgentsFastAPIMLOps

This course includes

Live mentor led Ucanly sessions plus self paced recorded content
Production style projects in every module
Ucanly portfolio review, mock technical interviews, and a personalized roadmap to Advanced
Lifetime access to course materials and future updates
Certificate of Completion from Ucanly

Course content

8 modules · 47 lessons · 15 h 31 min

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.

Requirements

  • Completion of the Beginner level, or working knowledge of Python, Pandas, and basic machine learning
  • A computer capable of running Python and common deep learning libraries
  • Comfort training and evaluating a simple machine learning model

About this course

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.

Earn a Ucanly certificate

Complete this course to earn a Ucanly certificate with its own page and QR code. Save it as a PDF, share its link, or add it to the certifications on your LinkedIn profile.

Certificate IncludedCertificate EligibleUcanly certificate

Frequently asked questions

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.