AI Engineering
AI Engineering focuses on building, deploying, and scaling production-ready AI systems.
Course overview
AI Engineering focuses on building, deploying, and scaling production-ready AI systems.
What you’ll learn
- Master the architecture of Deep Learning models and Transformers.
- Build and optimize Generative AI applications using LLMs like GPT-4, Llama 3, and Gemini.
- Implement advanced RAG (Retrieval-Augmented Generation) pipelines for domain-specific data.
- Develop autonomous AI Agents using frameworks like LangGraph and CrewAI.
- Learn MLOps: Scale, monitor, and deploy models using Docker, Kubernetes, and AWS SageMaker.
- Master high-performance AI tools: PyTorch, Hugging Face, and Vector Databases (Pinecone/Milvus).
Course Curriculum
A structured, progressive curriculum designed to build depth, intuition, and real-world proficiency over time.
This section introduces key concepts and builds intuition through structured lessons and exercises.
Who this course is for
- Proficiency in Python programming
- Intermediate understanding of Linear Algebra and Probability
- Familiarity with Data Manipulation (Pandas/NumPy)
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Want to know whether this course is right for you?
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