AI Enginner 2026 Complete Course, GEN AI, Deep, Machine, LLM

Source: https://www.udemy.com/course/ai-enginner-2026-complete-course-gen-ai-deep-machine-llm/

What you’ll learn

• Build and evaluate Machine Learning models using regression, classification, clustering, and ensemble techniques with proper validation and optimization.
• Design, train, and debug Deep Learning models including fully connected networks, CNNs, and sequence models (RNNs, LSTMs, GRUs) using PyTorch or TensorFlow.
• Understand and implement Transformer-based Large Language Models (LLMs), including attention, embeddings, tokenization, and fine-tuning concepts.
• Create production-ready Generative AI applications using prompt engineering, embeddings, semantic search, and Retrieval-Augmented Generation (RAG).
• Develop agentic AI systems that perform multi-step reasoning, tool calling, and task execution with memory and control mechanisms.
• Apply AI engineering best practices such as feature engineering, model optimization, reproducibility, cost control, evaluation, and performance tuning.
• Integrate AI models into real applications by designing full-stack architectures that connect backends, APIs, and user interfaces with AI systems

Requirements

• Basic Python programming knowledge
• Curiosity to understand how AI works under the hood
• No prior experience in Machine Learning, Deep Learning, or Generative AI is required — everything is explained from first principles to production.

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