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AI Enginner 2026 Complete Course, GEN AI, Deep, Machine, LLM
Service
17,48 $US
5,07 $US
Moyens de paiement disponibles
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
AI Enginner 2026 Complete Course, GEN AI, Deep, Machine, LLM