Master AI Engineering: Build, Train, and Deploy Scalable AI Solutions with Real-World Projects and Hands-On Learning.(AI
What you will learn
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Build AI models using Python, TensorFlow, and PyTorch to create intelligent systems capable of solving real-world problems
Preprocess, clean, and analyze complex datasets to ensure high-quality input for machine learning and AI model training
Train, evaluate, and optimize machine learning models for tasks like regression, classification, and clustering
Design, implement, and fine-tune neural networks, including CNNs and RNNs, for advanced AI applications
Apply Natural Language Processing (NLP) techniques to analyze, interpret, and generate human-like text data
Leverage transfer learning to adapt pre-trained AI models for new tasks, reducing development time and resources
Deploy AI models using scalable APIs and containerization tools like Docker for seamless integration into applications
Monitor AI model performance, detect data drift, and establish retraining workflows for consistent reliability
Solve real-world business and technical challenges using AI-driven approaches and intelligent systems
Develop end-to-end AI projects, from ideation and prototyping to deployment and long-term maintenance
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