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Udemy - AI Engineer Professional Certificate Course torrent


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Info hash: 79FBE661F64DEE84A08ADE6EFC1DE2902F0D0096
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Health:
 seeds: 6, leechers: 2
Torrent language: English English
Total Size: 1.40 GB
Number of files:
24   
Uploader:
freecoursewb
Torrent added:2025-06-21 20:25:34

Download Udemy - AI Engineer Professional Certificate Course torrent




Torrent Description
AI Engineer Professional Certificate Course

https://WebToolTip.com

Published 6/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 13m | Size: 1.41 GB

Master Deep Learning, Transformers, MLOps & AI Agent Development with Real-World Projects

What you'll learn
Tune and optimize machine learning models using advanced techniques
Build and train CNNs for image classification and computer vision tasks
Develop RNNs, LSTMs, and GRUs for time series and sequence modeling
Understand and implement transformers and attention mechanisms
Apply transfer learning to fine-tune powerful pre-trained models
Design and analyze AI agents for autonomous decision-making
Use TensorFlow and PyTorch for deep learning projects
Deploy models using MLOps tools like Docker, MLflow, and CI/CD pipelines

Requirements
Completion of a beginner or associate-level AI or machine learning course (or equivalent knowledge)
Strong understanding of Python programming, including experience with functions, classes, and working with libraries like NumPy and Pandas
Solid grasp of basic machine learning concepts, including regression, classification, model evaluation, and overfitting
Familiarity with deep learning fundamentals, including neural networks and basic model architecture
Prior exposure to tools like Jupyter Notebook, TensorFlow, or PyTorch
Working knowledge of mathematics for AI, including linear algebra, probability, and calculus
A computer (Windows, macOS, or Linux) with reliable internet and the ability to install development tools
Willingness to explore complex, production-grade systems and invest time in hands-on coding, model experimentation, and deployment workflows

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