AI Training
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Software engineers, data engineers, and technical learners with basic programming
Technical pathway from mathematics for ML through classical algorithms, neural networks, PyTorch/TensorFlow, training and evaluation, transformers and LLM APIs, feature pipelines, computer vision and NLP code, deployment, responsible AI, and a production-style developer capstone.
What you'll cover
- Python, linear algebra, calculus, and probability for ML
- Classical ML, evaluation metrics, and deep learning fundamentals
- PyTorch, training loops, and transformer / LLM engineering
- Feature pipelines, CNN/NLP code, and model deployment
- Responsible AI, agents, and developer portfolio capstone
Requires comfort with Python and basic programming. Complete Introduction to AI first if you are new to AI concepts.
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