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7 courses matching “evaluation”

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Abstract cover artwork for RAG Systems in Production, a Agentic AI course Agentic AI
Agentic AI intermediate

RAG Systems in Production

The gap between a RAG demo and a RAG product is chunking strategy, retrieval evaluation and latency budgets. Covers document parsing, chunk boundary design, hybrid retrieval, cross-encoder re-ranking, and caching layers that keep p95 sane.

DO Daniel Okafor 4.9

$89.00

13 hours

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Abstract cover artwork for Deep Learning with PyTorch: Fundamentals to Fine-Tuning, a Deep Learning course Deep Learning
Deep Learning intermediate

Deep Learning with PyTorch: Fundamentals to Fine-Tuning

Autograd from first principles, then real training loops: learning-rate schedules, mixed precision, gradient accumulation, distributed data parallel, and the debugging discipline for a loss that will not go down. Finishes by fine-tuning a pretrained model on a custom dataset with a proper evaluation harness.

HT Hiroshi Tanaka 4.9

$99.00

22 hours

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Abstract cover artwork for Evaluation-Driven LLM Development, a Agentic AI course Agentic AI
Agentic AI advanced

Evaluation-Driven LLM Development

Shipping an LLM feature without an eval suite is shipping a rumour. Build golden datasets from production traffic, write graders that correlate with human judgement, and wire regression gates into CI so a prompt change cannot quietly degrade quality.

MA Marta Alves 4.8

$99.00

12 hours

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Abstract cover artwork for Fine-Tuning LLMs with LoRA and QLoRA, a Deep Learning course Deep Learning
Deep Learning advanced

Fine-Tuning LLMs with LoRA and QLoRA

Adapt a large model on a single GPU. Parameter-efficient fine-tuning, 4-bit quantisation, dataset curation and formatting, catastrophic-forgetting mitigation, and evaluation that detects when your tune made the model worse at everything else. Includes the decision framework for fine-tune versus RAG versus prompt engineering.

AR Ahmed Rahal 4.8

$119.00

13 hours

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Abstract cover artwork for Agentic RAG: Retrieval That Reasons, a Agentic AI course Agentic AI
Agentic AI intermediate

Agentic RAG: Retrieval That Reasons

Naive RAG retrieves once and hopes. Agentic RAG grades what it retrieved, rewrites the query when results are thin, and decides when it has enough context. Covers relevance grading, query rewriting loops, hybrid dense plus keyword retrieval, reciprocal rank fusion and LLM-as-judge re-ranking, with honest evaluation of when each technique actually helps.

DO Daniel Okafor 4.8

$79.00

10 hours

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Abstract cover artwork for MLOps: Shipping Models That Survive Contact With Users, a Machine Learning course Machine Learning
Machine Learning advanced

MLOps: Shipping Models That Survive Contact With Users

Experiment tracking, model registries, reproducible training pipelines, shadow deployments, drift detection and automated rollback. You will build a pipeline where a retrained model cannot reach production without passing evaluation gates, and where a bad deploy is detected in minutes rather than quarters.

AR Ahmed Rahal 4.7

$119.00

20 hours

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Abstract cover artwork for LLM Observability with LangSmith, a Agentic AI course Agentic AI
Agentic AI intermediate

LLM Observability with LangSmith

You cannot debug what you cannot see. Instrument agent runs with distributed tracing, attach custom metadata and tags so runs are filterable, build evaluation datasets from production traffic, and set up regression tests that catch quality drops before users do. Includes selective tracing so your traces stay signal, not noise.

MA Marta Alves 4.6

$59.00

6 hours

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