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DSTC-00857 Online (e-LMS) Graduate / Intermediate

Human-in-the-Loop: AI Training and RLHF

by - DSTC

Master Human-in-the-Loop: AI Training and RLHF in 3 weeks through hands-on, project-based online training with DSTC.

โ˜…โ˜…โ˜…โ˜…โ˜… Be the first to review โ€ข 3 Weeks ยท 30 hrs โ€ข e-Certificate Included
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From โ‚น10,700 + GST

๐Ÿ“š Syllabus & Course Curriculum

Data Science & Analytics

Module-by-module breakdown of Human-in-the-Loop: AI Training and RLHF, from foundations to a certified capstone project.

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Outline

Define core principles of Human-in-the-Loop Learning and its role in modern AI pipelines โ€ข Analyze the role of humans in model training, testing, and continuous monitoring workflows โ€ข Compare feedback modalities including labels, rankings, preferences, and corrections

Outline

Evaluate why traditional supervised learning falls short for complex AI alignment tasks โ€ข Identify core components of RLHF pipelines and their interdependencies โ€ข Examine real-world examples including GPT alignment, code assistants, and human evaluation

Outline

Design effective annotation interfaces and comprehensive task guidelines for labelers โ€ข Implement labeler training, calibration protocols, and bias reduction strategies โ€ข Apply ranking, preference comparison, and paired evaluation techniques for quality feedback

Outline

Build robust reward models from aggregated human feedback signals โ€ข Execute fine-tuning with PPO (Proximal Policy Optimization) for policy improvement โ€ข Align LLMs with RLHF objectives while balancing human control and model capability

Outline

Deploy Human-in-the-Loop workflows in production AI environments โ€ข Leverage active learning and iterative retraining for continuous model improvement โ€ข Integrate APIs, dashboards, and automated feedback loops for scalable operations

Outline

Assess limitations and risks inherent in RLHF implementations โ€ข Navigate ethical and legal considerations in HITL system design โ€ข Balance human-AI collaboration with appropriate control mechanisms

Outline

Architect end-to-end RLHF pipelines from feedback collection to model deployment โ€ข Validate system performance against safety, helpfulness, and harmlessness criteria โ€ข Present solutions to expert panel for feedback and industry readiness assessment

Earn government-registered certification in Human-in-the-Loop: AI Training and RLHF

e-Certificate and e-Marksheet issued on successful completion.

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Scholar Registration

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