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Technical Basics

Generative AI Engineering

This course covers engineering practices for building generative features, prompt design, and output calibration. You will learn to implement structured JSON outputs, configure parameter-efficient LoRA adapters, and design safety evaluation guardrails. By the end, you will deploy automated pipelines to monitor and filter model responses.

Created by SkillCite Instructor
Last updated Aug 2026
Generative AI Engineering
Free
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This course includes:
  • 4 weeks of structured content
  • 13 video lessons & readings
  • 6 hands-on lab exercises & quizzes
  • Verified certificate on completion
What you'll learn

Learning Outcomes

By the end of this course, you'll be able to:

Apply production prompting patterns, including chain-of-thought.
Enforce structured JSON output configurations on model responses.
Calibrate model temperature, top-p, and frequency parameters.
Differentiate fine-tuning, adapters, and model distillation use cases.
Design automated model safety and response evaluation pipelines.

How this course opens doors

Prompt Engineering

Apply chain-of-thought and few-shot patterns to steer generation results.

Structured Outputs

Enforce strict JSON schema outputs to simplify backend database parsing.

Safety Pipelines

Construct automated guardrails to filter toxic queries and verify responses.

4w
Access Duration
Course Content

Course curriculum

6 modules · 28 lessons
01
1. Foundations of Generative AI Engineering
~31 min
What Does a Generative AI~5 min
Types of Generative Tasks~6 min
The Generative AI Engineer's Job~5 min
Quality Dimensions~5 min
Module 1 Quiz — Foundations~10 min
02
2. Prompt Engineering for Production
~36 min
03
3. Controlling Generation Quality & Behavior
~31 min
04
4. Adapting Models — Fine-Tuning, Adapters & Distillation
~26 min
05
5. Multimodal & Specialized Generation
~26 min
06
6. Safety, Evaluation & Responsible Generation
~26 min
Skills you'll gain

Skills Cloud

Chain-of-Thought PromptsStructured JSON SchemasHyperparameter TuningModel Fine-TuningSafety Filter SetupAutomated Evaluation
Target Audience

Who this course is for

AI Engineers

Design prompts, calibrate hyperparameters, and build evaluation pipelines.

Backend Engineers

Integrate structured JSON schemas and connect model safety filters.

Product Developers

Prototype multimodal features and evaluate output qualities.

Offered by

Your instructor

SI

SkillCite Instructor

SkillCite AI

86 courses

SkillCite Industry Expert Instructors bring decades of combined real-world expertise directly to you, making complex concepts simple.

Certification

Earn a Verifiable Certificate

Certificate of Completion
Learner Name
Generative AI Engineering
SC-2026-VERIFIED
Verified

SkillCite Verified Certificate

Complete all modules and pass the final assessment to earn a shareable, verifiable digital credential.

Verifiable via public API with unique credential ID
Shareable on LinkedIn, Twitter, and personal portfolio
Recognized by employers and technology companies
Week-by-Week

Course Timeline

Week 1
Production Prompting Patterns

Master chain-of-thought prompts, configure few-shot logs, and build templates.

Few-shot templatesReasoning promptsTemplate engines
Week 2
Structured Output Control

Define JSON outputs, calibrate temperatures, and track parser errors.

JSON structuresHyperparametersParser checks
Week 3
Model Adaptation & Fine-Tuning

Examine fine-tuning parameters, configure LoRA adapters, and audit distillation.

Fine-tuning logsLoRA adaptersDistillation checks
Week 4
Multimodal Systems

Connect image, audio, and text APIs to build unified generation features.

Multimodal syncImage API checksAudio logs
Week 5
Safety & Evaluation Pipelines

Build response safety guardrails, run evaluations, and deploy monitors.

Safety gatesEvaluation frameworksToxic filters
Common Questions

FAQ

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