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Generate Insights with LLMs

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Coursera

Generate Insights with LLMs

Hurix Digital

Instructor: Hurix Digital

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Measure and improve LLM output quality using metrics like ROUGE and BLEU to systematically enhance executive business communications.

  • Design scalable data-to-text pipelines by integrating SQL data sources, Python processing, and LLM APIs for automated reporting.

  • Apply human-in-the-loop evaluation to complement automated metrics and assess relevance, clarity, and real business value of outputs.

  • Make cost-performance trade-offs by comparing open-source and commercial LLMs based on cost, latency, and enterprise needs.

Details to know

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Recently updated!

March 2026

Assessments

8 assignments¹

AI Graded see disclaimer
Taught in English

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Build your subject-matter expertise

This course is part of the AI Techniques, Causal Inference & Business Optimization Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

Learners will apply LLMs to generate first-draft executive briefs that summarize model insights and refine prompts to meet specified ROUGE or BLEU scores.

What's included

2 videos1 reading2 assignments

Learners will create comprehensive data-to-text pipelines that combine SQL, Python, and LLM APIs to automatically transform KPI (Key Performance Indicator ) tables into narrative summaries.

What's included

3 videos1 reading1 assignment1 ungraded lab

Learners will fine-tune small LLMs on company FAQs and measure improvement in response relevance through systematic human evaluation.

What's included

2 videos2 readings2 assignments

Learners will evaluate cost vs. latency trade-offs between open-source and commercial LLMs for real-time chat applications through systematic analysis.

What's included

2 videos1 reading3 assignments

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Hurix Digital
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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.