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AI & Data

Prompt Engineering for SMEs

Use AI like a senior engineer, not a tourist.

Duration
2 weeks
Format
2 live sessions + 1 lab per week
Track type
Intensive
Open seats
11 across 1 cohort
Apply for this course →See cohort calendar

About this course

Why students take this

Built for SME owners, marketers, and managers who want to deploy AI inside their team — not just personally. Two weeks of practical workflow design.

We end with a written AI playbook for your specific business: when to use AI, what to keep human, security + IP guardrails, team training plans, and a tooling stack you can roll out next week.

Custom-fit playbooks for

  • Customer support automation that doesn't feel robotic
  • Marketing content production at scale
  • Sales workflows: discovery → proposal → close
  • Operations: meeting notes, summaries, reporting
  • Hiring + onboarding workflows

Outcomes

What you’ll walk away with

Every outcome below is something a graduate can demonstrate on the last day of class — not a vague promise.

  • 01

    Build production-ready AI-powered features

  • 02

    Write prompts, evals, and guardrails like a senior

  • 03

    Ship a portfolio AI project that demonstrates real skill

Syllabus

How the 2 weeks actually unfold

We move in deliberate phases. Each one builds on the last, so by week 2you’re working on real briefs — not still typing your first hello-world.

  1. W1

    Prompt patterns that work

    Zero/few-shot, chain-of-thought, structured output.

    You can…
    • Apply 5 production prompt patterns
    • Get structured output (JSON) reliably
    • Debug bad outputs systematically
  2. W2

    Team playbook + guardrails

    IP, hallucinations, training, rollout.

    You can…
    • Write a team AI playbook
    • Guardrail AI use for compliance
    • Roll out AI workflows to a team

Who this is for

A great fit if you’re…

  • Engineers wanting to add AI to their stack
  • Founders building AI-first products
  • Analysts moving from spreadsheets to Python

Tools you’ll use

The stack you’ll get fluent in

  • OpenAI, Anthropic, Google APIs
  • Python, Jupyter, Pandas, scikit-learn
  • Vector databases, RAG pipelines

Format: 2 live sessions + 1 lab per week. Heavy hands-on coding.

FAQ

Questions students ask before joining

Do I need to know Python?+

Helpful but not required for the intro courses. The Data and LLM courses assume Python basics.

Do I need a GPU?+

No — we use cloud APIs. Your laptop can be modest.

Will I use my own data?+

You can — the LLM and Data courses both encourage bringing your own dataset for the final project.

Are these tools free to use?+

Most have free tiers. We provide API credits during cohort for paid features.

Also in AI & Data

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Python for Data Analysis

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Next step

4-minute application. Quote in 24 hours.

Tell us about your background and goals. We’ll send the syllabus, fee plan, and a cohort that fits.

Apply for Prompt Engineering for SMEs →