DTS 4262 units400 LevelSecond Semester

Data Science Innovation and Entrepreneurship

B.Sc. Data Science, University of Uyo

DTS 426 (Data Science Innovation and Entrepreneurship) is a 2-unit, 400 Level course taught in the Second Semester at the University of Uyo, Akwa Ibom State, Nigeria.

Entrepreneurship specific to data: what makes a data product commercially viable, how data businesses are structured, and how to price, protect and scale an offering built on data and models.

On Areté, DTS 426 comes with

  • 2 recommended textbooks
  • an AI tutor that has read this course’s outline and notes
Sign in to study DTS 426

Free for University of Uyo students — sign in with your email, no password.

Course outline

  1. 01The data product landscape: analytics services, embedded models, data marketplaces, decision tools
  2. 02Identifying commercially viable data opportunities; the value of a prediction
  3. 03Data as an asset: acquisition, ownership, licensing and the data moat
  4. 04Business models for data products: subscription, usage-based, freemium, marketplace
  5. 05Costing a data product: infrastructure, compute, storage and human-in-the-loop costs
  6. 06Building an MVP for a data product; when a spreadsheet is the right first version
  7. 07Intellectual property for data and models; trade secrets vs patents
  8. 08Regulatory constraints on data businesses in Nigeria
  9. 09Scaling: from a one-off analysis to a repeatable, automated service

Recommended textbooks

  • Data Science for Business — Foster Provost & Tom Fawcett

    The core text for thinking commercially about data

  • Prediction Machines — Agrawal, Gans & Goldfarb

    On the economics of AI — what falling prediction cost changes about a business

How to pass DTS 426

  • The central question of this course is "who pays, and why?" — a technically excellent model with no buyer is a hobby
  • Prediction Machines' framing (AI reduces the cost of prediction; judgement becomes the scarce input) is a genuinely useful lens for essay answers
  • Cost out the infrastructure for your idea honestly; cloud compute has bankrupted more data startups than bad models have
  • Combine this with ENT 321 and DTS 428 — one coherent venture built on your project is worth far more than three disconnected submissions

DTS 426 — questions and answers

What is DTS 426 at the University of Uyo?
DTS 426 (Data Science Innovation and Entrepreneurship) is a 2-unit, 400 Level course taught in the Second Semester at the University of Uyo, Akwa Ibom State, Nigeria. Entrepreneurship specific to data: what makes a data product commercially viable, how data businesses are structured, and how to price, protect and scale an offering built on data and models.
What topics are covered in DTS 426?
The DTS 426 outline covers 9 topics: The data product landscape: analytics services, embedded models, data marketplaces, decision tools; Identifying commercially viable data opportunities; the value of a prediction; Data as an asset: acquisition, ownership, licensing and the data moat; Business models for data products: subscription, usage-based, freemium, marketplace; Costing a data product: infrastructure, compute, storage and human-in-the-loop costs; Building an MVP for a data product; when a spreadsheet is the right first version; Intellectual property for data and models; trade secrets vs patents; Regulatory constraints on data businesses in Nigeria; Scaling: from a one-off analysis to a repeatable, automated service.
What textbooks are recommended for DTS 426?
Recommended reading for DTS 426: Data Science for Business by Foster Provost & Tom Fawcett; Prediction Machines by Agrawal, Gans & Goldfarb.
How do I pass DTS 426?
The central question of this course is "who pays, and why?" — a technically excellent model with no buyer is a hobby Prediction Machines' framing (AI reduces the cost of prediction; judgement becomes the scarce input) is a genuinely useful lens for essay answers Cost out the infrastructure for your idea honestly; cloud compute has bankrupted more data startups than bad models have Combine this with ENT 321 and DTS 428 — one coherent venture built on your project is worth far more than three disconnected submissions
Where can I find DTS 426 lecture notes and past questions?
Areté (https://www.aretecyb.tech/courses/dts-426) carries 2 recommended textbooks for DTS 426, plus an AI tutor that has read the outline. It is free for University of Uyo students — sign in with your email, no password.

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