UUY-DTS 1113 units100 LevelFirst Semester

Fundamentals of Data Science

B.Sc. Data Science, University of Uyo

UUY-DTS 111 (Fundamentals of Data Science) is a 3-unit, 100 Level course taught in the First Semester at the University of Uyo, Akwa Ibom State, Nigeria.

Your orientation to the discipline: what data science actually is, what a data scientist does day to day, and the end-to-end lifecycle of a data project from question to deployed insight. Heavily practical — you will handle real datasets in your first semester.

On Areté, UUY-DTS 111 comes with

  • 3 recommended textbooks
  • an AI tutor that has read this course’s outline and notes
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Course outline

  1. 01What data science is: the intersection of statistics, computing and domain knowledge
  2. 02Roles in the field: data analyst, data scientist, data engineer, ML engineer
  3. 03The data science lifecycle: problem framing, collection, cleaning, exploration, modelling, communication, deployment
  4. 04Types of data: structured, semi-structured and unstructured; quantitative vs qualitative
  5. 05Data sources: surveys, sensors, transactions, logs, web scraping, open data portals
  6. 06Data quality: missing values, duplicates, outliers, inconsistent coding
  7. 07Exploratory data analysis and basic visualisation
  8. 08Tools of the trade: spreadsheets, Python/R notebooks, SQL, version control
  9. 09Case studies of data science in health, agriculture, finance and government in Nigeria

Recommended textbooks

  • Data Science from Scratch — Joel Grus

    2nd ed. — builds every idea from first principles in plain Python

  • R for Data Science — Hadley Wickham & Garrett Grolemund

    2nd ed. — free at r4ds.hadley.nz; the best lifecycle overview anywhere

  • Doing Data Science — Cathy O'Neil & Rachel Schutt

    Strong on what the job actually looks like

How to pass UUY-DTS 111

  • Pick one real dataset in your first month (Nigeria open data, NBS, or a Kaggle set) and carry it through every stage of the lifecycle as you learn each stage
  • Cleaning is 70–80% of real data work and is barely 10% of the syllabus — over-invest in it anyway
  • Start a public GitHub repository now; by 400 Level it is the portfolio that gets you hired
  • Learn to state the business question before touching the data — an elegant model answering the wrong question scores zero

UUY-DTS 111 — questions and answers

What is UUY-DTS 111 at the University of Uyo?
UUY-DTS 111 (Fundamentals of Data Science) is a 3-unit, 100 Level course taught in the First Semester at the University of Uyo, Akwa Ibom State, Nigeria. Your orientation to the discipline: what data science actually is, what a data scientist does day to day, and the end-to-end lifecycle of a data project from question to deployed insight. Heavily practical — you will handle real datasets in your first semester.
What topics are covered in UUY-DTS 111?
The UUY-DTS 111 outline covers 9 topics: What data science is: the intersection of statistics, computing and domain knowledge; Roles in the field: data analyst, data scientist, data engineer, ML engineer; The data science lifecycle: problem framing, collection, cleaning, exploration, modelling, communication, deployment; Types of data: structured, semi-structured and unstructured; quantitative vs qualitative; Data sources: surveys, sensors, transactions, logs, web scraping, open data portals; Data quality: missing values, duplicates, outliers, inconsistent coding; Exploratory data analysis and basic visualisation; Tools of the trade: spreadsheets, Python/R notebooks, SQL, version control; Case studies of data science in health, agriculture, finance and government in Nigeria.
What textbooks are recommended for UUY-DTS 111?
Recommended reading for UUY-DTS 111: Data Science from Scratch by Joel Grus; R for Data Science by Hadley Wickham & Garrett Grolemund; Doing Data Science by Cathy O'Neil & Rachel Schutt.
How do I pass UUY-DTS 111?
Pick one real dataset in your first month (Nigeria open data, NBS, or a Kaggle set) and carry it through every stage of the lifecycle as you learn each stage Cleaning is 70–80% of real data work and is barely 10% of the syllabus — over-invest in it anyway Start a public GitHub repository now; by 400 Level it is the portfolio that gets you hired Learn to state the business question before touching the data — an elegant model answering the wrong question scores zero
Where can I find UUY-DTS 111 lecture notes and past questions?
Areté (https://www.aretecyb.tech/courses/uuy-dts-111) carries 3 recommended textbooks for UUY-DTS 111, 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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