University of America › Departments › Data Science

📊 Department of
Data Science

Train to extract insight, build pipelines, and drive decisions through data. The DS Department equips students with the statistical, computational, and business skills to thrive in the data economy.

📊 Data Analytics 🤖 Machine Learning 🏗️ Data Engineering 📈 Business Intelligence 🧠 Deep Learning 🌐 Big Data
28
Core Courses
2
Degree Programs
6
Years Total Study
50%
Project Grade Weight
Degree Programs
BSc & MSc in Data Science
Two structured programs designed for different stages of your academic journey.

BSc Data Science

A comprehensive 4-year undergraduate program building expertise in data analysis, machine learning, and engineering.

Duration4 Years (8 Semesters)
Credits124
EntryHS Diploma or Grade 9+
Format100% Online
Year 1 — Foundations (Sem 1–2)
  • DS101 — Introduction to Data Science 4 cr
  • MATH101 — Calculus for Data Scientists 3 cr
  • MATH102 — Linear Algebra 3 cr
  • PROG101 — Python Programming 4 cr
  • STAT101 — Statistics Fundamentals 3 cr
  • DS102 — Data Wrangling & Visualization 4 cr
Year 2 — Core Skills (Sem 3–4)
  • DS201 — Machine Learning Fundamentals 4 cr
  • DS202 — Database Systems & SQL 3 cr
  • DS203 — Exploratory Data Analysis 3 cr
  • STAT201 — Probability Theory 3 cr
  • DS204 — Data Engineering Pipelines 4 cr
  • DS205 — Big Data Technologies 3 cr
Year 3 — Advanced Topics (Sem 5–6)
  • DS301 — Deep Learning 4 cr
  • DS302 — Natural Language Processing 4 cr
  • DS303 — Computer Vision 3 cr
  • DS304 — Time Series Analysis 3 cr
  • DS305 — Cloud Computing for DS 3 cr
  • DS306 — Ethics in Data Science 2 cr
Year 4 — Specialization & Capstone (Sem 7–8)
  • DS401 — Advanced ML & AI 4 cr
  • DS402 — Business Intelligence & Analytics 3 cr
  • DS403 — Research Methods 2 cr
  • DS404 — Capstone Project I 6 cr
  • DS405 — Capstone Project II 6 cr
  • ELEC1 — Elective (choose 1) 3 cr
Browse all DS BSc courses →

MSc Data Science

An advanced 2-year graduate program focused on research, large-scale systems, and original contribution to the field.

Duration2 Years (4 Semesters)
Credits64
EntryBSc in relevant field
Format100% Online
Semester 1 — Advanced Core
  • DS501 — Advanced Statistical Learning 4 cr
  • DS502 — Big Data Systems & Architecture 4 cr
  • DS503 — Research Methods in Data Science 3 cr
  • DS504 — Graduate Seminar I 1 cr
Semester 2 — Deep Specialization
  • DS505 — Deep Learning & Neural Networks 4 cr
  • DS506 — MLOps & Production Systems 4 cr
  • DS507 — Causal Inference 3 cr
  • DS508 — Thesis Proposal 2 cr
Semester 3 — Research & Industry
  • DS601 — Advanced Topics: Generative AI 3 cr
  • DS602 — Industry Collaboration Project 6 cr
  • DS603 — Thesis Research I 6 cr
Semester 4 — Thesis Defense
  • DS701 — Thesis Research II 6 cr
  • DS702 — Thesis Writing & Submission 4 cr
  • DS703 — Oral Defense & Publication 4 cr
Browse all DS MSc courses →
Course Spotlight
Featured Courses
A selection of the most impactful courses in the Data Science curriculum.
DS101
Introduction to Data Science
The complete data science lifecycle. From problem framing to insight delivery.
Year 14 CreditsPython
Projects: 3 × applied EDA tasks
Midterm: Conceptual + Python problems
Final: End-to-end analysis project
View Lecture 1 →
DS201
Machine Learning Fundamentals
Supervised, unsupervised, and semi-supervised learning. Model evaluation and selection.
Year 24 CreditsScikit-learn
Projects: Build 3 complete ML models
Midterm: Algorithm derivation
Final: Kaggle-style competition
View in Catalog →
DS301
Deep Learning
Neural networks from scratch to PyTorch. CNNs, RNNs, Transformers, and training techniques.
Year 34 CreditsPyTorch
Projects: Train 4 neural network models
Midterm: Architecture design questions
Final: Novel model implementation
View in Catalog →
DS302
Natural Language Processing
Text preprocessing, embeddings, transformers, and fine-tuning LLMs.
Year 34 CreditsHuggingFace
Projects: Sentiment analysis + chatbot build
Midterm: NLP pipeline questions
Final: Fine-tune a language model
View in Catalog →
DS404
Capstone Project I
Semester-long industry-scale data science project with real data and stakeholders.
Year 46 CreditsCapstone
Projects: THE project — full lifecycle DS system
Midterm: Progress presentation
Final: Full technical defense
View in Catalog →
DS505
Deep Learning & Neural Networks (MSc)
Advanced architectures: Vision Transformers, Diffusion Models, Graph Neural Networks.
MSc Sem 24 CreditsResearch
Projects: Reproduce a research paper in full
Midterm: Architecture analysis
Final: Novel architecture contribution
View in Catalog →
Grading System
How You're Assessed

Grade Weights

  • 📁 Projects: 50% — Hands-on applied work
  • 📝 Midterm: 20% — Mid-semester exam
  • 🎯 Final Exam: 30% — Comprehensive end-of-term
Projects 50%
Mid 20%
Final 30%

Project Structure

  • 2–4 projects per course per semester
  • Individual + team projects mixed
  • Graded on methodology, code, and results
  • Final capstone project replaces final exam in Year 4
  • All projects require a written report + code

Exam Format

  • Midterm: 90 minutes, open-notes allowed
  • Final: 3 hours, reference sheet allowed
  • Mix of MCQ, short-answer, and applied problems
  • Code-tracing and debugging questions included
  • Oral exam component in MSc year 2