Data science, AI, machine learning and deep learning
Data science means using data to answer a useful question. A good answer explains what the data show and what they cannot show.
Data science uses data to answer questions, quantify uncertainty and support decisions. AI is the broader aim of building systems with behaviours associated with intelligence. Machine learning is a way to learn patterns from data; deep learning is a family of machine-learning methods based on neural networks. Data science can use these methods, but cleaning a registry or comparing distributions can be valuable without a predictive model.
The Week 1 gallery illustrates transferable lessons: maps can expose spatial patterns; failure-only records omit a necessary denominator; a search-based prediction system needs monitoring as behaviour changes; operational or satellite records may answer a later question; fraud or screening thresholds trade different mistakes; recommendation, travel-time, language and irrigation systems all depend on what their recorded signals mean. Focus on these reasoning lessons rather than memorising historical dates.
Sources: W1 PDF pp. 3, 13-17, 22-30, 32-53, 57-60; L1 Parts 1-5.
Practice problems
Supplementary study questions on the lecture concepts — not verbatim exam questions. Each answer counts toward spaced review.
1. Conceptual understanding
Definitions and distinctions.
Which statement best describes data science?
Which relationship is correct?
2. Application
Apply the concept to a case or calculation.
A teacher first chooses a complex model, then looks for a question it can answer. What should improve?
Which task is mainly descriptive?
3. Interpretation and limitations
Evaluate assumptions and justify conclusions.
An analysis ends with a correct chart but no explanation. What is still needed?
A data check reveals that half the expected students are absent. What is a useful next step?
Explain it in writing
Self-checked, not marked. Write a few sentences, then compare with the example answer. Your writing is saved as you type.
Show an example answer
Count missing assignments by class, check that each row represents one assignment, and report which classes may need a review. A descriptive table can be useful.
Check: did you answer the question, use evidence or working, and avoid claiming more than the evidence supports?
Show an example answer
AI is the broad idea of computer systems carrying out intelligent tasks. Machine learning learns patterns from data. Deep learning is a family of machine-learning methods using neural networks.
Check: did you answer the question, use evidence or working, and avoid claiming more than the evidence supports?