Data Science

Question 1

What is data science

Answer 1

The study of data to extract meaningful insights for businesses, uses statistics, scientific computing, algorithms

Question 2

What can data science include

Answer 2

Data visualisation, machine learning, artificial intelligence, statistics, mathematics, software engineering

Question 3

What is a desired skill set for a data scientist

Answer 3

Communication, machine learning, statistics and probability, data visualisation, computer science and HPC, data wrangling and databases, data ethics and regulation, domain expertise

Question 4

What are some reasons why we may want to find patterns in data

Answer 4

We may want to find patterns in data to detect anomalies or outliers, cluster groups of similar things, identify relationships between things, or apply a label to an observation

Question 5

Why are identified patterns only useful if they allow us to do something

Answer 5

We want actionable insights that help us make decisions or take actions based on the data

Question 6

What is a common example of finding patterns in data

Answer 6

A common example of finding patterns in data is predicting whether an email is spam or not

Question 7

What kind of patterns/insights do we often want to find using data analysis

Answer 7

We often want to find complex patterns or insights in massive amounts of data that are not easily discoverable by humans

Question 8

Define Datum

Answer 8

A single piece of information

Question 9

What is datum in the context of data analysis

Answer 9

A datum if often an observation or measurement of something, recording information about that thing

Question 10

How is data impacted by the problem we are trying to solve

Answer 10

The type and amount of data we collect will depend on the problem we are trying to solve

Question 11

What is the “Age of Big Data” and how has it affected the value of data

Answer 11

A period where massive collections of data are obtained frequently. This has led to data being an expensive commodity and potentially sold to high bidders who would benefit from insights that data might hold

Question 12

What are some examples of different types of data that can be collected

Answer 12

Numerical data, text data and images

Question 13

What is atomic data

Answer 13

A primitive type that cannot be broken down into a smaller unit (Integer, Boolean, Characters) e.g. Your age is an atomic piece of data

Question 14

What is composite data

Answer 14

A composition or aggregation of data that can be broken down into smaller units (Strings, Records, Lists) e.g. your student record is a piece of composite data, collating your name, age, address, modules, …

Question 15

What is Quantitative Data/Numerical Data

Answer 15

A type of data that represents a numerical value which quantifies something

Question 16

Define Discrete values

Answer 16

Only made of discrete steps, cannot be subdivided, e.g. whole numbers

Question 17

Define Continuous values

Answer 17

Falls within a range, and can fall between discrete values, e.g. temperature

Question 18

Can numerical data be subdivided into discrete and continuous values

Answer 18

Yes they can

Question 19

Define Qualitative Data/Categorical Data

Answer 19

A type of data that represents a description or label that is not inherently numerical, e.g. postcode, module’s taken, name. Can be a number but isn’t anything quantifying

Question 20

Define Nominal Values

Answer 20

No natural order, can potentially be grouped, e.g. hair colour nationality, name

Question 21

Define Ordinal Values

Answer 21

Has some innate ordering, e.g. Not very likely, unlikely, neutral, likely, very likely

Question 22

What are some common programming languages used in data science

Answer 22

Python, R, C, and C++

Question 22

What are the pros of using pre-existing packages or frameworks in data science

Answer 22

It allows for faster implementation, and is maintained by others, which reduces risk

Question 23

What are some pre-existing packages in Python for data science

Answer 23

Scikit-learn, NumPy, Matplotlib, pandas, jupyter, and docker

Question 24

What are some subgroups of numerical data

Answer 24

Discrete values and continuous values

Question 25

What are some subgroups of categorical data

Answer 25

Nominal values and ordinal values

Question 26

What is dynamic typing in python

Answer 26

We check the type of an entity at runtime, rather than at compliation like in java

Question 27

What is procedural programming in python

Answer 27

We often write scripts, where steps/instructions are carried out one after the other until the program terminates