Summary Data Science Concepts

Grade

 50% exam
 50% final essay & weekly reports



Exam: multiple choice, 50 questions



1: Data science
Lecture a: data science intro
Why data science?

 Data science = DS
 World wide growing interest
 Affects many fields
 Exploding demand for data scientists



Explain data science as a discipline and in relation to other disciplines

,What is data science?

 Interdisciplinary field
 Concept to unify:
- Statistics
- Data analysis
- Machine learning
 Understand & analyse actual phenomena with data



DS vs business intelligence




Data science process

,Lecture b: ICT trends
Trends in ICT
 Discuss key ICT trends that have enabled DS



Industrial revolutions
 Invention of writing
 Printing press (1450)
 1st revolution (1784)
- Development of steam engine
- Transition from agrarian & rural society  to industrial & urban society
 2nd revolution (1890)
- Further advancements in manufacturing & production technology  assembly line
- Electricity
- Mass production
- Division of labour
 Disruptive innovation => creates new market & value network
- Eventually disrupts an existing market & value network
- Luddism => group of workers that destroyed machinery, they
feared that machines would replace their role
Malthusian catastrophe => human population grows
exponentially, resources grow much slower
- Near future: world has to face long periods of famine
- Escape: advances in technology triggered by industrial
revolution
 3rd revolution (1970s)
- Innovation of computer
- Digital revolution
- From mechanical & analogue technology  to digital electronics
- Automated info processing
- Neo luddism



Artificial intelligence
 Artificial intelligence (AI) => intelligence demonstrated by machines
 Study of intelligent agents
- Intelligent agent => any device that perceives its environment & takes actions that
maximize its chance of achieving its goals
- Simulation of human intelligence processes by machines
 Flourished in 1960s
- Advances in computing
 AI winter => reduced interest AI

, - Moore’s law => speed & capability of computers will increase, while their price decreases
- Supercomputer
- Human brain still more advanced & efficient than supercomputers
 Artificial narrow intelligence (ANI)
- Weak AI => equals or exceeds human intelligence for particular domain
- Not better in other domains
Artificial general intelligence (AGI)
- Strong AI => computer as smart as human & can so same intellectual tasks
- Turing test => test if it is AI or a human
Artificial superintelligence (ASI)
- Smarter than best human brains in every field
- Can range from little smarter than human to billions of times smarter
- Singularity => hypothetical point in time at which tech growth becomes uncontrollable &
irreversible  unforeseeable changes to human civilization



Pervasive computing & industry 4.0
 Exponential growth of computing
- More innovations
- Smart devices
 Waves of computing
1. Mainframe = 1 computer, many people
2. PC = 1 computer, 1 person
3. Ubiquitous = many computers, 1 person
 Smart products
- Monitoring, control, optimisation, autonomy
- Internet of things (IoT) => network of physical objects or things embedded with
electronics, software, sensors & network connectivity  enable data collection &
exchange
- IoT = physical object + controllers + sensors + actuators + internet
- Smart system architecture, smart farming
 4th industrial revolution (present)
- Agriculture tech
- Mass customisation with cyber-physical systems