Data SCIENCE
HONG KONG
Small Data is the real Revolution.
... you can join from the comfort of your laptop.
Not centralized "big iron" but
decentralized data wrangling.
the next decade belongs to distributed
models, not centralized ones; to
collaboration, not control; and to
Small Data, not Big Data.
Rufus Pollock
THAT's Why for us
DATA SCIENCE IS
about data literacy
(relevant regardless of size)
our STUDENTS Are individuals
who want to
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Learn relevant 21st century skills
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Increase earning potential
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Career change
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Become more marketable
How it works?
Practical, real-world, hands
on instruction.
WELCOME TO
"General Assembly is an educational institution that transforms thinkers into creators through education in technology, business and design"
sweet, sweet, data
dATA SCIeNCE USES
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Stack Overflow tag recommendation and response time prediction
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Locating ethnic food in ethnic neighbourhoods
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Building optimal NBA teams
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Recommending new musical artists
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Prioritize emergency calls in Seattle
- Finding the right college for you
DATA Science WORK FLOW
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Acquire
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Parse
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Filter
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Mine
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Represent
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Refine
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Interact
DATA SCIENTISTS
Qualities
- Statistical and machine learning knowledge
- Engineering experience
- Academic curiosity
- Product sense
- Storytelling
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Cleverness
OUR SYLLABUS
UNIT 1: THE BASICS
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Python for Data Science.
- Machine learning (linear models)
- Data Visualisation
UNIT 2: TEXT TO DATABASE
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Data Acquisition, Manipulation and Preparation
- MongoDB + JSON
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API Requests
- Python Pandas
UNIT 3: SUPERVISED LEARNING
- Regression Techniques
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Regression and Regularisation
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Logistic regression
- Classification Techniques
- Naive Bayes
- Decision Trees
- Support Vector Machines
- Regression Techniques
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Regression and Regularisation
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Logistic regression
- Classification Techniques
- Naive Bayes
- Decision Trees
- Support Vector Machines
UNIT 4: real world problems
- Unsupervised learning
- Classification Systems
- Recommendation Systems
- Decision Systems
- Unsupervised learning
- Classification Systems
- Recommendation Systems
- Decision Systems
UNIT 5: Your Projects
UNIT 5: Your Projects
MAKE.03 Open Gov HACKATHON
The first 6 weeks of the course!
OPEN DATA HONG KONG
COURSE DETAILS
Instructor
- Founder, Open Data HK (2013)
- FEWD Instructor, GA (2013)
- Analytical Engineer, Demyst (2013)
- Data Architect, DAnalytics (2012)
Data science course details
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Runs from 28 April to 9 July , 2014
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Meets Mondays & Wednesdays from 19:00 -22:00
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Classes held at Garage, Central
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Expected class size is ~15 students
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Tuition is HK$ 28,000
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Payment plan is available
- Application deadline on 15 April
General Assembly Benefits
- Practical, dynamic content developed by curriculum design team & adapted by local instructors
- Free 3 month membership to GA Front Row
- Final project/portfolio
- Permanent access to all course resources
- Strong, global, diverse community of makers
- Personalized instruction and support
BENEFITS
Is it for me?
Commitment
"Data Science involves the programmatic implementation of statistical models"
- Good grasp of statistics required
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Some knowledge of Python beneficial
- 10 hours of pre-course work
- 4 hours of weekly homework
System Requirements
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Bring Your Own Laptop
- Linux or OSX are preferred
- Windows can come too
- Python v2.7.6
- Chrome Browser
Question?
Small Data
By Mart van de Ven
Small Data
Info Session for General Assembly's Data Science course taught in Hong Kong by Mart van de Ven.
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