CODE / DESIGN
HONG KONG
WELCOME TO
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.
"General Assembly is an educational institution that transforms thinkers into creators through education in technology, business and design"
GESTALT THEORY
"essence or shape of an entity's complete form"
organize visual elements into groups or unified wholes when certain principles are applied.
Similarity
Continuation
Closure
PROXIMITY
Figure/ ground
Symmetry and order
Save the details for last
GESTALT THEORY ELSEWHERE
"essence or shape of an entity's complete form"
organize any kind of elements into groups or unified wholes
when certain principles are applied.
INFORMATION THEORY
SIMILARITY
CONTINUATION
CLOSURE
PROXIMITY
FIGURE & GROUND
APPLICATION ARCHITECTURE
SIMILARITY
CONTINUATION
CLOSURE
PROXIMITY
FIGURE & GROUND
code demo
COURSE DETAILS
Linear Regression
MAKE.02 data.one app hackathon
Happening this wednesday + weekend
Qualities
- Statistical and machine learning knowledge
- Engineering experience
- Academic curiosity
- Product sense
- Storytelling
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Cleverness
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
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
Instructors
- Founder, Open Data HK (2013)
- FEWD Instructor, GA (2013)
- Analytical Engineer, Demyst (2013)
- Data Architect, DAnalytics (2012)
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
Is it for me?
Question?
Code for the Web. Design for People.
By Mart van de Ven
Code for the Web. Design for People.
Intro Session to the relationship between Code / Design for General Assembly's Front End Web Development course taught in Hong Kong by Mart van de Ven and Kit Yuen.
