I've been creating cute little characters for as long as I can remember - and I absolutely love it. Over many years of trial and error, I've uncovered a few handy secrets that make it easier to draw cute cartoons. Now, I use those secrets to help over 9000 students discover their love of drawing 'kawaii' cute characters of their own!
In this lecture you'll learn all about the "Cute Ratio", which is a simple system I use to keep basic cartoon characters looking cute. By sticking to some simple rules, you too will be able to create kawaii styled cartoons in no time.
Warm-up is one of those things that nobody wants to do, but probably should. It gets you into the creative mood and gets you into the drawing groove. Don't underestimate the benefits of warming up!
Dozens of students asked what equipment I use when creating my characters, which is a great question, so I thought it was about time I answered. In this video I talk about my setup, but that doesn't mean you will need the same system or devices. The easiest and cheapest way to start is pencil and paper. This is the bare requirement. If you are wanting to explore the digital world of art creation, I recommend either an iPad with a stylus (because many people already own an iPad) or picking up an Intuos tablet to plug into your computer. This course was 90% created using Sketchbook Pro (ie. The screen you see in bulk of the lessons is Sketchbook Pro), which uses layers and has the ability to change brushes, etc. This is what I would recommend using when starting out. If you have any questions, feel free to ask.
Data Science Course Coverage
Duration – 120 Hours
BIG DATA ANALYTICS AND THE DATA SCIENTIST ROLE
The characteristics of Big Data
The practice of analytics
The role and required skills of a Data Scientist
DATA ANALYTICS LIFECYCLE
Model planning and building
Operationalizing a data analytics project
INITIAL ANALYSIS OF THE DATA
Using basic R commands to analyze data
Using statistical measures and visualization (Box, Scatter, Histogram, Bubble Charts) to understand data
The theory, process, and analysis of results to evaluate a model
ADVANCED ANALYTICS – THEORY AND METHODS
Hypothesis Tests (ANOVA, T Test, HoV, Chi-Sq, Logistic, Median tests)
Classification using Nearest Neighbours
Market Basket Analysis using Association rules
Naïve Bayesian classifiers
Neural Networks and Support Vector Machines
Time Series Analysis
Vector Space model
Stop Word Removal
Latent Semantic Indexing
Hierarchical Agglomerative Clustering
ADVANCED ANALYTICS FOR BIG DATA – TECHNOLOGY AND TOOLS