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Data Science Short Course (in collaboration with DSM)

Build solid foundational skills across the data science skill spectrum

In this short course, running 2 nights a week for 4 weeks, you will build solid foundational skills from across the data science skill spectrum. The intention of the course is to make you comfortable using several widely used, cutting-edge techniques, but also give you a deep understanding of the fundamental issues in data science. This will make learning new techniques on your own time much easier, long after you have finished the course.

The course is highly practical. You will work through real live examples using a variety of fun data sources, including transaction-level data from a café, a quarter of a million tax returns, and a survey of cheating spouses. If you have access to a dataset that you would like to use for your homework, bring it along!

A big part of learning data science is getting plugged into the community. To this end, you will be trying to solve difficult problems with other interesting people in the class

Testimonials

"As a non-statistical person, the course was a great way to immerse me in data exploration, understand new methods and build my knowledge to deal better with technical resources & data analysts" - Craig (August Class, 2015).

"Great, enthusiastic presenter. Good teaching style: short bursts of lecturing followed by exercises" - Alex (August Class, 2015).




Instructors

Hugh Parsonage

What to Bring

Laptop

Week One: Data Munging

  • More advanced use of dplyr, data.table, and data reshaping
  • ‍More advanced use of ggplot2

Week Two: Prediction

  • Introduction to predictive modelling
  • Structural modelling vs machine learning 
  • Predicting different data types
  • Building a predictive model using linear regression 
  • A brief introduction to Bayesian modelling
  • Classification and regression trees

Week Three: Evaluation

  • Overfitting
  • Training vs test error
  • Cross-validation

Week Four:More Advanced Predictions

  • ‍Shrinkage methods, ridge regression, the lasso
  • Smoothing splines
  • ‍Random forests and boosting
  • ‍Variable importance

WHAT's NEXT?

LOCATION
Collective Campus

1/20 Queen St, Melbourne 3000

SCHEDULE
  • Tuesday, 1st November  - Thursday, 24th November

    Every Tuesday & Thursday, 6:00 PM - 8:30 PM

COST
  • All Access Pass: $995

    Early Bird All Access Pass: $945 (sold out)

    Super Early Bird: $895 (sold out)

ENROL
Enrol

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