Sep 23–26, 2019

Hands-on data science with Python

Michael Cullan (The Data Incubator)
9:00am—5:00pm Monday, September 23—Tuesday, September 24
Location: 1A 15/16
Average rating: ***..
(3.00, 2 ratings)

Participants should plan to attend both days of training course. Note: to attend training courses, you must be registered for a Platinum or Training pass; does not include access to tutorials on Tuesday.

Michael Cullan walks you through developing a machine learning pipeline from prototyping to production. You'll learn about data cleaning, feature engineering, model building and evaluation, and deployment and then extend these models into two applications from real-world datasets. All work will be done in Python.

What you'll learn, and how you can apply it

  • Understand the basics of machine learning, feature engineering, anomaly detection, and recommendation engines
  • Explore scikit-learn fundamentals
  • Learn to create machine learning processes with scikit-learn
  • Evaluate and apply machine learning to real-world problems

Who is this presentation for?

  • You're a software engineer or programmer with a background in Python, and you want to develop a basic understanding of machine learning.
  • You're in a nontechnical role, and you want to more effectively communicate about machine learning with the engineers and data scientists in your company.




  • A working knowledge of Python
  • Familiarity with pandas (useful but not required)


Day 1: Anomaly detection

  • Data format and goal
  • Limitations of time series data
  • Detrending and seasonality
  • Windowing and local scores
  • Setting thresholds for classification
  • Online learning

Day 2: Recommendation engines

  • Overview of data and its wrangling
  • Item-item correlations and finding similar items
  • User similarity and predicting user ratings
  • Collaborative filtering
  • Evaluating model performance

About your instructor

Photo of Michael Cullan

Michael Cullan is a data scientist in residence at the Data Incubator, where he combines a passion for teaching and statistical programming. He has three years of teaching experience in academic and professional settings and four years of research experience spanning topics in nonparametric statistics, applied mathematics, and artificial intelligence. He holds a master’s degree in statistics.

Conference registration

Get the Platinum pass or the Training pass to add this course to your package.

Comments on this page are now closed.


Picture of Michael Cullan
Michael Cullan | Data Scientist in Residence
09/20/2019 8:15am EDT

Hi Rachana,
Attendees will all be given a login for a JupyterHub pod containing lecture and lab notebooks, so you’ll be all set as long as you have an internet connection!
Michael Cullan

rachana gurrapu | Lead Analytics Engineer
09/20/2019 5:31am EDT

Hi Michael,

Are there any notebooks we might have to download before or any laptop configurations needed for a better learning experience.


Rachana Gurrapu

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