CA$2,500

Data Exploration Bootcamp with Python (Private class for 2 people)

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18 Shorncliffe, Ave

Toronto, Ontario M5P 2V6

Canada

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Description

This bootcamp is designed to introduce you to data exploration using the Python programming language. Through this intense, weeklong program you will master the skills necessary to manipulate, visualize and explore datasets to extract valuable insights.

Expert Instructor

This course is taught by Ted Petrou, an expert in exploring data with Python through Pandas. He is the author of the newly released Pandas Cookbook, a thorough step-by-step guide to accomplish a variety of data analysis tasks with Pandas. Ted is also speaking at the upcoming NYC PyData Conference during the last week of November.

Private, Personalized Class

There will only be two students for the entire week of the class. This means you will get personalized attention and all your questions answered immediately. You will feel free to ask any questions you have without hesitation. Ted is an enthusiastic instructor and will help you along your journey long after the course has completed.

Is this course for you?

If you are excited about the world of machine learning and data science but have yet to fully dive in, this course will catapult your skills so that you can smoothly transition into it. Data exploration is the foundation for all good data analysis and where the vast majority of time is spent for data scientists. No prior programming experience is needed as a thorough introduction to Python will be given in a pre-course assignment.

When

Dec 11th - 15th: 9 a.m. - 5 p.m.

Structure of Course

Learning is accomplished by working through difficult assignments and receiving and reviewing modeled solutions. Using a 'flipped classroom', students will prepare and read each day's material before coming to class. In class, students will rotate from instructor guided lessons to student-focused exercises and projects. The instructor will personally review code and give feedback for course assignments. Approximately 300 short answer questions with detailed solutions will be available. No more than 10 students will be enrolled in the class ensuring personalized learning and participation.

Syllabus

Before the Course:

Students will need to set aside 20-30 hours to set up the programming environment and to complete a thorough overview of the fundamentals of Python. An additional class will be held before the bootcamp to ensure both students are completing this assignment.

Day 1: Introduction to Pandas

Perhaps the most popular and widely used open-source data wrangling tool of the times, the Pandas library and its main data structures, the Series and DataFrame will be introduced. We will learn how to select subsets of data in a variety of ways.

Day 2: Split-Apply-Combine

Insights within datasets are often hidden amongst different groupings. The split-apply-combine paradigm is the fundamental procedure to explore differences amongst groups within datasets.

Day 3: Tidy Data

Real-world data is messy and not immediately available for aggregation, visualization or machine learning. Identifying messy data and transforming it into tidy data (as described by Hadley Wickham) provides a structure to data for making further analysis easier.

Day 4: Exploratory Data Analysis

Exploratory data analysis is a process to gain understanding and intuition about datasets. Visualizations are the foundations of EDA and communicate the discoveries within. The Seaborn library works directly with tidy data to create effortless and elegant visualizations.

Day 5: Applied Machine Learning

After tidying, exploring and visualizing data, machine learning models can be applied to gain deeper insights into the data. Workflows for preparing, modeling, validating and predicting data with Python's powerful machine learning library scikit-learn will be built.

Post-Course Project

The intelligence provided by a data analysis needs to be communicated through a data product or report. Students will continue their progress by building and deploying a web application showcasing an end-to-end data analysis.

Instructor

Ted Petrou is the author of Pandas Cookbook and founder of Dunder Data. He worked as a data scientist at Schlumberger where he spent the vast majority of his time exploring data. Some of his projects include using targeted sentiment analysis to discover the root cause of part failure from engineer text, developing customized client/server dashboarding applications and real-time web services to avoid mispricing of sales items. Ted received his Masters degree in statistics from Rice University and used his analytical skills to play poker professionally and teach math before becoming a data scientist. Before moving to Toronto, he founded the Houston Data Science meetup group and held over 30 free tutorials for the public.

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Date and Time

Location

18 Shorncliffe, Ave

Toronto, Ontario M5P 2V6

Canada

View Map

Refund Policy

No Refunds

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