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Introduction to Data Science

  • Beginner
  • 18 and older
  • $3,500
  • 11 Broadway, New York, NY
  • 60 hours over 20 sessions
Introduction to Data Science

Start Dates (0)

  • $3,500
  • The Flatiron School @ 11 Broadway Ste 260, New York, NY 10004
  • 60 hours over 20 sessions
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Class Description

Description

What you'll learn in this data science course:

This part time course provides students with the skills to extract meaning from datasets too large for Excel. Over the course of two weekends, students will learn to gain customer insights by analyzing a public dataset with hundreds of thousands of records using the pandas library and Python.  

All Data Science students should feel comfortable using Excel for basic statistics. This includes concepts such as mean, mode, median, outliers and normal distributions. Students who are already comfortable with Python do not have to attend the Python portion of the course.

Curriculum:
  • Python - Learn the basics of expressing with Python with a focus on what's most important for data science.
  • Pandas - Create charts, manipulate data with ease and run statistical inference on any part of your dataset with this very popular stats library.

  • Data Science - Learn the skills of massaging data into the format needed as well as deciding how and what tools to apply to get the most out of your data.
We teach the Data Science skills employers value.

Pre-requisite:
All Data Science students should feel comfortable using Excel for basic statistics.

Refund Policy

Due to the high costs of hardware, software, facilities and staff resources a non-refundable, non-transferable 25% of tuition is required per course, per participant.

  • Payments, less the non-refundable amount, are refundable until 4 weeks (31 days) prior to the start of the confirmed course start date.
  • No refund will be issued for cancellations or withdrawals within the 31 days of the start of the confirmed course start date.
A $35 cancellation fee will be applied to all refunds.

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The Flatiron School

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