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Data Science (Part-Time)

Gain the skills needed to excel in the field of data science and machine learning with the General Assembly's practical and hands-on course. Learn to analyze and model data using Python and effectively communicate your insights to both technical and non-technical audiences. Accelerate your career in just ten weeks.

  • Level All levels
  • Age 18 and older
  • Price $4,500
  • Location Mentor-guided, online class

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Start Dates (5)

  • $4,500
  • Mentor-guided, online class
Show all 20 sessions
  • Tue, Mar 12 at 10:00am - 1:00pm
  • Thu, Mar 14 at 10:00am - 1:00pm
  • Tue, Mar 19 at 10:00am - 1:00pm
  • Thu, Mar 21 at 10:00am - 1:00pm
  • Tue, Mar 26 at 10:00am - 1:00pm
  • Thu, Mar 28 at 10:00am - 1:00pm
  • Tue, Apr 02 at 10:00am - 1:00pm
  • Thu, Apr 04 at 10:00am - 1:00pm
  • Tue, Apr 09 at 10:00am - 1:00pm
  • Thu, Apr 11 at 10:00am - 1:00pm
  • Tue, Apr 16 at 10:00am - 1:00pm
  • Thu, Apr 18 at 10:00am - 1:00pm
  • Tue, Apr 23 at 10:00am - 1:00pm
  • Thu, Apr 25 at 10:00am - 1:00pm
  • Tue, Apr 30 at 10:00am - 1:00pm
  • Thu, May 02 at 10:00am - 1:00pm
  • Tue, May 07 at 10:00am - 1:00pm
  • Thu, May 09 at 10:00am - 1:00pm
  • Tue, May 14 at 10:00am - 1:00pm
  • Thu, May 16 at 10:00am - 1:00pm
Show all 20 sessions
  • Mon, Apr 15 at 10:00am - 1:00pm
  • Wed, Apr 17 at 10:00am - 1:00pm
  • Mon, Apr 22 at 10:00am - 1:00pm
  • Wed, Apr 24 at 10:00am - 1:00pm
  • Mon, Apr 29 at 10:00am - 1:00pm
  • Wed, May 01 at 10:00am - 1:00pm
  • Mon, May 06 at 10:00am - 1:00pm
  • Wed, May 08 at 10:00am - 1:00pm
  • Mon, May 13 at 10:00am - 1:00pm
  • Wed, May 15 at 10:00am - 1:00pm
  • Wed, May 22 at 10:00am - 1:00pm
  • Wed, May 29 at 10:00am - 1:00pm
  • Mon, Jun 03 at 10:00am - 1:00pm
  • Wed, Jun 05 at 10:00am - 1:00pm
  • Mon, Jun 10 at 10:00am - 1:00pm
  • Wed, Jun 12 at 10:00am - 1:00pm
  • Mon, Jun 17 at 10:00am - 1:00pm
  • Mon, Jun 24 at 10:00am - 1:00pm
  • Wed, Jun 26 at 10:00am - 1:00pm
  • Mon, Jul 08 at 10:00am - 1:00pm
Notes
Except: May 20, May 27, Jun 19, Jul 1, Jul 3
Show all 25 sessions
  • Mon, Apr 15 at 10:00am - 1:00pm
  • Wed, Apr 17 at 10:00am - 1:00pm
  • Mon, Apr 22 at 10:00am - 1:00pm
  • Wed, Apr 24 at 10:00am - 1:00pm
  • Mon, Apr 29 at 10:00am - 1:00pm
  • Wed, May 01 at 10:00am - 1:00pm
  • Mon, May 06 at 10:00am - 1:00pm
  • Wed, May 08 at 10:00am - 1:00pm
  • Mon, May 13 at 10:00am - 1:00pm
  • Wed, May 15 at 10:00am - 1:00pm
  • Mon, May 20 at 10:00am - 1:00pm
  • Wed, May 22 at 10:00am - 1:00pm
  • Mon, May 27 at 10:00am - 1:00pm
  • Wed, May 29 at 10:00am - 1:00pm
  • Mon, Jun 03 at 10:00am - 1:00pm
  • Wed, Jun 05 at 10:00am - 1:00pm
  • Mon, Jun 10 at 10:00am - 1:00pm
  • Wed, Jun 12 at 10:00am - 1:00pm
  • Mon, Jun 17 at 10:00am - 1:00pm
  • Wed, Jun 19 at 10:00am - 1:00pm
  • Mon, Jun 24 at 10:00am - 1:00pm
  • Wed, Jun 26 at 10:00am - 1:00pm
  • Mon, Jul 01 at 10:00am - 1:00pm
  • Wed, Jul 03 at 10:00am - 1:00pm
  • Mon, Jul 08 at 10:00am - 1:00pm
Notes
Except: May 20, May 27, Jun 19, Jul 1, Jul 3
Show all 20 sessions
  • Tue, Jun 18 at 10:00am - 1:00pm
  • Thu, Jun 20 at 10:00am - 1:00pm
  • Tue, Jun 25 at 10:00am - 1:00pm
  • Thu, Jun 27 at 10:00am - 1:00pm
  • Tue, Jul 09 at 10:00am - 1:00pm
  • Thu, Jul 11 at 10:00am - 1:00pm
  • Tue, Jul 16 at 10:00am - 1:00pm
  • Thu, Jul 18 at 10:00am - 1:00pm
  • Tue, Jul 23 at 10:00am - 1:00pm
  • Thu, Jul 25 at 10:00am - 1:00pm
  • Tue, Jul 30 at 10:00am - 1:00pm
  • Thu, Aug 01 at 10:00am - 1:00pm
  • Tue, Aug 06 at 10:00am - 1:00pm
  • Thu, Aug 08 at 10:00am - 1:00pm
  • Tue, Aug 13 at 10:00am - 1:00pm
  • Thu, Aug 15 at 10:00am - 1:00pm
  • Tue, Aug 20 at 10:00am - 1:00pm
  • Thu, Aug 22 at 10:00am - 1:00pm
  • Tue, Aug 27 at 10:00am - 1:00pm
  • Thu, Aug 29 at 10:00am - 1:00pm
Notes
Except: Jul 2, Jul 4
Show all 22 sessions
  • Tue, Jun 18 at 10:00am - 1:00pm
  • Thu, Jun 20 at 10:00am - 1:00pm
  • Tue, Jun 25 at 10:00am - 1:00pm
  • Thu, Jun 27 at 10:00am - 1:00pm
  • Tue, Jul 02 at 10:00am - 1:00pm
  • Thu, Jul 04 at 10:00am - 1:00pm
  • Tue, Jul 09 at 10:00am - 1:00pm
  • Thu, Jul 11 at 10:00am - 1:00pm
  • Tue, Jul 16 at 10:00am - 1:00pm
  • Thu, Jul 18 at 10:00am - 1:00pm
  • Tue, Jul 23 at 10:00am - 1:00pm
  • Thu, Jul 25 at 10:00am - 1:00pm
  • Tue, Jul 30 at 10:00am - 1:00pm
  • Thu, Aug 01 at 10:00am - 1:00pm
  • Tue, Aug 06 at 10:00am - 1:00pm
  • Thu, Aug 08 at 10:00am - 1:00pm
  • Tue, Aug 13 at 10:00am - 1:00pm
  • Thu, Aug 15 at 10:00am - 1:00pm
  • Tue, Aug 20 at 10:00am - 1:00pm
  • Thu, Aug 22 at 10:00am - 1:00pm
  • Tue, Aug 27 at 10:00am - 1:00pm
  • Thu, Aug 29 at 10:00am - 1:00pm
Notes
Except: Jul 2, Jul 4
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Class Description

Description

What you'll learn in this data science course:

Get the skills needed to advance your career in Data Science, in as little as ten weeks. There are some prerequisites: being comfortable with programming fundamentals, core Python syntax and basic statistics.

General Assembly’s Data Science part-time course is a practical introduction to the interdisciplinary field of data science and machine learning, which lies at the intersection of computer science, statistics, and business. You will learn to use the Python programming language to acquire, parse, and model data for informing business strategy.

Who's It For?

This is a fast-paced course with some prerequisites. Students should be comfortable with programming fundamentals, core Python syntax, and basic statistics. There is an option to complete up to 25 hours of online preparatory lessons. The General Assembly Admissions team can discuss your background and learning goals to advise if this course is a good fit for you.

What You'll Learn:

A significant portion of the course is a hands- on approach to fundamental modeling techniques and machine learning algorithms. You’ll also practice communicating your results and insights by compiling technical documentation and a stakeholder presentation. Throughout this expert-designed program, you’ll:

  • Perform exploratory data analysis with Python.
  • Build and refine machine learning models to predict patterns from data sets.
  • Communicate data-driven insights to technical and non-technical audiences alike.
  • Apply what you’ve learned to create a portfolio project: a predictive model that addresses a real-world data problem.

Duration and Study Load:

  • 10 weeks part-time
  • You will be expected to spend time working on homework and projects outside of class hours each week, but the workload is designed to be manageable alongside a full-time job.

Payment Options:

General Assembly offers a variety of different financing options, including installment plans, student loans, income share loans and tuition discounts so you can focus on what counts — your education.

Map:

GA classes are online via Zoom and Slack to reflect the most common workplace setup you’ll find once you land your tech job. You will take instructor led sessions and self paced sessions, always with access to real time Instructor feedback. Career Coach support is available from day one and until you find a job both.


Remote Learning

This course is available for "remote" learning and will be available to anyone with access to an internet device with a microphone (this includes most models of computers, tablets). Classes will take place with a "Live" instructor at the date/times listed below.

Upon registration, the instructor will send along additional information about how to log-on and participate in the class.

School Notes:
For students enrolling in 12 week part time and immersive classes, it is not recommended that you book more than one class simultaneously.

Refund Policy

If you can't make it to a class/workshop, please email us at [email protected] at least 7 days before the scheduled event date. No refunds will be given after this timeframe.


In any event where a customer wants to cancel their enrollment and is eligible for a full refund, a 5% processing fee will be deducted from the refund amount.

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