Python and Machine Learning Bootcamp Series
14

November 14 – November 15
2 Sessions

GA St. Louis (Livestream)

Online Class
Livestream
$375 USD
Regular Ticket
$375 USD
Total

Questions? Read our FAQs

Python and Machine Learning Bootcamp Series | November 14

Craig Sakuma Photo


Founder, QuantSprout

14

November 14 – November 15
2 Sessions

GA St. Louis (Livestream)

Online Class
Livestream
$375 USD
Regular Ticket
$375 USD
Total

Questions? Read our FAQs

About This Workshop Series

Machine Learning is perhaps the most powerful force in technology, and Python is perhaps the most popular language for doing it. This 2-day workshop helps students understand, build, and interpret machine learning models using the python ecosystem.

This workshop will introduce you to the most important machine learning concepts in a way that’s clear, accessible, and easy to put into action. With no assumed knowledge of Machine Learning, you’ll understand how to think about and interpret Machine Learning problems, and best practices for using the most popular machine learning techniques in a variety of domains.

It starts with the basics of Python’s major data science libraries (Numpy, Pandas, and SciKit Learn), and builds on these to help you implement state-of-the-art machine learning techniques on your own data.

Limited space available!

The well-being of our employees, students, clients, instructors, and guests is our number one priority here at General Assembly. We are monitoring the COVID-19 situation very carefully and are adjusting delivery of our programs.


Due to the current health concerns, all GA short-form events, workshops & bootcamps will temporarily be held online - including this one.


Registered students will be notified 24 hours in advance of this program with information on how to log in to the Zoom Meeting Room and other tools you’ll need for the session. Registration for this class will close 2 hours prior to the session start in order to allow all students ample opportunity to have the technology enabled.

Schedule

Nov 14
Saturday, 14 November 10 am – 5 pm CST Session I: Python-for-Data Basics, Machine Learning Introduction

Morning

  • Introduction to Numpy and Pandas.
  • Popular methods for handling and prepping your data.

Afternoon

  • Introduction to Machine Learning.
  • Regression.

Nov 15
Sunday, 15 November 10 am – 5 pm CST Session II: Machine Learning Continued, Bringing It All Together

Morning

    • Cross Validation.
    • Regularization.

    Afternoon

      • Classification.
      • Putting it all together.

Takeaways

In this workshop you'll learn :

  • How to use Numpy and Pandas to import and organize your data.
  • The different types of machine learning problems, and when to use different methods.
  • Best practices for prepping your data to make it Machine Learning ready.
  • Regression Algorithms, and how to use them to predict continuous data.
  • Classification algorithms, and how to use them to predict binary outcomes.
  • Relative strengths and weaknesses of different Machine learning techniques.
  • Best practices to make sure your models can handle data they haven’t seen before.
  • Advice on future learning paths depending on your desired career goals.
  • Visualize the results of your analysis.

Preparation

  • You will need access to a laptop or computer with a working webcam and microphone as well as a strong internet connection. Also with 5GB free space to install recommended tools:
    • Please have a copy of Anaconda installed on your computer, which can be downloaded here: (www.anaconda.com/distribution).
    • Familiarity with the core Python programming language, either with the Introduction to Python Bootcamp or similar experience. The Python For Data Bootcamp is recommended for maximum benefit, but not required.
    • This course will occur completely online using Zoom and Slack.
    • Course set up information will be emailed to all students signed up around 24 hours before (and again an hour before) your course launches.

About the Instructor

Craig Sakuma Photo

Founder,
QuantSprout

Craig has been a data science and analytics instructor at General Assembly since 2014 and he has over 2,000 hours of teaching experience. Prior to teaching at General Assembly, he worked as a data scientist at Euclid Analytics. Craig has also founded an e-commerce furniture business, Deal Decor, and worked as a consultant at the Boston Consulting Group. He has an engineering degree from Northwestern and an MBA from Wharton. For fun, Craig enjoys traveling and has spent a total of 5 years living overseas in three different countries.

Refund Policy

We understand that, sometimes, plans change. If you can no longer make it to a class or workshop, please email us at least 7 days before the scheduled event date. No refunds will be given to cancellations made within a week of the class or workshop.

Community Code of Conduct

Your registration for or attendance at any General Assembly offering indicates your agreement to abide by this Community Code of Conduct policy and its terms.

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