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Recorded Webinar on Content Optimization with Multi-Armed Bandits & Python

Recorded Webinar on Content Optimization with Multi-Armed Bandits & Python

An overview of visualization in Python

An overview of visualization in Python

$35.00 | Enroll Now
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  • Overview
  • Learning Outcomes
  • Instructors
  • Syllabus
  • Dates
  • Prerequisites
  • Student Stories
  • FAQS
  • Requirements
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  • Overview
  • Learning Outcomes
  • Instructors
  • Syllabus
  • Dates
  • Prerequisites
  • Student Stories
  • FAQS
  • Requirements

Overview

Whenever you have multiple items to choose from, and are not sure which will result in the highest level of engagement or action, you have to make a choice. Multi-armed bandit, a branch of machine learning, is the fastest, most efficient method to make such a choice. This course examines a learn-as-you-go online learning method called reinforcement learning. Typical applications of multi-armed bandits include subject line testing for emails, button colors, page design/layout, and headline optimization. Anything you can test in the A/B fashion, you can do with bandits.

*This is a recorded webinar.

Intermediate Level Course
100% Online Courses
10-15 Study Hours Weekly
Expert Instructors
Tution-Back Guarantee

Learning Outcomes

This webinar examines reinforcement learning, a learn-as-you-go online learning method. You will learn different strategies for balancing exploration and exploitation in order to learn the best action to take when you initially know nothing about the payoffs of the different actions. You will learn how to implement bandit algorithms, tune them, and incorporate them into various apps.

  • Visualization in Python
  • Multi-Armed Bandits: a way to maximize reward given uncertain payoffs
  • Bandit algorithms: greedy, epsilon greedy, epsilon decreasing, exponential, upper confidence bound, and Bayesian
  • Data Types: Static, Restless, and Volatile data
  • Simulate bandit systems and visualize the results
  • Application 1: Command line application that uses bandits
  • Application 2: Website that uses bandits

Who Should Take This Course

Those with an interest in an overview of visualization in Python.

Instructors

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Course Syllabus

Week 1

Students should be familiar with any high-level programming language (C++, Java, Python).

Week 2

No instruction for this week.

Week 3

No instruction for this week.

Week 4

No instruction for this week.

Class Dates

2023

No classes scheduled at this time.

2024

No classes scheduled at this time.

2025

No classes scheduled at this time.

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Prerequisites

There are no prerequisites for this course.

Students should be familiar with any high-level programming language (C++, Java, Python).

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What Our Students Say​

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Chafik Abdellaoui

Excellent course!  Great support from Professor and Teaching Assistant!  Loved every single thing about this course and its content.

Chafik Abdellaoui
Business Systems Analyst IV at The Coca-Cola Company
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Yannick Messiaux

Very interesting course, excellent content. I'm looking forward using these concepts in my business soon.

Yannick Messiaux
AgieCharmilles Management SA
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We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.
  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.
Please see this page for more information.

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The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics. Please see our course search or knowledge center for more information.

Do your courses have for-credit options?

Our courses have several for-credit options:
  • Continuing education units (CEU)
  • College credit through The American Council on Education (ACE CREDIT)
  • Course credits that are transferable to the INFORMS Certified Analytics Professional (CAP®)
Please see our knowledge center for more information.

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The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information visit: https://www.schev.edu/ Please see our knowledge center for more information.

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Many of the courses at The Institute for Statistics Education have been recommended for C.E.U.’s, based on the length of the course (typically 5.0 CEUs for 4-week courses).

Visit our knowledge base and learn more.

FAQs + Knowledge Base

Related Courses

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Mapping in R Course

Introduction to Python Programming

This course will introduce you to the basics of programming in Python on either Windows or Mac platform.
Topic: Data Science, Using Python | Skill: Introductory | Credit Options: CEU
Class Start Dates: May 12, 2023, Sep 8, 2023, Jan 12, 2024

Additional Course Information

Organization of Course

Recorded webinar: content is delivered via video that you may view at your leisure. There is no homework and no instructor interaction.

Time Requirements

Approximately 3 hours

Course Text

No required text.  We have this suggested resource: When you launch Anaconda for Python, the Launcher program has many sample iPython notebooks on the right side. These are great tutorials for data analysis and visualization in python.

Software

You should have installed the Python 2.7 version of Anaconda, by Continuum Analytics. Useful links are below:

  1. Installing Python: https://wiki.python.org/moin/BeginnersGuide/Download
  2. Install virtualenv and virtualenvwrapper: http://docs.python-guide.org/en/latest/dev/virtualenvs/
  3. Get a Github account: https://github.com/
  4. Python Hello World: http://www.learnpython.org/en/Hello,_World!
  5. Using the terminal:https://learncodethehardway.org/
  6. Python programming: https://learnpythonthehardway.org/
  7. Anaconda: https://www.anaconda.com/products/individual

Course Fee & Information

Unlike standard Statistics.com courses, this recorded webinar is available on-demand and is not tied to a date.

Options for Credit and Recognition

There are no options for credit and recognition for this course.

Supplemental Information

There is no supplemental content for this course.

Miscellaneous

There is no additional information for this course.

Register for This Course​

Recorded Webinar on Content Optimization with Multi-Armed Bandits & Python
$35.00 | Enroll Now
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Statistics.com offers academic and professional education in statistics, analytics, and data science at beginner, intermediate, and advanced levels of instruction. Statistics.com is a part of Elder Research, a data science consultancy with 25 years of experience in data analytics.

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