Machine Learning - Classification Models in Python (Webinar)
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Machine Learning - Classification Models in Python (Webinar)

9/16/2019 to 9/30/2019
When: Mondays, September 16, 23, 30
Mondays 6:00 PM - 9:00 PM
Where: Online Webinar
Los Angeles, California 
United States
Contact: Caitlin Topkis

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Machine Learning - Classification Models in Python

In partnership with CFA Society Los Angeles and Cognitir

This hands-on, programming-based data science course is a sequel to Cognitir’s Introduction to Data Science course. It will provide an overview of modern machine learning algorithms that analysts, portfolio managers, traders and chief investment officers should understand given the improved ability to capture and analyze data.

This course will explore classification methods including neural networks and decision trees, which are among the most effective data science techniques. An introduction to deep learning, a technique which has significantly increased the performance of machine learning algorithms over the last years and is heavily used in the industry, is also included.

At the end of the workshop, participants will be comfortable applying the Python programming language to build common classification algorithms and evaluate & interpret their accuracy.

Attendees may use a PC or Mac to access slides and other resources we provide for the class.

What This Course Offers
  • An overview of core classification methods and how to use them to solve real-world problems in the finance industry
  • Hands-on Python programming experience
  • Course notes, certificate of completion, and post-seminar email support for 1 year
  • An engaging and practical training approach with a qualified instructor with relevant technical, business, and educational experiences
Who Is This Course For:

This course is relevant for individuals working with or needing to understand machine-learning algorithms, specifically classification methods.

Introduction to Data Science



Mondays, September 16, 23, 30, 2019

6:00 PM - 9:00 PM



$499 / Members (email for member pricing code)

$599 / Non-members


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