Classical machine learning algorithms

This module is the second part of the "Data Science and Modeling" certificate. The objective is to get to know and use the fundamental techniques of machine learning and to gauge the impact of such tools in a company.

OBJECTIVES

This course will give you :

• An in-depth knowledge of the fundamentals of machine learning and its business applications.
• Technical understanding of the basics of machine learning
• Concrete experience with machine learning models and their applications to give a new dimension to your company.

CONTENT

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  Day 1: Clustering methods and classification

  Getting to grips with the fundamentals of machine learning with clustering (data partitioning) and classification algorithms.

  The main concepts covered in this module are: the Scikit-learn library, clustering and classification methods.

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  Day 2: Regression Methods and Time Series

  Learn how to use regression and time series methods, and then apply them in business.

  The main concepts covered in this module are: regression, time series and data modeling.

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  Day 3: Business applications of time series

  Experience with time series methods to solve a business problem using machine learning.

  The main concepts covered in this module are: data modeling and time series using Scikit-learn.

TRAINERS/TEACHERS

Hugo Hadjur

Expertise : Data science

Assistant Professor in IA & Data Science | PhD student at ENS Lyon and aivancity

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Levente Szabados

Expertise : Data science

Visiting professor in Data science | Lecturer at Frankfurt school of finance & management

See his profile