Data Science

Applied Data Science with Python

Overview

This course provides theoretical and practical aspects of using Python applied to Data Science, Business Analytics, and Data Logistics. Emphasis is on a survey of core concepts, terminology, and theory. This course is supplemented by a variety of hands-on labs that help participants reinforce their theoretical knowledge of the learned material.

Duration: 

2 days

Who Should Take This Course

Audience

This course is suitable for: Business Analysts, Developers, IT Architects, and Technical Managers

Prerequisites

Participants should have a working knowledge of Python or have strong programming experience with another language. Familiarity with core statistical concepts such as variance, correlation, etc. is helpful.

Course Outline

Applied Data Science with Python

  1. What is Data Science?
  2. Data Processing Phases
  3. Descriptive Statistics Computing Features in Python
  4. Repairing and Normalizing Data
  5. Data Visualization with matplotlib
  6. Data Science and ML Algorithms in scikit-learn
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