Data Analysis with Python (PYTHON05)

 

Course Overview

Everyone's talking about it: Data is the new gold, so let's dig. Python is our mining tool. Learn how to prepare your data for analysis correctly and efficiently and how to evaluate it in a targeted way using hypothesis techniques.

Who should attend

Data analysts, business analysts, data engineers, BI specialists, database specialists, Excel analysts

Prerequisites

Course Advanced Python (Associate Training) (PYTHON03) or equivalent knowledge

Course Objectives

  • Data preparation
  • Data transformation
  • Quality evaluations
  • Analysis
  • Data analysis applications
  • Introduction to Machine Learning and AI

Course Content

  • Basics of Numpy
    • What this package can do
    • Which data analyses are possible
  • Introduction to pandas
    • Pandas Data Structures
    • Functionality
    • Which data analyses are possible and useful with pandas
  • Loading and saving data
    • Practical handling of the most important file formats
    • Efficiency, performance and reliability
  • Prepare and clean up data
    • Dealing with missing data
    • Data transformation
  • Linking, combining and transforming data
  • Visualization
  • Aggregation and grouping of data
  • Time series
  • Pandas for advanced learners
  • Modelling Libraries
  • Examples from data analysis
  • Overview learning models with scikit
Online Training
Modality: L

Duration 3 days

Classroom Training
Modality: C

Duration 3 days

 

Schedule

German
Time zone: Central European Time (CET)
Online Training Time zone: Central European Time (CET) Course language: German
Online Training Time zone: Central European Summer Time (CEST) Course language: German
Online Training Time zone: Central European Summer Time (CEST) Course language: German
Online Training Time zone: Central European Time (CET) Course language: German
Instructor-led Online Training:   This computer icon in the schedule indicates that this date/time will be conducted as Instructor-Led Online Training.