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DATA-007 Data Analytics and Business Intelligence
PROGRAMME BROCHURE

Python for Data Analysis

An applied five-day programme focused specifically on Python for Data Analysis.

Duration 5 days
Level Professional
Programme DATA-007
KAIZEN EUROPEAN ACADEMY Executive & Professional Development www.kaizeneurope.academy
01

Programme Overview

This five-day Kaizen European Academy programme is dedicated specifically to Python for Data Analysis. It develops practical capability in Python Analytics through structured explanation, applied tools, realistic scenarios and guided workshops. Participants move from core concepts to hands-on application, performance control and an implementation plan that can be transferred directly to their workplace.

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Learning Objectives

Explain the essential concepts, terminology and professional context of Python for Data Analysis.
Apply the principal methods and tools used in Python for Data Analysis.
Analyse realistic situations and make evidence-based decisions related to Python for Data Analysis.
Evaluate performance, risk and control requirements in Python for Data Analysis.
Develop a practical implementation or improvement plan for Python for Data Analysis.

Who Should Attend

Professionals, specialists, supervisors and managers whose responsibilities involve python for data analysis or who need to build practical capability in this area.

Programme Methodology

Instructor-led explanation, facilitated discussion, subject-specific case studies, practical templates, individual and group exercises, simulations or technical scenarios where appropriate, peer review and a final implementation workshop.

Learning Outcomes

Explain the essential concepts, terminology and professional context of Python for Data Analysis. Apply the principal methods and tools used in Python for Data Analysis. Analyse realistic situations and make evidence-based decisions related to Python for Data Analysis. Evaluate performance, risk and control requirements in Python for Data Analysis. Develop a practical implementation or improvement plan for Python for Data Analysis.

Prerequisites

No formal prerequisite is required. Relevant professional experience is helpful; technical courses may assume basic familiarity with the operating environment.

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Course Outline

Day01

Python for Data Analysis: Foundations and Operating Context

  • Scope, terminology and professional context of Python for Data Analysis
  • Current practices and emerging trends in Python for Data Analysis
  • Roles, responsibilities and stakeholder expectations in Python for Data Analysis
  • Diagnostic assessment of current Python for Data Analysis practices
Day02

Core Methods and Tools for Python Analytics

  • Python analytics environment
  • Data structures
  • NumPy concepts
  • pandas Series and DataFrames
Day03

Applied Practice in Python for Data Analysis

  • Data import
  • Data cleaning
  • Transformation
  • Aggregation
Day04

Performance, Risk and Control in Python for Data Analysis

  • Merging datasets
  • Exploratory analysis
  • Visualization
  • Statistics with Python
Day05

Python for Data Analysis: Integrated Workshop and Implementation

  • Time-series basics
  • Automation
  • Reusable functions
  • Notebook practices
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What You Will Receive

Programme learning materials
Practical resources and templates where applicable
Kaizen completion certificate
Participant support throughout the learning week
Kaizen European Academy

Executive & Professional Development across selected European destinations.

CONTACT & INFORMATION

Website: www.kaizeneurope.academy
Contact: www.kaizeneurope.academy/#contact