Euro-training Center
 Associate Certified Analytics Professional aCAP G2637 QR Code
Share (36) Like Download Brochure (PDF) Dates and locations

Associate Certified Analytics Professional aCAP



This program is designed to prepare participants for the certification exam only.

This training program is designed to enhance participants' knowledge and skills in analytics. Through it, they will gain a deep understanding of analytical methods, tools, and best practices essential for effective data-driven decision-making.

Program Objectives:

By the end of this program, participants will be able to:

  • Grasp the core concepts and principles of data analytics.

  • Utilize various techniques to analyze data and generate insights.

  • Create and validate data models to support decision-making.

  • Effectively communicate findings and recommendations to stakeholders.

  • Gain the knowledge and skills necessary to pass the aCAP certification exam.

Targeted Audience:

  • Aspiring data analysts seeking certification.

  • Professionals transitioning into analytics roles.

  • Managers looking to enhance their data-driven decision-making skills.

  • IT professionals interested in analytics.

Program Outlines:

Unit 1:

Data Analytics Fundamentals:

  • Overview of data analytics and its importance in business.

  • Understanding different data types and sources.

  • Techniques for collecting and sourcing data.

  • Ensuring data quality and governance.

  • Overview of commonly used analytical tools and software.

Unit 2:

Statistical and Quantitative Analysis:

  • Understanding measures of central tendency, variability, and distribution.

  • Conducting hypothesis testing and confidence interval estimation.

  • Applying linear and logistic regression techniques.

  • Analyzing time series data for trends and seasonality.

  • Utilizing probability distributions and building predictive models.

Unit 3:

Data Management and Preparation:

  • Techniques for cleaning and preparing data for analysis.

  • Methods for transforming and normalizing data.

  • Combining data from different sources for comprehensive analysis.

  • Techniques for exploring and visualizing data.

  • Creating new features to improve model performance.

Unit 4:

Advanced Analytical Techniques:

  • Introduction to machine learning concepts and algorithms.

  • Techniques for classification and regression tasks.

  • Methods for clustering and association analysis.

  • Basics of NLP and text analytics.

  • Techniques for evaluating and validating models.

Unit 5:

Communicating Analytical Results

  •  Principles and best practices for effective data visualization.

  •  Hands-on practice with tools like Tableau, Power BI, or Python..

  •  Techniques for presenting data in a compelling narrative.

  •  Creating insightful reports and dashboards.

  •  Best practices for presenting findings and recommendations to diverse audiences.

  • Prepare for the certifiation exam.

Note: This program is designed to prepare participants for the certification exam only.

Select training course venue