عربي
عربي
Passionately developing careers since 2000.
عربي
عربي
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Why Attend
This course focuses on the essentials of designing a robust data collection process, selecting optimal sampling techniques, validating data quality, and exploring visualization options alongside their corresponding descriptive statistical KPIs. Participants will also gain insight into advanced techniques and tools for comprehensive data analysis, laying the groundwork for a successful career in the field of data or as preparation for Machine Learning courses or programs. This course is designed to provide participants with a clear understanding of data structuring for efficient analysis, scientific profiling of different groups through smart data examination, and practical experience with current technology tools available in the market.
Overview
Course Outline
Schedule & Fees
Methodology
Each statistical tool or methodology used during the course is supported by its own case study with step-by-step outputs that go in parallel with multi stage analysis.
In addition to group discussions, all analysis tools are detailed and demonstrated with sequential screen shot applications on comparative technologies (EXCEL â STATISTICA and SAS â R and Python).
Course Objectives
By the end of the course, participants will be able to:
Plan and manage the lifecycle of a successful data analysis project
Translate business challenges into comprehensive databases
Assess and improve data quality for analysis and reporting
Summarize and interpret data using descriptive statistics
Uncover the complete narrative behind data analysis
Target Audience
Applied Data Analysis is the foundation for all Machine Learning and Artificial Intelligence (AI) practitioners. It is prerequisite knowledge that is applicable in all industries and data related functions.
Target Competencies
Project Design
Findings Visualization
Data Analysis
Problem Solving using analytical tools
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