Negocio Trainings
Learning never exhausts the mind
Data Analysis Techniques
Data Analysis Techniques is a comprehensive course designed to equip participants with the essential skills and knowledge needed to effectively analyze and interpret data
- Course Schedule
Classroom Sessions:
| Date | Venue | Price |
|---|
18 - 22 Mar 2025
Dubai - UAE
$ 5,950
16 - 20 Sep 2025
Dubai - UAE
$ 5,950
14 - 18 Oct 2025
London - UK
$ 5,950
21 - 25 Oct 2025
Doha - Qatar
$ 5,950
- Course Description
INTRODUCTION
Data Analysis Techniques is a comprehensive course designed to equip participants with the essential skills and knowledge needed to effectively analyze and interpret data. In today’s data-driven world, the ability to extract meaningful insights from data is crucial for informed decision-making across various industries.
WHY IT MATTERS
Data is the backbone of modern businesses and organizations. It provides valuable information that can be used to identify patterns, trends, and opportunities, enabling businesses to make informed decisions, optimize processes, and gain a competitive edge. Understanding how to analyze and interpret data is a key skill for professionals in roles ranging from marketing and finance to operations and management.
OBJECTIVES
- Gain a solid understanding of fundamental data analysis concepts.
- Acquire hands-on experience with popular data analysis tools and techniques.
- Learn how to interpret and communicate findings from data analysis.
- Develop the skills to make informed business decisions based on data insights.
WHO SHOULD ATTEND ?
This course is suitable for professionals and students who want to enhance their data analysis skills, including:
- Business Analysts
- Data Analysts
- Marketing Professionals
- Financial Analysts
- Operations Managers
- Researchers
- Anyone interested in leveraging data for decision-making.
- Course Outline
DAY 1
Introduction to Data Analysis
- Overview of Data Analysis
- Importance of Data in Decision-Making
- Introduction to Data Analysis Tools
DAY 2
Data Collection and Cleaning
- Methods of Data Collection
- Data Cleaning and Preprocessing
- Dealing with Missing Data
DAY 3
Exploratory Data Analysis (EDA)
- Descriptive Statistics
- Data Visualization Techniques
- EDA with Pandas and Matplotlib/Seaborn
DAY 4
Statistical Analysis
- Hypothesis Testing
- Regression Analysis
- Inferential Statistics
DAY 5
Advanced Data Analysis Techniques
- Machine Learning Overview
- Clustering and Classification
- Practical Application of Advanced Techniques
- Options & Brochure