Analyzing Data with Confidence: A Beginner's Guide to Data Analysis Using Excel

Analyzing Data with Confidence: A Beginner’s Guide to Data Analysis Using Excel (Virtual)


Course Information

Start Date 15 Jul 2024, Mon
Start Date
End Date15 Jul 2024, Mon
Time9.30am to 4.30pm
Mode
FeeSGD 680.00 (excluding GST)
Contact Eunice | 6720 3333 | training.aventis@gmail.com
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  • Course Outline

The course covers a range of topics related to data analysis, including data cleaning and preprocessing, data mining, data visualization, and statistical analysis. The course typically begins with an introduction to the data analysis process, including the importance of data cleaning and preprocessing. Students will learn how to identify and correct common data quality issues, such as missing data, outliers, and inconsistent formatting.

This data analysis course is designed to provide a comprehensive yet practical overview of the whole analytics value chain, with a particular emphasis on the tools needed to extract objective insights from data. You will learn about the analytical process, including an overview of statistical ideas and techniques. You will also participate in hands-on exercises using Microsoft Excel and learn real data analysis skills.

* Learners should have an internet-enabled laptop with Microsoft Excel version 2016 or later preinstalled and comfortable with with performing more advanced functions on Excel and possess basic knowledge in statistics when attending this course.

Earn A Professional Certificate in Data Analytics in 4 Days!

Aventis' Professional Certificate in Data Analytics series aims to provide beginners with a comprehensive understanding of the 4 pillars of data analytics: data management, data analysis, data visualisation, and data storytelling.

Complete these 4 courses and earn your Professional Certificate:

  1. A Beginner's Guide to Data Management & Data Reporting
  2. A Beginner's Guide to Data Analysis
  3. A Beginner's Guide to Data Visualisation
  4. A Beginner's Guide to Data Storytelling

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