In an increasingly data-centric world, the ability to derive meaningful insights from raw data is essential. The IBM Data Analyst Capstone Project gives you the opportunity to apply the skills and techniques learned throughout the IBM Data Analyst Professional Certificate. Working with actual datasets, you will carry out tasks commonly performed by professional data analysts, such as data collection from multiple sources, data wrangling, exploratory analysis, statistical analysis, data visualization, and creating interactive dashboards. Your final deliverable will include a comprehensive data analysis report, complete with an executive summary, detailed insights, and a conclusion for organizational stakeholders.

IBM Data Analyst Capstone Project

IBM Data Analyst Capstone Project
This course is part of IBM Data Analyst Professional Certificate



Instructors: Rav Ahuja
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What you'll learn
Apply techniques to gather and wrangle data from multiple sources.
Analyze data to identify patterns, trends, and insights through exploratory techniques.
Create visual representations of data using Python libraries to communicate findings effectively.
Construct interactive dashboards with BI tools to present and explore data dynamically.
Skills you'll gain
- Data Collection
- Presentations
- Exploratory Data Analysis
- Data Visualization Software
- Business Intelligence Software
- Data Manipulation
- Statistical Visualization
- Data Cleansing
- Data Visualization
- Looker (Software)
- Data Analysis
- Interactive Data Visualization
- Business Intelligence
- Data Presentation
- Web Scraping
- Dashboard Creation
- Data Wrangling
- IBM Cognos Analytics
Tools you'll learn
Details to know

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There are 6 modules in this course
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Reviewed on Jun 20, 2021
The course is great and the tools used in this course are those widely used by data analysts in real life.
Reviewed on Jun 3, 2023
In a nutshell, this Capstone Project is very well prepared. Thank you for the creators and the contributors.
Reviewed on Jul 17, 2022
A good beginner friendly course in data analysis. Using the jupyter notebook was easier than going over to some websites to open the same jupyter notebook.
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