Fundamentals of Data Science
Completed by Zainab Ogunjobi on July 6, 2025
Verified learner ·
Badge ID: rcYUmjwhSy2GFJo8IQstMw
About this Badge
This Data Science Learning Path is designed for beginners or those with some foundational knowledge in programming and statistics. It covers essential concepts, tools, and techniques in data science, from data cleaning and exploration to machine learning algorithms. Learners will gain a strong foundation in data analysis, predictive modeling, and data visualization using Python, SQL, and key data science libraries. The curriculum gradually progresses from basic to intermediate-level skills.
Learning objectives
- Create and analyze data visualizations and dashboards using Excel, Cognos Analytics, and Power BI to effectively communicate data insights.
- Develop skills in data analysis processes, including data gathering, cleaning, and visualization, using tools like Google Sheets, Excel, and Power BI.
- Understand the roles and responsibilities of data analysts, data scientists, and data engineers, and differentiate between them within the data ecosystem.
- Apply foundational data analytics practices and tools to solve real-world data analysis tasks and prepare for introductory-level data analyst positions.
Skills learned
- IBM Cognos Analytics
- Interactive Data Visualization
- Data Visualization Software
- Pivot Tables And Charts
- Business Analytics
- Scatter Plots
- Tree Maps
- Analytical Skills
- Apache Hive
- Apache Spark
- Apache Hadoop
- Microsoft Excel
- Google Sheets
- Data Presentation
- Data Lakes
- Data Sharing
- Spreadsheet Software
- Histogram
- Data Ethics
- Data Manipulation
- Data Mart
- Data Processing
- Data Storytelling
- Dashboard
- Statistical Analysis
- Data Warehousing
- Business Intelligence
- Data Modeling
- SQL
- Data Strategy
- Analytics
- Data Management
- Data-Driven Decision-Making
Learning content completed
Some of the content and skills presented have been contributed by the content provider.