20 Scholarships
This 20-hour course equips the participant with essential skills in data analysis, including the use of statistical tools to work with data sets and extract actionable insights. Participants will gain hands-on experience with SPSS for data entry, editing, and organizing datasets, as well as performing inferential statistical analysis.
The course also covers Python programming, with a focus on using libraries like NumPy for data analysis and pandas for data management. Participants will learn the four key steps of data analysis—reading, describing, cleaning, and visualizing data—while practicing with various data visualization libraries to extract and communicate insights. Additionally, the course explores machine learning algorithms and their application to real-world datasets. By the end, participants will be confident in analyzing data, making data-driven decisions, and using industry-standard tools to manage and visualize data.
Eligibility:
- Proven record of academic excellence, community engagement, and/or professional achievements
- English language proficiency (B1)
- Proven awareness of Excel
- Proven awareness of other digital tools is a plus
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