Data Ladies is a monthly community engagement initiative in response to the success of DataFest Africa and with support from different partners in the data ecosystem. The aim of the project is to foster a sense of community among individuals and organizations interested in working with data in Uganda and the East African region, with a particular focus on promoting the participation and leadership of women in the data industry. The project provides a platform for networking, knowledge sharing, and collaboration, ultimately supporting and accelerating the growth of data-driven innovation and impact across sectors in the region.
The sessions cover various topics in data science, including data analysis, machine learning, data visualization, and data storytelling. Our goal is to create a community of women data scientists who are equipped with the necessary skills, knowledge, and resources to thrive in the data-driven world. By promoting diversity and inclusivity in data science, we believe that we can unlock the full potential of data to drive innovation, solve complex problems, and make a positive impact on society.
UPCOMING DATA LADIESÂ SESSIONS
| Session 1: April 2023 Meetup
Programming for Data Science: (Introduction to R, Introduction to Python)
|
| Session 2: May 2023 Meetup
Querying Data (Introduction to SQL: From fundamental to advanced SQL)
|
| Session 3
Analyzing and Visualizing Data (Statistics for Data Scientists, Analysing & Visualising data with Power BI, Advanced Excel for Data Scientists)
|
| Session 4
Machine Learning & Data Mining (Introduction to Classification: Loan prediction, Introduction to Regression: Income Prediction)
|
| Session 5
Deep Learning (Introduction to Neural Nets: Image detection)
|
| Session 6
Deep Learning 2 (Introduction to Natural Language Processing: Working with text (Spam detection/Hate speech detection/Sentiment Analysis))
|
| Session 7: ML Hackathon
Applied Data Science (Monitoring Hate Speech during the 2021 Uganda and 2022 Kenya General Elections)
|
| Session 8
Deployment (Deploying your work/Deploying Machine learning models/working with APIs)
|
| Session 9: ML Hackathon
Applied Data Science: Noise detection in Kampala
|
| Session 10: ML Hackathon
Applied Data Science: Building a Predictive text keyboard
|
