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AI RESEARCH
Our online Data Science Research Program offers in-depth exploration into data analysis, machine learning, and predictive modeling. Tailored for aspiring data scientists, this summer program involves hands-on projects with real-world data, focusing on a UN Sustainable Development Goal.
Registration for the 2025 summer session will open soon.
PROGRAM CONTENT
- Receive guidance from professionals in both academia and industry for your research endeavors
- Apply advanced Machine Learning techniques to gain deep insights into societal challenges
- Engage in a collaborative environment to ideate creative approaches for addressing tangible global problems alongside peers with similar interests
- Gain the opportunity to connect with young analysts and data scientists from diverse fields, forming valuable connections for the future
PROGRAM HIGHLIGHT
- Structured modules with daily and weekly goals for smooth progress tracking
- Conduct comprehensive exploratory data analysis using Pandas, and visualization libraries like Seaborn and Matplotlib
- Gain basic proficiency in machine learning techniques, including Decision Tree and Random Forest, for predictive data analysis
- Work in tandem with fellow participants on dataset(s) to achieve the program deliverables
- Showcase your research findings in a culmination event
WHO CAN JOIN?
- A student who has completed a Python programming course or attending a python programming camp
- A student exhibiting advanced analytical and problem-solving capabilities
PREREQUISITE
Showcase your Python skills with a valid certificate from an accredited Python course or camp.
SELECTION
Apply for our research program: Submit an application, followed by an interview with the DIYA Research Team for evaluation.
REGISTRATION
Successful interviewees will receive an email with a registration link to confirm their participation.
SAMPLE SCHEDULE (2024)
Week 1 | June 24 - June 28 | Research students will refresh their programming skills by completing video lessons and assignments. Students will be introduced to an area of study to conduct research and collect relevant material and datasets to formulate a research question. |
Week 2 | July 1- July 5 | Students will engage in data collection and utilize Python and Pandas for cleaning the data. They will perform exploratory data analysis to identify trends, patterns, and insights within the dataset. |
Week 3 | July 8 - July 12 | Students will work on data collection and cleaning using python libraries. They will refine their dataset with basic exploratory work. |
Week 4 | July 15 - Jul 19 | Students will employ various visualization techniques for in-depth analysis and exploration of the dataset. They will draw meaningful inferences and understanding of data patterns through comprehensive exploratory analysis through visualization. |
Week 5 | July 22 - July 26 | Students will explore Machine Learning concepts, applying Decision Tree and Random Forest algorithms for predictions and mastering hyper parameter tuning to improve the performance of their machine learning models. |
Week 6 | July 29 - Aug 2 | Students will refine their work and document their findings in their report. They will create a slide deck highlighting their machine learning analysis and prepare for a live final presentation at the culmination event. |
Culmination Event | Aug 3 (Sat) | Students will present their research project to a panel of experts from universities and industry, showcasing their work and insights. |
EARN A CERTIFICATE
Earn a completion certificate that will be validated by DIYA Research
