1. Build Job-Ready Skills

• Help MS students strengthen coding skills in SQL and Python.
• Practice modeling, data mining, and data analysis tasks.
• Learn to use platforms like GitHub, Kaggle, Hugging Face, AWS, and Google Cloud.
• Bridge the gap between classroom learning and real-world data applications.

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2. Prepare for Careers

• Provide structured interview preparation by practicing common technical questions in statistics, probability, machine learning, and linear algebra.
• Share insider knowledge from students’ co-op and job search experiences.
• Develop confidence in problem-solving, technical communication, and teamwork.

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3. Create a Supportive Community

• Offer a space where students can learn informally without pressure.
• Encourage peer-to-peer mentoring, especially for students without prior work experience.
• Build a professional network across MS programs (Math, Applied Math, Operations Research, Statistics).

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4. Provide Hands-On Opportunities

• Work together on Kaggle projects and other data competitions.
• Practice solving coding problems from LeetCode and beyond.
• Occasionally bring in industry guest speakers to share insights on data careers.

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5. Make It Fun and Social

• Balance skill-building with social connection — pizza lunches, teamwork, and informal discussion.
• Create an environment where students look forward to coming each week.