- Teaches students:
- Ages 13+
- Teaching since:
What I love about programming is the ability to take an idea and bring it to life with code. When I first started, I was really intimidated because I didn't have a computer science degree and had never coded before. Fast forward a few years after teaching myself code, and I'm now a data scientist.
I love teaching my students how to learn as well as programming concepts. It's almost more important to know "what to Google" than to know everything there is to know about coding.
I'm not just here as a tutor you see for 30 or 60 minute sessions. My goal is to help you grow as a programmer whether you're taking your first course in college, self-teaching for a career change, or applying to Google.
• Working with doctors to assess the effectiveness of interventions
• Utilizing SQL, Python, and SAS to gather data on members
• Running propensity score matching to perform observational studies pairing treated members to control members.
• Producing visualizations and reports to present results to internal clients.
•Created daily HTML newsletter with an automated web scraping script in Python.
•Created an automated Python script to download API data to be stored in a SQL server
•Used regex to extract contact details and company names from raw text data.
•Built machine learning models as backends to Flask apps.
•Utilized Python to obtain, clean, and analyze data.
•Stored large datasets in MongoDB and PostgreSQL databases.
•Extracted data from open sources using web scraping.
•Calculating ROI utilising market mix modelling to evaluate marketing initiatives
•Performing constructing and improving econometric models utilising R and Excel
•Creating intuitive data visualisations to clearly communicate the results to all audiences
•Translating complicated statistical analyses into clear, actionable insights
• Providing a deeper insight into stakeholder relations to find best performing areas and areas of improvement.
• Utilizing SPSS, Excel, and Tableau to produce analysis and easily comprehensible visual representations of data.
• Managing online surveys to collect stakeholder data.
• Regularly cleaning and refining data to obtain the maximum benefit from analysis.
•Consulting with a team of MSc Development Management Candidates
•Collecting macroeconomic data from Latin American countries
•Utilizing STATA to analyze the relationship between violence and low development and Latin American migration.