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Data_Scientist_Nanodegree

Projects completed for the Udacity Data Scientists Nanodegree Term 1

  1. Finding Donors: Build an algorithm that best identifies potential donors.

  2. Image Classifier: Implement an image classifier with PyTorch.

  3. Identify Customer Segment: Apply unsupervised learning techniques to identify clusters of the population that are most likely to be purchasers of products for a mailout campaign.

Projects completed for the Udacity Data Scientists Nanodegree Term 2

  1. Write a Data Science Blog Post: Analyze Airbnb data in Boston and Seattle to find out what kind of listings are more likely to have higher revenues. Accompanying blog post can be found here

  2. Build Pipelines to Classify Messages with Figure Eight: Build ETL and ML pipelines to classify messages sent during disasters.

  3. Design a Recommendation Engine with IBM: Implement recommendation techniques using data from the IBM Watson Studio platform.

  4. Data Science Capstone Project. Explore data from Starbucks Rewards Mobile App and implement a promotional strategy with uplift models. Accompanying blog post can be found here: part 1, part 2.

Portfolio Exercises

These are optional, ungraded exercises for the course

Starbucks Portfolio Exercise: Implement uplift models to identify which customers we should send promotions to entice them to purchase a product. Accompanying blog post can be found here