### Course 1: Natural Language Processing with Classification and Vector Spaces

In this course, you will: a) Perform sentiment analysis of tweets using logistic regression and then naïve Bayes; b) Use vector space models to discover relationships between words and use PCA to reduce the dimensionality of the vector space and visualize those relationships; and, c) Write a simple English to French translation algorithm using pre-computed word embeddings and locality sensitive hashing to relate words via approximate k-nearest neighbor search.

**Week 1: Logistic Regression for Sentiment Analysis of Tweets**

Use a simple method to classify positive or negative sentiment in tweets

**Week 2: Naïve Bayes for Sentiment Analysis of Tweets**

Use a more advanced model for sentiment analysis

**Week 3: Vector Space Models**

Use vector space models to discover relationships between words and use principal component analysis (PCA) to reduce the dimensionality of the vector space and visualize those relationships

**Week 4: Word Embeddings and Locality Sensitive Hashing for Machine Translation**

Write a simple English-to-French translation algorithm using pre-computed word embeddings and locality sensitive hashing to relate words via approximate k-nearest neighbors search