General Assembly Data Science, Los Angeles, September 2014
General Info
Here, you'll find links to slides, handouts, and other material.
- General Assembly Class Information
- General Resources: Links to Python and other tools and libraries that we'll be using.
Key Dates
- 09/10/2014: Data Science Information Session
- 09/16/2014: First Day of Class
- 11/27/2014: Last Day of Class (Tentative)
Classes
- Class 0 : Install Party - Installing Python & Other Dependencies
- Class 1 : Introduction to Data Science & Basic Data Manipulation
- Class 2 : Python & Data Parsing
- Class 3 : SQL & Python
- Class 4 : NoSQL & Python
- Class 5 : Introduction to Machine Learning
- Class 6 : Linear Regression and Regularization
- Class 7 : Logistic Regression (Project Outline Due!)
- Midterm Project Due (See instructor for details).
- Class 8 : Naive Bayes & Bayesian Estimators (Project Outline Discussion!)
- Class 9 : Decision Trees and Random Forests
- Class 10 : Classification Review
- Class 11 : Ensemble Learning
- Class 12 : K-Means Clustering
- Class 13 : PCA & Unsupervised Learning
- Class 14 : Recommendation Systems
- Class 15 : Further Topics in Unsupervised Learning
- Class 16 : Model Selection and Evaluation
- Class 17 : Dataset Transformation (Speaker from Datasift)
- Class 18 : Data Visualization
- Class 19 : Hadoop and Map Reduce
- Class 20 : Field Trip to Factual!!!!
- Class 21 : Distributed Data Processing with BDAS and Spark
- Class 22 : Final Presentations and Reports!
- Post-Class : Data Science Career Panel
Final "Happy Fun" Project Info
- Presentation and Report Due on Last Day of Class.
- Project Ideas and Data
Useful Books
Instructor Contact Information
- Yasin Dara, yasin.s.dara@gmail.com
- Cell: (612)-208-7364 (Yes, it's okay!)