Course Summary: Data Science & Machine Learning

Our Data Science and Machine Learning evening cohort is a 6 week course.

Decision science is the brains behind big data analytics. It's not a new field; people have been doing decision science for decades. In the "old days" data was limited, hence complex algorithms were needed to extract useful insights from the data. Given the shift in the data paradigm, we no longer need very complex algorithms. Instead, we need to run simple stuff at scale.

At the end of the day, data science is all about counting smart. In this course, we will learn the essential skills for modern development, and implement industry standard algorithms on large datasets. And, all the while, we will keep it simple.
Decision Science is a mix of Computer Science, Statistics, and Management Skills. In this bootcamp, we will focus on Computer Science (C) and Statistics (S).

Course Details

Week 1 : Develop Essential Skills
  • S: Introduction to Machine Learning
  • C: Unix For Data Science
  • C: SQL For Data Science
  • C: Python Essential Training
Week 2 : Warm-up
  • S: Decision Trees
  • S: Text Mining: Naive Bayes
  • Review Data Aggregation Project
Week 3 : Getting Started with Ensemble Methods
  • S: Ensemble Techniques
  • S: Random Forests
  • S: Recommendation Engines: Collaborative Filtering
Week 4 : Ensemble Method continued
  • S: Gradient Boosting Machines (GBM)
  • C: Principal Component Analysis
Week 5 : Classical Model
  • S: Generalized Linear Models: Linear Regression, Regularization, Logistical Regression
  • S: Clustering: Knn, K-Means
  • Review Final Class Project
Week 6 : Matching and Graphing
  • S: Data Fusion and Fuzzy Matching
  • C: Stable Marriage Algorithm
  • Summary and Putting it all together
  • Data Science Career Counseling
Data Science Learning Objectives
  • Use Unix to manipulate data and solve problems in serial and parallel.
  • Master basic coding problems typically asked during data science interviews.
  • Learn to apply machine learning techniques to solve data-driven problems. And learn the reasons why.
  • Tools used : Python, SciKit,,, SQL, and lastly Linux
  • Most Important: Learn to converse with data and keep it simple. Use common sense.

Next Steps:

  • Drop us a note, to schedule an interview, and see if this course is a good fit for you.


Next Cohort

  • April 4 th, 2016 - May 11th, 2016
    Tuesday and Thursday: 6:30 PM to 9:30 PM


  • $6,000 USD


Financing Options available with : Pave