Data Science Machine Learning

This 3 months course is broken down into 2 distinct class modules which cover Python fundamentals, exploratory analysis, data cleaning, feature engineering, algorithm selection, and model training.  At the end of the course students will be able to work on a final project with a given a dataset similar to datasets worked with throughout the course. They will go through each of the steps covered and build a model on their own.

The course modules cost are $500 for DS 101 and $1000 for DS 201 but we have an introductory discount of 50%.


DS 101 - Intro to Python for Data Science


In this class we will cover the necessary concepts to kickstart your data science journey. The course will center around the fundamentals of the Python Programming Language while introducing the most relevant Python libraries for manipulating and visualizing data.


DS 201 - Data Science/Machine Learning

DS 201-1 Working With Data

In DS 201-1, we will cover the techniques that real life data scientists use to gain insight into a dataset. From data engineering, to more advanced manipulation and visualizations; this course will show you how to unlock the secrets of any dataset — with the expressed goal of building experiments that require the building of a hypothesis function or “Model”.


DS 201-2 Building and Evaluating ML Models

In DS 201-2, we will learn how to build your own Machine Learning models, We will be using the popular SciKit Learn and TensorFlow libraries to show you how Data Scientists “learn” a model to a dataset and how to make predictions with those models. We will also be covering the finer points of ML Modeling, namely Data Prep, Parameter Selection, and testing Model performance.