Data Science

Syllabus

1. Python, Data Structures & Algorithms

   Module 1 introduces the fundamentals of Python for Data Science. You’ll learn the fundamentals of programming with Python, how to organize your data with data structures, and basic algorithms.

2. Math & Statistics

   Math and statistics are a fundamental skill for anyone working with large amounts of data. In this module, we'll review linear algebra, gradients, optimization, confidence intervals & testing, distributions, and linear models.

3. Introduction to Machine Learning

   Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. In this module we will explore supervised learning, clustering, and embedding.

4. Data Engineering

   With Data Engineering, you will learn to leverage different data formats, from raw data to production analytical or predictive uses. We'll be looking at relational databases (SQL), MapReduce framework for NoSQL schemas, network/graphical data, text data (NLP), sequential data (time series), and image data.

5. Data Science in Business

   Being a good Data Scientist requires clearly communicating information to stakeholders. In this module you will learn the skills necessary to manage a real project. This includes effective data analysis and presentation, Object Oriented & other programming paradigms, source code and data management, as well as deployment and maintenance.

6. Team Project

   Together with a few classmates, you will build a project based on real-world data. This includes presenting an analysis of the data, justifying the approach, presenting a solution and demonstrating statistically the efficacy of your solution.

7. Solo Project

   For your capstone project, you will develop a machine learning solution on complex real-world data, and deploy a prototype micro-service. You will be responsible for all decisions from what data to use and how, to the data pipeline and model.