Full Stack Data Science

“Jack of all trades, master of none, though oft times better than master of one.”

One of the common pain points that we have come across in big organizations is the last-mile delivery of data science applications. One common delivery vehicle is to create dashboards(BI). But the one, that’s very useful and neglected more often than not, is to create APIs and provide seamless integration with other applications within the company. This requires you to have a basic understanding of machine learning, server-side programming and front-end application.

In this workshop, you would learn how to build a seamless end-to-end data driven application - Data Exploration, Machine Learning Model, RESTful API and Web Application - to solve a business prediction problem.

Course Content

  1. Introduction to Data Science Process
  2. Building a simple Machine Learning model
  3. Building a simple ML Service (localhost)
  4. Improving the ML model and creating many models
  5. Creating RESTful API and deploying to cloud
  6. Create dashboard to visualise the results and interact with the API.
  7. Persisting model output
  8. Updating the model as more data comes in (batch only - no streaming)
  9. Creating a simple application that accomplishes this end-to-end

This will be covered over eight sessions of two hours each over two days.

Session 1: Introduction and Concepts

Session 2: Build a Simple ML Service

Session 3: Build & Evaluate ML Models

Session 4: Practice Session

Session 5: Build a Simple Dashboard

Session 6: Deploy to cloud

Session 7: Repeatable ML as a Service

Session 8: Practice Session & Wrap-up

Target Audience


Software Requirements

We will be using Python data stack for the workshop. Please install Ananconda for Python 3.5 for the workshop. Additional requirement will be communicated to participants.

Facilitators’ Profile

Anand Chitipothu is a software consultant and trainer based in Visakhapatnam. He has over 13 years of experience in architecting and developing variety of software applications. He is co-author of web.py, a micro web framework in Python. He has worked at Strand Life Sciences and Internet Archive. You can tweet him at @anandology

Amit Kapoor teaches the craft of telling visual stories with data. He conducts workshops and trainings on Data Science in Python and R, as well as on Data Visualisation topics. His background is in strategy consulting having worked with AT Kearney in India, then with Booz & Company in Europe and more recently for startups in Bangalore. He did his B.Tech in Mechanical Engineering from IIT, Delhi and PGDM (MBA) from IIM, Ahmedabad. You can find more about him at http://amitkaps.com/ and tweet him at @amitkaps.

Bargava Subramanian is a practicing Data Scientist. He has 14 years of experience delivering business analytics solutions to Investment Banks, Entertainment Studios and High-Tech companies. He has given talks and conducted workshops on Data Science, Machine Learning, Deep Learning and Optimization in Python and R. He has a Masters in Statistics from University of Maryland, College Park, USA. He is an ardent NBA fan. You can tweet to him at @bargava.