Diploma Level Course
Tools in Data Science
This practical course will teach students to use popular tools for sourcing data, transforming it, analyzing it, communicating these as visual stories, and deploying them in production. Pre-requisites: Python, HTML, JavaScript, Excel, data science basics
by S Anand
Course ID: BSSE2002
Course Credits: 3
Course Type: Data Science
Pre-requisites: None
Co-requisites: BSCS2004 - Machine Learning Foundations
Course structure & Assessments
9 modules over 12 weeks of coursework, online assignments for each module, 1 remote online exam, 2 take home projects, 1 in-person end term exam. For details of standard course structure and assessments, visit Academics page.
| MODULE 1 | Development Tools and concepts to build models and apps. |
| MODULE 2 | Deployment Tools and concepts to publish what you built. |
| MODULE 3 | Large Language Models that make your work easier and your apps smarter. |
| MODULE 4 | Data Sourcing to get data from the web, files, and databases. |
| MODULE 5 | Data Preparation to clean up and convert the inputs to the right format. |
| MODULE 6 | Data Analysis to find surprising insights in the data. |
| MODULE 7 | Data Visualization to communicate those insights as visual stories. |
About the Instructors
Anand is a co-founder of Gramener, a data science company. He leads a team that tells visual stories from data. He is recognized as one of India’s top 10 scientists, and is a regular TEDx speaker.
Anand is a gold medallist from IIM Bangalore and an alumnus of IIT Madras, London Business School, IBM, Infosys Consulting, Lehman Brothers, and BCG.
More importantly, he has hand-transcribed every Calvin & Hobbes strip ever, is addicted to Minecraft (thanks to his daughter), and dreams of watching every film on the IMDb Top 250 (except The Shining).
Please use only the above methods for program queries. Response time: 3 working days. During peak periods, Google Meet links will be shared. Call wait times may be longer.