Students wanting to build Machine Learning Applications without wanting to write lot of code.
The objective of the program
To teach students to build Machine Learning Applications without the need to write a lot of code.
Skills that the learner will develop at the end of the course
Be able to understand and develop the ability to build a simple machine learning-based application with minimal or no coding.
ABOUT THE INSTRUCTOR
Anand is a co-founder of Gramener, a data science company. He leads a team that automates insights from data and narrates these as visual data stories. He is recognized as one of India’s top 10 data scientists and is a regular TEDx speaker. Anand is a gold medalist at IIM Bangalore and an alumnus of IIT Madras, London Business School, IBM, Infosys, Lehman Brothers, and BCG. More importantly, he has hand-transcribed every Calvin & Hobbes strip ever and dreams of watching every film on the IMDb Top 250.
Criteria to complete the course and get the certificate:
In order to successfully finish the course, candidates have to ensure that they:
- Log into the Gramex IDE with the same email address which you have used to register with NPTEL+ course.
- Create a model on the IDE and ensure that it works, by following the instructions in the lectures.
- Introduction to Gramex IDE
- Creating a Simple Microservice
- Connecting to Data
- Rendering Data as a table on browser
- Solving a Classification problem
- Solving a Regression problem
- Machine Learning as a (micro)service
- Exposing above (Classification & Regression) as REST API
- Building a user-friendly UI for above Classification and Regression Problems
- Assignment: Wine Problem
The split of content in terms of fundamentals that will be taught, tools included, etc
- Solving (Classification/Regression) problems
- Using Gramex Low Code Platform
Learning outcomes for each module
- Ability to build a simple machine learning-based application with minimal or no coding.
Total number of assessments and activities – mode of evaluation, tools required
Device compatibility: Laptop/Desktop