Hyperparameter Tuning and Feature Engineering
Strategies for hyperparameter tuning. Techniques for effective feature engineering.
Building Basic ML Pipelines
Creating a simple ML pipeline. Integrating version control into the workflow.
Setting Up Your Environment
Installing essential tools and libraries. Configuring version control (e.g., Git).
Introduction to MLOps and AutoML
Overview of MLOps and AutoML concepts. Importance in the machine learning lifecycle.
How the completeness of each section is measured in the course?
There are MCQ-based short tests given after each section to assess the understanding of a learner in each section. Finally, the capstone project is evaluated manually by the instructors.
Who can get the certificate?
All attendees who complete all sections of the course along with the capstone project will get the certificate.
What job roles can i take if i attend this course?
Data scientists, Data Analyst, BFSI Analyst, and other relevant analytics roles can be explored in BFSI domain after taking this course.