Rapid Machine Learning Bootcamp

Mode

Offline / Online  / Weekend

Duration

4 Hours

Who Should Enroll

This bootcamp is designed for working professionals, college students, data enthusiasts, and individuals looking to enhance their skill set in machine learning.

Prerequisites

No prior knowledge is needed. A basic understanding of programming and statistics is helpful but not required.

Program Objectives

The primary objective of this bootcamp is to simplify key machine learning concepts and provide practical insights into their application. The program is designed to introduce participants to fundamental machine learning concepts, such as underfitting, overfitting, and model evaluation. Participants will gain hands-on experience by working on a predictive analysis project using Python and Scikit-learn, and they will also get an overview of machine learning workflows, including model deployment and monitoring.

Key Topics

• ML Concepts Simplified: Introduction to basic machine learning concepts such as underfitting, overfitting, and model evaluation.
• Linear and Logistic Regression: A visual and practical approach to understanding regression models.
• Project: Predictive Analysis: Hands-on project where participants will create a predictive model using Python and Scikit-learn.
• Wrap-up on ML Workflows: Overview of the processes involved in deploying and monitoring machine learning models.

Faculty and Resources

The course is taught by experienced industry professionals with expertise in machine learning. Participants will have access to practical resources and tools to enhance their learning experience.

Certification

Upon completion, participants will receive a Certificate of Participation in Rapid Machine Learning Bootcamp.

Register

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