The document outlines a 40-hour training agenda on enterprise artificial intelligence covering machine learning libraries and algorithms, building and deploying machine learning models using structured and unstructured databases, digital agriculture using deep learning, and model operations for production. The agenda is split over 5 days and covers topics such as regression, classification, model building with Docker, GitHub, IBM DB2, Cassandra, and deployment operations.

1. ENTERPRISE AI
40 HOURS LEARNING ABOUT ENTERPRISE AI WITH DB2,CASSANDRA,
DIGITAL AGRICULTURE, AND LLMPOS.

2. AGENDA DAY 1&2
2
➢ Introduction to ML and its Libraries
➢ ML libraries – Practical
➢ Supervised learning- Regression
➢ Simple and Multiple Linear Regression- Practical
➢ Classification
➢ Logistic Regression – Practicals

3. AGENDA DAY 3
3
➢ End to End ML model building
and Deployment with docker and Github

4. AGENDA DAY 4&5
➢ ML model building using IBM DB2
(Structured Data type)
➢ ML model Building using Cassandra
(Unstructured Database)
➢ Digital Agriculture- using Deep Learning
➢ LLMOps – Deployment and learning in Production
4

5. AGENDA
DAY1& 2
5
Day Forenoon Afternoon
Day1
Introduction to ML and its Libraries ML libraries - Practical
Day2
Supervised learning- Regression,
Simple and Multiple Linear
Regression- Practical's
Classification
Logistic Regression – Practical's

6. AGENDA
DAY 3,4, &5
6
Day Forenoon Afternoon
Day3
End to End ML model building and Deployment with docker and GitHub
Day4
ML model building using IBM DB2
(Structured Data type
ML model Building using
Cassandra
(Unstructured Data base))
Day5 Digital Agriculture- using Deep Learning
LLMOps – Deployment and
learning in Production

7. THANK YOU
Object Automation
Email address: hr@object-automation.com
http://www.object-automation.com