Understanding LLM’s: December 12th & 13th, 2024
2 – Half Days (9:00 a.m to 12:00 p.m PST) ENDING IN :
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Kickstart Snowflake in a Day
Duration: 1 Day Code: BDT172 Category:Snowflake was developed from ground up to use advanced cloud computing features provided by Software as a Service (SaaS).
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Byte-Sized ML Series: Machine Learning Introduction
Duration: 90 Minutes Code: BDT177 Category:This concise session will provide a clear overview of machine learning.
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Introduction to Recommendation Systems
Duration: 1 Day Code: BDT171 Category:In this course you will learn about the recommendation algorithms for collaborative filtering.
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DevOps Toolkit: Git, Docker, Kubernetes, and CI/CD
Duration: 3 Days Code: BDT170 Category:In this course you will understand the fundamentals of DevOps and the patterns to develop, build and deploy applications.
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Data storytelling for Leaders
Duration: 4 hours (1 Session) Code: BDT169 Category:Delivering compelling data stories is one of the most overlooked capabilities in business. Unlike Math and English, most of us haven’t had classes for storytelling at school.
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Introduction to Spark 3.x
Duration: 2 Days Code: BDT168 Category:This course follows the “Introduction to Apache Spark version 2.3, and it will help you to master the Apache Spark platform.
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Intermediate Spark 3.X
Duration: 2 Days Code: BDT167 Category:This course is an introduction to Apache Spark version 3.x.
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Summarize Your Data with Pivot Tables in Python
Duration: 6 hours (Two Sessions, 3-3-hours ) Code: BDT166 Category:In this class, you will have the opportunity to develop Python scripts to create pivot tables by leveraging the Pandas module.
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Python for Beginners
Duration: 12 Hours (Four Sessions, Each 3-hours) Code: BDT165 Category:Learn how to code in Python, one of the most popular programming languages today. This class covers the fundamentals of developing scripts to automate routine work and scale large-load work.
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Introduction to R Programming
Duration: 3 Days Code: BDT164 Category:In this hands-on course, the R programming language is taught with the objectives to collect, analyze, and visualize datasets from various sources, and apply practical statistical data analysis.