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Datacamp – Associate AI Engineer for Data Scientists 2024-8

Datacamp – Associate AI Engineer for Data Scientists 2024-8

Published on: 2024-08-31 21:44:36

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Descriptions

Associate AI Engineer for Data Scientists, Begin building AI solutions and gain the career-building skills you need to succeed as an AI Engineer, from model development to deployment into production! In this track, you’ll train and evaluate robust predictive models on real-world datasets across a variety of domains. Starting with the fundamentals of machine learning, you’ll get hands-on with some of the most popular Python libraries for machine learning and deep learning, including scikit-learn, PyTorch, and many more. As you progress, you’ll get hands-on with Large Language Models (LLMs) for a variety of natural language tasks. You’ll learn to fine-tune Llama 3 on custom data and integrate this into a LangChain application to begin surfacing predictions to end-users. Finally, you’ll discover what it takes to move an AI model from a notebook into production. You’ll build foundational skills in MLOps, including testing, version control, and monitoring performance in production.

What you’ll learn

Specificatoin of Associate AI Engineer for Data Scientists

Content of Associate AI Engineer for Data Scientists

Associate AI Engineer for Data Scientists

Pictures

Associate AI Engineer for Data Scientists

Sample Clip

Installation Guide

Extract the files and watch with your favorite player

Subtitle : English

Quality: 720p

Download Links

Intermediate Deep Learning with PyTorch

Download – 94 MB

Introduction to Deep Learning with PyTorch

Download – 86 MB

Introduction to LLMs in Python

Download – 108 MB

Introduction to Testing in Python

Download – 83 MB

MLOps Concepts

Download – 83 MB

MLOps Deployment and Life Cycling

Download – 96 MB

Monitoring Machine Learning Concepts

Download – 71 MB

Responsible AI Data Management

Download – 99 MB

Software Engineering Principles in Python

Download – 69 MB

Supervised Learning with scikit-learn

Download – 87 MB

Unsupervised Learning in Python

Download – 117 MB

Working with Llama 3

Download – 60 MB

introduction-to-git

Download – 114 MB

Password file(s): www.abc.com

File size

1.14 GB

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