Home AI Courses Mastering Gen AI: Agents with RAG and LangChain

Mastering Gen AI: Agents with RAG and LangChain

(0 reviews)

Learn how to develop AI agents using RAG and LangChain, as well as how to integrate sophisticated AI technologies.

Key AI Functions:generative ai,rag,langchain,ai agents

Description

Reviews

Alternative Tools

Description for Mastering Gen AI: Agents with RAG and LangChain

In-Context Learning and Prompt Engineering: Comprehend the principles of in-context learning and sophisticated prompt engineering for efficient prompt formulation.
LangChain Concepts and Tools: Acquire an understanding of LangChain tools, components, chat models, chains, and agents.
Integration of RAG and AI Technologies: Acquire knowledge on integrating RAG, PyTorch, Hugging Face, and LLMs with LangChain technologies for Generative AI applications.
Development of AI Agents: Develop AI agents in a hands-on, realistic way with LangChain and RAG.

Level: Intermediate

Certification Degree: Yes

Languages the Course is Available: 1

Offered by: On edX provided by IBM

Duration: 2-4 hours per week 2 weeks (approximately)

Schedule: Flexible

Reviews for Mastering Gen AI: Agents with RAG and LangChain

0 / 5

from 0 reviews

Ease of Use

Ease of Customization

Intuitive Interface

Value for Money

Support Team Responsiveness

Featured Tools

ML in Healthcare: Fundamentals & Applications

IBM Data Engineering Professional Certificate

Alternative Tools for Mastering Gen AI: Agents with RAG and LangChain

Featured Tools

Acquire the ability to differentiate between static and dynamic training and inference, manage model dependencies, establish distributed training for defect tolerance and replication, and generate exportable models.

#Machine Learning #Google Cloud

ML in Healthcare: Fundamentals & Applications

Explore healthcare data mining methods, theoretical foundations of key techniques, selection criteria, and practical applications with emphasis on data cleansing, transformation, and modeling for real-world problem solving.

#Machine Learning #Data Mining

Deep Learning in Business

The course provides comprehensive coverage of AI and ML's increasing integration, structured into three sections focusing on business strategy, fundamental technologies, and hands-on projects, to aid in strategy development and technical planning.

#Artificial Intelligence (AI) #Artificial Neural Network

IBM Data Engineering Professional Certificate

Gain practical skills in relational and NoSQL databases, Big Data tools, and data pipelines for comprehensive data engineering tasks.

#Data Science #Data Analysis

Supervised ML: Regression

Besides Python programming and data science fundamentals, the course covers supervised machine learning regression, which includes training models for continuous outcomes, error metrics, Elastic Net, LASSO, Ridge regularization, and data science fundamentals for aspiring data scientists.

#Linear Regression #Machine Learning (ML) Algorithms

Compare & Review AI Tool Directory AI Course Marketplace