Description for Gen AI Architecture and Application Development
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Edureka
Duration: 12 hours (approximately)
Schedule: Flexible
Pricing for Gen AI Architecture and Application Development
Use Cases for Gen AI Architecture and Application Development
FAQs for Gen AI Architecture and Application Development
Reviews for Gen AI Architecture and Application Development
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Gen AI Architecture and Application Development
Achieve a professional status as an AI Engineer. Acquire the knowledge necessary to develop next-generation applications that are propelled by generative AI, a skill that is indispensable for startups, agencies, and large corporations.
Learn to use the latest LLM APIs, the LangChain Expression Language (LCEL), and develop a conversational agent.
Investigate the field of artificial intelligence and machine learning. While investigating the transformative disciplines of artificial intelligence, machine learning, and deep learning, enhance your Python abilities.
Learners gain essential AI engineering abilities from the course, such as prompt engineering, LangChain integration, and RAG approach application.
Learn how to develop AI agents using RAG and LangChain, as well as how to integrate sophisticated AI technologies.
Featured Tools
Acquire the knowledge necessary to direct your AI voyage. In this program, a CEO will instruct you on how to become a hands-on, AI-powered leader who is prepared to unlock the transformative potential of GenAI for your organization.
Gain extensive knowledge in AI technologies relevant to digital marketing, involving precise data analysis, content creation, and tools for optimizing social media and consumer segmentation.
Become the leader your data team requires. In four courses, acquire the skills necessary to lead a data science team that produces high-quality analyses.
Understand the core concepts of data analytics, its primary phases, key data roles, various data structures, file formats, and the comprehensive data analysis process.
Master the operations of large language models. Acquire proficiency in the deployment, management, and optimization of extensive language models on a variety of platforms, such as Azure, AWS, Databricks, local infrastructure, and open source solutions, through practical projects.