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Building Agentic AI Systems with Open-Source Models Course Overview

Building Agentic AI Systems with Open-Source Models Course Overview

Building Agentic AI Systems with Open-Source Models is an innovative course designed to equip learners with the skills needed to create intelligent systems that can make autonomous decisions. Participants will explore key concepts in AI, delve into open-source frameworks, and understand the ethical implications of deploying agentic systems.

Learning objectives include mastering the development of AI models, implementing decision-making algorithms, and optimizing system performance. By the end of the course, learners will be able to apply their knowledge to build robust, ethical AI solutions that drive real-world applications. This hands-on experience ensures that participants leave with the tools necessary to thrive in the evolving field of artificial intelligence.

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1,975 (USD)
  • Live Training (Duration : 48 Hours)
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Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

  • Live Training (Duration : 48 Hours)
  • Per Participant
  • Classroom Training fee on request
Koeing Learning Stack

Koenig Learning Stack

Free Pre-requisite Training

Join a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.

Assessments (Qubits)

Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.

Post Training Reports

Receive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.

Class Recordings

Get access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.

Free Lab Extensions

Extend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.

Free Revision Classes

Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.

Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

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♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

Request More Information

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Course Prerequisites

Certainly! Here are the minimum required prerequisites for successfully undertaking the "Building Agentic AI Systems with Open-Source Models" course:


  • Basic understanding of programming concepts: Familiarity with any programming language, preferably Python, is essential as it will be used throughout the course.
  • Fundamental knowledge of data structures and algorithms: A grasp of basic data handling techniques will help in understanding AI system development.
  • Introduction to machine learning: Previous exposure to machine learning principles will be beneficial but is not strictly necessary. A desire to learn is key.
  • Familiarity with Linux/Unix commands: Basic navigation and command line usage will aid in interacting with open-source tools and models effectively.

These prerequisites are designed to ensure a foundational understanding that will enhance your learning experience in the course. Don't worry if you're not an expert in these areas—our course is structured to support your growth throughout the training.


Target Audience for Building Agentic AI Systems with Open-Source Models

  1. The Building Agentic AI Systems with Open-Source Models course equips professionals with skills to create intelligent AI systems using available frameworks, appealing to those keen on AI innovation.


  2. Target Audience and Job Roles:


  • Data Scientists
  • Machine Learning Engineers
  • AI Researchers
  • Software Developers
  • System Architects
  • Product Managers
  • IT Analysts
  • DevOps Engineers
  • Tech Entrepreneurs
  • Academic Researchers
  • IT Consultants
  • Business Analysts
  • Project Managers in Technology
  • Corporate Trainers in IT


Learning Objectives - What you will Learn in this Building Agentic AI Systems with Open-Source Models?

Introduction:
The Building Agentic AI Systems with Open-Source Models course empowers learners to design, implement, and evaluate autonomous AI systems using open-source frameworks, fostering a deep understanding of AI methodologies and their practical applications.

Learning Objectives and Outcomes:

  • Understand the foundational concepts of agentic AI systems.
  • Explore various open-source models and their capabilities.
  • Design autonomous systems utilizing predictive algorithms.
  • Implement machine learning techniques for real-world applications.
  • Analyze the ethical implications of AI systems.
  • Evaluate the efficacy of different AI models in performance metrics.
  • Collaborate on projects to build agentic AI applications.
  • Integrate natural language processing and computer vision in AI systems.
  • Troubleshoot and optimize AI models for high efficiency.
  • Stay updated with current trends and advancements in AI technology.

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