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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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Course Advisor

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Simmi Anand

9+ Years Experience

I am Simmi Anand, a Microsoft Certified Trainer, and UiPath Certified Advanced RPA Developer with over 10 years of rich experience in corporate training and the IT sector. I have been working with Koenig Solutions for the past 7+ years, providing quality training on Robotic Process Automation using UiPath and Automation Anywhere. In addition, I also deliver training on Microsoft and Google technologies, including Mobile Application Development for Android, iOS with Swift, Hybrid Mobile Application using PhoneGap, Microsoft SQL Server, Microsoft PowerApps & Flow, Power Platform and PostgreSQL to global and corporate clients.
 
One reason I enjoy this field and the challenges that come with it is the opportunity to connect with people and solve their IT needs. I am also passionate about learning technologies and gaining solid knowledge about them. I have conducted various onsite training assignments globally with esteemed clients such as Microsoft - India, KPMG, Raw Bank - DRC, FRCI - Mauritius, Google Train the Trainer Project, Infosys, TCS, Wipro, and many others.

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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