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Accelerating Development with AI: Practical Workflows for Java, .NET, and Python Course Overview

Accelerating Development with AI: Practical Workflows for Java, .NET, and Python Course Overview

Accelerating Development with AI: Practical Workflows for Java, .NET, and Python is a hands-on course designed to enhance your programming skills by leveraging artificial intelligence. Participants will learn to integrate AI tools into their development processes, fostering greater efficiency and innovation. Key learning objectives include understanding how to automate repetitive tasks, improve code quality, and enhance application performance using AI-driven solutions. The course emphasizes practical applications, allowing students to implement workflows that can be immediately applied to real-world projects. Join us to unlock the potential of AI and transform your software development approach, positioning yourself at the forefront of technology.

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  • Live Training (Duration : 08 Hours)
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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

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

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Target Audience for Accelerating Development with AI: Practical Workflows for Java, .NET, and Python

Accelerating Development with AI focuses on enhancing programming efficiencies in Java, .NET, and Python through AI-powered workflows, targeting professionals looking to advance their skills and optimize software development processes.


  • Software Developers
  • Application Architects
  • Data Scientists
  • AI/ML Engineers
  • DevOps Engineers
  • Technical Managers
  • IT Project Managers
  • System Analysts
  • Database Administrators
  • Software Quality Assurance Engineers
  • IT Consultants
  • Full Stack Developers
  • Web Developers
  • Business Analysts
  • Technology Enthusiasts


Learning Objectives - What you will Learn in this Accelerating Development with AI: Practical Workflows for Java, .NET, and Python?

Course Introduction: The "Accelerating Development with AI: Practical Workflows for Java, .NET, and Python" course empowers developers to integrate AI technologies into their applications, enhancing productivity and innovation through practical workflows.

Learning Objectives and Outcomes:

  • Understand the fundamentals of AI and its application in software development.
  • Explore AI integration techniques using Java, .NET, and Python.
  • Develop practical skills in building AI-driven features within applications.
  • Learn to streamline workflows to enhance development efficiency.
  • Gain proficiency in utilizing AI libraries and tools specific to each programming language.
  • Implement best practices for testing and deploying AI-enabled applications.
  • Analyze real-world case studies to understand AI’s impact on development processes.
  • Foster collaboration between AI specialists and software developers.
  • Evaluate performance metrics for AI algorithms in applications.
  • Stay current with the latest trends in AI technologies and frameworks.

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