Intelligent Applications Training in Minneapolis

This instructor-led, live training in Minneapolis (online or onsite) is designed for intermediate to advanced artificial intelligence (AI) professionals and software developers who are interested in building intelligent applications using AI and machine learning (ML) techniques.

By the end of this training, participants will be able to:

• Comprehend the advanced principles and technologies underlying AI and ML.
• Analyze and visualize data to support the development of AI/ML models.
• Construct, train, and deploy AI/ML models efficiently.
• Develop intelligent applications capable of addressing real-world challenges.
• Assess the ethical implications of AI applications across various sectors, including those for government.

This instructor-led, live training in Minneapolis (online or onsite) is aimed at intermediate to advanced data scientists, engineers, and artificial intelligence practitioners who wish to master the complexities of intelligent applications and leverage them to address sophisticated, real-world challenges for government.

By the end of this training, participants will be able to:

• Implement and evaluate deep learning architectures.
• Apply machine learning at scale within a distributed computing environment.
• Design and execute reinforcement learning models for decision-making processes.
• Develop advanced natural language processing systems for enhanced language understanding.
• Utilize computer vision techniques for comprehensive image and video analysis.
• Address ethical considerations in the development and deployment of AI systems for government.

This instructor-led, live training in Minneapolis (online or onsite) is aimed at beginner-level IT professionals who wish to gain a foundational understanding of intelligent applications and their application across various industries for government.

By the end of this training, participants will be able to:

• Understand the history, principles, and impact of artificial intelligence in public sector contexts.
• Identify and apply different machine learning algorithms suitable for government use cases.
• Manage and analyze data effectively to support AI applications in governmental workflows.
• Recognize the practical applications and limitations of AI technology within different sectors, including those relevant to government operations.
• Discuss the ethical considerations and societal implications of AI technology, particularly as they pertain to government responsibilities and public trust.