Advanced AI Development with GPT, Langchain and Pandas
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Design and train advanced neural network architectures for complex tasks
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Apply transfer learning to accelerate AI model development in new domains
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Implement explainability techniques to increase model transparency and trust
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Deploy and scale AI models using cloud-native tools and practices
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Integrate AI components into applications via APIs and microservices
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Monitor and maintain model performance in live environments.
Overview
Off the shelf (OTS)
This course is designed for experienced developers, data scientists, and technical architects who want to deepen their knowledge of artificial intelligence systems. It is particularly suited to those involved in building advanced AI applications, integrating AI components into production systems, or scaling machine learning pipelines.
Strong experience in Python programming and familiarity with machine learning concepts and frameworks such as TensorFlow or PyTorch is essential. Prior experience with cloud environments and API development is recommended.
The Advanced AI Development Training Course focuses on the end-to-end development, deployment, and optimisation of AI models for real-world applications. Participants will explore advanced topics in neural network design, transfer learning, model interpretability, and production deployment strategies. The course also includes hands-on work with state-of-the-art frameworks and APIs for integrating AI models into scalable architectures. Emphasis is placed on both the technical and operational challenges of deploying robust and maintainable AI systems.
Key Topics Covered:
• Advanced neural network architectures and deep learning techniques
• Transfer learning and model fine-tuning for domain-specific applications
• Explainable AI (XAI) and model interpretability tools
• Scaling AI workloads in cloud environments
• Monitoring and maintaining AI models in production
• Building and integrating AI APIs and microservices
The course is delivered over two days and includes practical coding exercises and real-world deployment scenarios.
Delivery method
Virtual
Course duration
14 hours
Competency level
Working

Delivery method
-
Virtual
Course duration
14 hours
Competency level
-
Working
