This practical course focuses on designing and implementing neural networks for unstructured data using frameworks such as TensorFlow and Keras. Starting with architecture and different types of deep learning layers, it covers implementation methodologies, big data tools and application areas for customized as well as pre-built models, including generative AI.
Audience
This course is ideal for data engineers, data scientists, researchers, solution architects, software engineers, AI enthusiasts, statisticians, and other IT professionals looking for a practical foundation in deep learning with neural networks.
Course objectives At the end of this course, you will be able to:
• Design and develop neural network models in structured frameworks
• Understand core buzzwords and terminology
• Develop your own deep learning project
• Build a suitable deep learning model for a given problem statement
• Optimize the deep learning models through hyperparameter tuning
• Understand and apply generative AI in your own projects
• History of deep learning
• Overview of deep learning
• A single neuron
• What is a transfer function?
• Introduction to TensorFlow
• The TensorFlow architecture
• TensorFlow data
• Introduction to Keras
• The Keras architecture
• Keras models
• Keras sequential vs functional API
• Keras layers
• Keras core modules
• Overfitting and underfitting
• Overfitting & Underfitting: How to avoid?
• Activation functions
• Loss functions
• Optimization functions
• Why regularize?
• Regularization types
• Hyperparameters
• Optimization techniques
• Convolutions
• Pooling in neural networks
• The Big Data perspective
• The Big Data Deep Learning Team and Roles
• Apache Spark and Databricks
• Determined AI
• Ezmeral MLOps
• What is generative AI
• Generative models in AI
• Large language models (LLM)
• Applications of generative AI
• Responsible generative AI
Prerequisites
A basic understanding of any programming or scripting language would be helpful for this course.
Firma NT GROUP Sp. z o.o. jest Autoryzowanym partnerem firmy HPE
Spółka posiada wpis do ewidencji placówek niepublicznych Nr ew. ES.VIII.4320-6/p.n./2003 wydany z upoważnienia Prezydenta Miasta Łodzi
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