DEEP LEARNING AND COMPLEX ALGORITHMS

Required background: basic AI and programming skills, practical experience
Number of training days: 5 days

Training objective:
The training will provide participants with a deeper knowledge of AI, with which they will be able to solve complex problems and apply AI technologies to larger projects.

Description of the training:
The training will provide a deeper insight into the operation of neural networks, including their building blocks and applications. We will also learn in detail about deep learning techniques such as convolutional neural networks and recurrent neural networks. We will then turn to the application of AI in image recognition and language processing, as well as in time series analysis. Finally, through practical examples, we will practice the use of complex algorithms to solve various real-world problems.

Detailed topics:

Day 1: Basics of neural networks

  • Introduction to neural networks and their building blocks
  • Overview of different types of neural networks (e.g. multilayer perceptron, convolutional networks, recurrent networks)
  • Basic neural network structures and deep learning principles

Day 2: deep learning techniques and algorithms

  • Deep learning principles and techniques
  • Convolutional Neural Networks (CNN) and their applications (e.g. image recognition)
  • Recurrent neural networks (RNN) and their applications (e.g. language processing, time series analysis)

Day 3: Image processing and recognition using deep learning

  • Deep learning applications in image recognition and processing
  • Image processing techniques and algorithms (e.g. image segmentation, object recognition)
  • Practical examples and project work in image recognition

Day 4: Language processing and time series analysis with deep learning algorithms

  • Deep learning applications in language processing (e.g. text generation, machine translation)
  • Time series analysis and predictive model building with deep learning algorithms
  • Practical examples and project work in language processing and time series analysis

Day 5: Complex algorithms and project work in deep learning

  • Application of complex deep learning algorithms to solve real problems
  • Project work and practical exercises
  • Presentation and feedback on deep learning projects completed by participants

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