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Course Outline
Introduction to Artificial Intelligence
- Defining AI and its applications.
- Distinguishing between AI, Machine Learning, and Deep Learning.
- Overview of popular tools and platforms.
Python for AI
- Refresher on Python fundamentals.
- Utilizing Jupyter Notebook.
- Installing and managing libraries.
Working with Data
- Data preparation and cleaning techniques.
- Leveraging Pandas and NumPy.
- Visualization using Matplotlib and Seaborn.
Machine Learning Basics
- Contrasting Supervised and Unsupervised Learning.
- Covering classification, regression, and clustering.
- Model training, validation, and testing processes.
Neural Networks and Deep Learning
- Exploring neural network architecture.
- Working with TensorFlow or PyTorch.
- Constructing and training models.
Natural Language and Computer Vision
- Text classification and sentiment analysis.
- Fundamentals of image recognition.
- Utilizing pre-trained models and transfer learning.
Deploying AI in Applications
- Saving and loading models.
- Integrating AI models into APIs or web applications.
- Best practices for testing and maintenance.
Summary and Next Steps
Requirements
- A solid understanding of programming logic and structures
- Experience with Python or comparable high-level programming languages
- Basic familiarity with algorithms and data structures
Audience
- IT systems professionals
- Software developers aiming to integrate AI capabilities
- Engineers and technical managers exploring AI-based solutions
40 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 8000 € + VAT*
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Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
