Artificial Intelligence (AI) for Developers Training Course
Artificial Intelligence (AI) comprises technologies that mimic human intelligence within machines and applications, facilitating the creation of smarter and more adaptable software.
This instructor-led live training, available online or on-site, targets intermediate developers aiming to construct AI-powered applications using practical tools and platforms.
Upon completion of this training, participants will be capable of:
- Grasping fundamental AI and machine learning concepts.
- Creating AI features utilizing Python and widely adopted libraries.
- Applying AI methodologies to real-world software development projects.
- Evaluating models and deploying intelligent services.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Practical implementation within a live laboratory environment.
Customization Options
- To arrange customized training for this course, please contact us.
Course Outline
Introduction to Artificial Intelligence
- Definition of AI and its applications
- Distinctions between AI, Machine Learning, and Deep Learning
- Overview of popular tools and platforms
Python for AI
- Refresher on Python fundamentals
- Utilizing Jupyter Notebook
- Installation and management of libraries
Working with Data
- Data preparation and cleaning processes
- Leveraging Pandas and NumPy
- Data visualization with Matplotlib and Seaborn
Machine Learning Basics
- Supervised vs. Unsupervised Learning
- Classification, regression, and clustering techniques
- Model training, validation, and testing
Neural Networks and Deep Learning
- Neural network architecture
- Utilizing TensorFlow or PyTorch
- Constructing and training models
Natural Language and Computer Vision
- Text classification and sentiment analysis
- Fundamentals of image recognition
- 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
- Proficiency in 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
- Engineers and technical managers investigating AI-based solutions
Open Training Courses require 5+ participants.
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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
Michal Maj - XL Catlin Services SE (AXA XL)
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