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Duration 35 hours
Course Outline
Introduction to AI within Python
- Fundamental concepts and the reach of AI
- Python tools and libraries for AI creation
- Structuring AI projects and defining workflows
Preparing Data for AI
- Processes for data cleansing, modification, and feature creation
- Managing missing values and dataset imbalances
- Techniques for feature scaling and encoding
Methods for Supervised Learning
- Algorithms for regression and classification tasks
- Ensemble strategies: Random Forest and Gradient Boosting
- Techniques for hyperparameter tuning and cross-validation
Methods for Unsupervised Learning
- Clustering approaches: K-Means, DBSCAN, and hierarchical clustering
- Dimensionality reduction techniques: PCA and t-SNE
- Practical applications of unsupervised learning
Neural Networks and Deep Learning
- Getting started with TensorFlow and Keras
- Constructing and training feedforward neural networks
- Strategies for optimizing neural network outcomes
Reinforcement Learning (Foundations)
- Essential ideas regarding agents, environments, and reward systems
- Building foundational reinforcement learning algorithms
- Real-world uses of reinforcement learning
Rolling Out AI Models
- Persisting and retrieving trained models
- Embedding models into applications through APIs
- Overseeing and maintaining AI systems in live production environments
Conclusion and Future Directions
Requirements
- A strong grasp of fundamental Python programming principles
- Practical experience with data analysis tools such as NumPy and pandas
- Familiarity with basic machine learning theories and algorithms
Target Audience
- Software engineers aiming to broaden their capabilities in AI development
- Data analysts looking to apply AI methodologies to intricate datasets
- R&D specialists involved in creating AI-enabled applications
Testimonials (2)
The trainer was very available to answer all te kind of question I did
Caterina - Stamtech
Course - Developing APIs with Python and FastAPI
Trainer develops training based on participant's pace
