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Duration 35 hours
Course Outline
Introduction to AI in Python
- Foundational concepts and the scope of AI
- Essential Python libraries for AI development
- Structuring AI projects and establishing effective workflows
Data Preparation for AI
- Data cleaning, transformation, and feature engineering
- Managing missing values and imbalanced data sets
- Techniques for feature scaling and encoding
Supervised Learning Techniques
- Algorithms for regression and classification
- Ensemble methods including Random Forest and Gradient Boosting
- Hyperparameter optimization and cross-validation strategies
Unsupervised Learning Techniques
- Clustering algorithms such as K-Means, DBSCAN, and hierarchical clustering
- Dimensionality reduction techniques including PCA and t-SNE
- Practical use cases for unsupervised learning
Neural Networks and Deep Learning
- Getting started with TensorFlow and Keras
- Constructing and training feedforward neural networks
- Strategies for optimizing neural network performance
Introduction to Reinforcement Learning
- Core principles involving agents, environments, and reward systems
- Implementing fundamental reinforcement learning algorithms
- Real-world applications of reinforcement learning
Deploying AI Models
- Persistence of trained models through saving and loading mechanisms
- Integrating models into applications via API endpoints
- Monitoring and maintaining AI systems in production environments
Summary and Future Directions
Requirements
- A strong grasp of core Python programming fundamentals
- Practical experience with data analysis tools such as NumPy and pandas
- Familiarity with foundational machine learning concepts and standard algorithms
Target Audience
- Software engineers seeking to broaden their expertise in AI development
- Data analysts looking to apply AI methodologies to complex data sets
- R&D specialists focused on creating AI-driven 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
