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Duration 35 hours
Course Outline
Introduction to AI in Python
- Core concepts and the scope of AI
- Essential Python libraries for AI development
- Structuring AI projects and managing workflows
Preparing Data for AI
- Data cleaning, transformation, and feature engineering
- Strategies for handling missing values and imbalanced data
- Techniques for feature scaling and encoding
Supervised Learning Approaches
- Algorithms for regression and classification
- Ensemble techniques including Random Forest and Gradient Boosting
- Hyperparameter tuning and cross-validation methods
Unsupervised Learning Strategies
- Clustering algorithms such as K-Means, DBSCAN, and hierarchical clustering
- Dimensionality reduction techniques like PCA and t-SNE
- Practical applications of unsupervised learning
Neural Networks and Deep Learning
- Foundations of TensorFlow and Keras
- Constructing and training feedforward neural networks
- Strategies for optimizing neural network performance
Introduction to Reinforcement Learning
- Key concepts: agents, environments, and reward structures
- Implementing foundational reinforcement learning algorithms
- Real-world applications of reinforcement learning
Deployment of AI Models
- Processes for saving and loading trained models
- Integrating models into applications via APIs
- Monitoring and maintaining AI systems in production environments
Conclusion and Future Directions
Requirements
- A strong grasp of fundamental Python programming concepts
- Proficiency with data analysis tools such as NumPy and pandas
- A foundational understanding of machine learning principles and algorithms
Target Audience
- Software developers looking to enhance their AI development capabilities
- Data analysts interested in applying AI techniques to complex datasets
- R&D specialists focused on building AI-powered 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
