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Duration 40 hours
Course Outline
Overview of Artificial Intelligence
- Definition of AI and its applications in the public sector
- Differentiating AI, Machine Learning, and Deep Learning
- Industry-standard tools and platforms for government use
Python for AI Development
- Review of core Python programming principles
- Utilizing Jupyter Notebook for analysis
- Installation and management of required libraries
Data Management for Government Applications
- Data preparation and cleansing procedures
- Application of Pandas and NumPy frameworks
- Data visualization using Matplotlib and Seaborn
Fundamentals of Machine Learning
- Comparison of supervised and unsupervised learning methods
- Techniques for classification, regression, and clustering
- Model training, validation, and testing protocols
Neural Networks and Advanced Deep Learning
- Architecture of neural networks
- Implementation using TensorFlow or PyTorch
- Construction and training of deep learning models
Natural Language Processing and Computer Vision
- Text classification and sentiment analysis capabilities
- Core principles of image recognition
- Leveraging pre-trained models and transfer learning
Deployment of AI for Government Services
- Procedures for saving and loading models
- Integration of AI models into APIs and web applications
- Best practices for system testing and ongoing maintenance
Summary and Future Directions
Requirements
- Proficiency in programming logic and structural design
- Practical experience with Python or comparable high-level programming languages
- Foundational knowledge of algorithms and data structures
Target Audience
- Information technology systems professionals
- Software developers integrating AI capabilities
- Engineers and technical managers evaluating AI-based solutions for government use
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
