Course Outline
Introduction
- Defining Predictive AI for Government
- Historical Context and Evolution of Predictive Analytics in the Public Sector
- Basic Principles of Machine Learning and Data Mining for Government Applications
Data Collection and Preprocessing
- Gathering Relevant Data for Government Use
- Cleaning and Preparing Data for Analysis in Public Sector Workflows
- Understanding Data Types and Sources for Government Projects
Exploratory Data Analysis (EDA)
- Visualizing Data for Insights in Government Operations
- Descriptive Statistics and Data Summarization for Public Sector Decision-Making
- Identifying Patterns and Relationships in Data for Government Applications
Statistical Modeling
- Basics of Statistical Inference for Government Analysis
- Regression Analysis for Predictive Governance
- Classification Models for Policy and Program Evaluation
Machine Learning Algorithms for Prediction
- Overview of Supervised Learning Algorithms for Government Use
- Decision Trees and Random Forests in Public Sector Predictive Analytics
- Neural Networks and Deep Learning Basics for Government Applications
Model Evaluation and Selection
- Understanding Model Accuracy and Performance Metrics for Government Projects
- Cross-Validation Techniques for Public Sector Data Analysis
- Overfitting and Model Tuning in Government Predictive Models
Practical Applications of Predictive AI for Government
- Case Studies Across Various Industries and Their Relevance to the Public Sector
- Ethical Considerations in Predictive Modeling for Government
- Limitations and Challenges of Predictive AI in the Public Sector
Hands-On Project
- Working with a Dataset to Create a Predictive Model for Government Use
- Applying the Model to Make Predictions in Government Operations
- Evaluating and Interpreting the Results for Public Sector Decision-Making
Summary and Next Steps
Requirements
- A foundational understanding of basic statistics
- Experience with any programming language
- Familiarity with data management and spreadsheet applications
- No prior experience in artificial intelligence or data science is required
Audience for Government
- IT professionals
- Data analysts
- Technical staff
Testimonials (3)
basics and loved the prepared documents and exercises
Rekha Nallam - GE Medical Systems Polska Sp. z o.o.
Course - Introduction to Predictive AI
Opportunity to use a pre-created models, understand how do they work and tweak them live and see the results. Choice ov VSCode with Jupyter was a perfect option for such way of leading the training.
Krzysztof - GE Medical Systems Polska Sp. z o.o.
Course - Introduction to Predictive AI
Difficult topics presented in simple, user-friendly way
