Course Outline
Lesson 1: Solving Business Problems Using AI and ML for Government
- Topic A: Identify AI and ML Solutions for Business Challenges
- Topic B: Formulate a Machine Learning Problem Statement
- Topic C: Select Appropriate Tools and Technologies
Lesson 2: Collecting and Refining the Dataset for Government Use
- Topic A: Collect the Required Dataset
- Topic B: Analyze the Dataset to Gain Insights
- Topic C: Utilize Visualizations to Analyze Data
- Topic D: Prepare Data for Analysis and Modeling
Lesson 3: Setting Up and Training a Model for Government Applications
- Topic A: Set Up a Machine Learning Model Framework
- Topic B: Train the Model with Public Sector Data
Lesson 4: Finalizing a Model for Government Use
- Topic A: Translate Model Results into Actionable Insights
- Topic B: Incorporate the Model into Long-Term Strategic Solutions
Lesson 5: Building Linear Regression Models for Government Analysis
- Topic A: Construct a Regression Model Using Linear Algebra Techniques
- Topic B: Develop Regularized Regression Models Using Linear Algebra
- Topic C: Create Iterative Linear Regression Models
Lesson 6: Building Classification Models for Government Applications
- Topic A: Train Binary Classification Models
- Topic B: Train Multi-Class Classification Models
- Topic C: Evaluate the Performance of Classification Models
- Topic D: Optimize and Tune Classification Models
Lesson 7: Building Clustering Models for Government Data
- Topic A: Construct k-Means Clustering Models
- Topic B: Develop Hierarchical Clustering Models
Lesson 8: Building Advanced Models for Government Use
- Topic A: Build Decision Tree Models
- Topic B: Construct Random Forest Models
Lesson 9: Building Support-Vector Machines for Government Applications
- Topic A: Develop SVM Models for Classification Tasks
- Topic B: Create SVM Models for Regression Analysis
Lesson 10: Building Artificial Neural Networks for Government Use
- Topic A: Construct Multi-Layer Perceptrons (MLP)
- Topic B: Develop Convolutional Neural Networks (CNN)
Lesson 11: Promoting Data Privacy and Ethical Practices for Government
- Topic A: Protect Data Privacy in Government Operations
- Topic B: Promote Ethical Practices in Data Use
- Topic C: Establish Policies for Data Privacy and Ethics
Requirements
To ensure your success in this course, you should have a foundational understanding of key artificial intelligence (AI) concepts. This includes, but is not limited to, machine learning, supervised and unsupervised learning, artificial neural networks, computer vision, and natural language processing. You can achieve this level of knowledge by completing the CertNexus AIBIZ™ (Exam AIZ-110) course.
Additionally, you should have practical experience working with databases and a high-level programming language such as Python, Java, or C/C++. You can acquire these skills and knowledge through courses offered by Logical Operations or comparable programs, including:
- Database Design: A Modern Approach
- Python® Programming: Introduction
- Python® Programming: Advanced
These prerequisites are essential for government professionals to effectively engage with and apply AI technologies in their respective roles.
