Build Machine Learning Models

Build Machine Learning Models Exam

Creating Machine Learning Models involves training computers to find patterns in data and use those patterns for predictions. Instead of writing strict instructions, developers provide examples, and the model figures out how to make decisions on its own. This makes machine learning useful for areas like speech recognition, fraud detection, and customer personalization.

Through this certification, learners explore how to prepare data, choose the right algorithm, and test the accuracy of their models. The goal is to make complex machine learning ideas approachable for anyone with a basic interest in programming and analytics. By applying these skills, learners can develop intelligent systems that bring automation and efficiency to real-world tasks.

Who should take the Exam?

This exam is ideal for:

• Data Analysts
• Data Scientists (entry-level or aspiring)
• Software Developers
• AI Enthusiasts
• Business Analysts
• Machine Learning Engineers (beginner level)

Skills Required

• Basic knowledge of Python programming
• Understanding of statistics and math concepts
• Logical thinking and problem-solving
• Interest in data analysis and modeling

Course Outline

• Domain 1 - Introduction to Machine Learning
• Domain 2 - Data Preparation
• Domain 3 - Supervised Learning Algorithms
• Domain 4 - Unsupervised Learning Algorithms
• Domain 5 - Model Training and Testing
• Domain 6 - Optimization and Tuning
• Domain 7 - Deep Learning Basics
• Domain 8 - Deployment of Models
• Domain 9 - Real-World Applications