Courses

The Machine Learning Specialist program provides in-depth training in the principles,
algorithms, and systems that power modern data-driven intelligence. Students will learn to
design, implement, and evaluate Machine Learning (ML) models capable of performing
a wide range of predictive and analytical tasks across industries.

This program develops both theoretical understanding and practical proficiency in
supervised, unsupervised, and reinforcement learning techniques, along with the
knowledge to build and deploy scalable ML systems. Graduates will be able to translate
data patterns into actionable insights that create measurable business value.

What You’ll Learn

• Fundamentals of Machine Learning theory and model types
• Supervised learning (regression, classification, decision trees, ensemble methods)
• Unsupervised learning (clustering, dimensionality reduction, anomaly detection)
• Neural networks and deep learning essentials
• Feature engineering and model evaluation metrics
• Data preprocessing, normalization, and handling imbalanced datasets
• Deployment of ML models using APIs, containers, and cloud platforms

Topics Covered

• Model training, tuning, and validation workflows
• Overfitting, bias-variance tradeoff, and regularization
• Machine Learning frameworks: TensorFlow, scikit-learn, and PyTorch overview
• Explainable AI (XAI) and model interpretability
• Integrating ML with cybersecurity and IoT systems
• Ethics, fairness, and governance in AI and ML applications

Format & Materials

• Instructor-led sessions and interactive code labs
• Practical exercises with real-world datasets and ML frameworks
• Capstone project: design, train, and deploy a functional ML model

Prerequisites

• Basic programming skills in Python or similar language
• Familiarity with statistics and data analysis concepts recommended

Outcomes & Next Steps

• Understand core ML concepts and how to select appropriate algorithms
• Develop and evaluate predictive models using modern tools
• Prepare for the Machine Learning Specialist Certification Exam
• Advance toward roles such as ML Engineer, Data Scientist, or AI Analyst