Build a strong mathematical foundation for Machine Learning and Artificial Intelligence with this comprehensive course on Probability and Statistics.
This course is designed to help you understand how data behaves, how models make predictions, and how to validate results using statistical techniques—skills that are essential for every AI and ML professional.
You will start with probability theory and random variables, learning how uncertainty is modeled in real-world systems. Then, you will explore probability distributions used in machine learning, such as normal, binomial, and Poisson distributions.
Next, the course dives into statistical inference, where you’ll learn estimation techniques and confidence intervals to draw meaningful conclusions from data.
You will also master hypothesis testing and p-values, enabling you to make data-driven decisions and validate assumptions in ML models. Different types of hypothesis tests are covered with practical examples.
Further, you’ll learn correlation and regression analysis, which are fundamental to predictive modeling and feature relationships in machine learning.
Finally, you will apply all concepts in a real-world statistical analysis project, working with actual datasets to simulate industry-level data science workflows.
External Reference
Coursera (ML/Statistics courses)
Internal Reference
Data Science Essentials for AI with Python
Founder & Chief Trainer | EDUNAVO | Telecom, AI, Cloud & Cyber Security Learning Leader
Technology leader, corporate trainer, and entrepreneur with 18+ years of experience in the ICT industry, spanning Telecom, Software Engineering, Cloud Computing, Cyber Security, AI/ML, and Management domains.
As Founder & Chief Trainer at EDUNAVO, I help professionals, engineers, and organizations build industry-ready skills through practical, hands-on, and outcome-driven learning programs.
Core Expertise:
• 5G Testing & Automation
• 5G Protocol & Device Testing
• Telecom Development & Open RAN
• Cloud Computing & AWS
• Cyber Security
• Artificial Intelligence & Machine Learning
• Software Development & Automation
• Project & Technology Management
Key Achievements:
• Trained 5,000+ students and professionals globally
• Created and delivered 30+ industry-focused certification programs
• Designed 20+ animated practical labs and simulation-based learning modules
• Built and deployed 8+ open-source lab environments for hands-on training
• Served 10+ corporate and institutional clients
• Expanded EDUNAVO's learner presence across 20+ countries
• Delivered corporate training programs in Telecom, Cloud, AI, Cyber Security, and Software Engineering domains
• Mentored engineers for career transitions, certifications, and interview success
At EDUNAVO, our mission is simple: bridge the gap between academic learning and real-world industry expectations through practical, job-oriented, and future-ready training.
"Learn Skills. Build Confidence. Accelerate Careers."
