Machine Learning (Mentor-Led Learning)

The Machine Learning – Intermediate course is designed for learners who have basic knowledge of Python and Machine Learning concepts and want to advance into core ML algorithms and supervised learning techniques. This mentor-led program focuses on algorithmic understanding, logical reasoning, and practical implementation.

The curriculum begins with types of Machine Learning, providing clarity on supervised, unsupervised, and semi-supervised learning. Special emphasis is placed on supervised learning and its categories, helping learners understand how labeled data is used to build predictive models.

Participants will gain in-depth knowledge of K-Nearest Neighbors (KNN) and Linear Regression algorithms, including their mathematical intuition, logic, and real-world applications. A unique feature of this course is the implementation of ML algorithms using Excel, enabling learners to understand algorithm behavior step by step without heavy coding.

Delivered in a mentor-led format, the course emphasizes conceptual clarity, guided practice, and industry-aligned teaching methods. Upon successful completion, learners receive industry-recognized certifications, including participation, industrial training, and internship completion certificates.

This intermediate Machine Learning course is ideal for students, analysts, and professionals who want to strengthen their understanding of supervised learning before moving into advanced ML models and Python-based implementations.