Artificial Intelligence (Mentor-Led Learning)

The Artificial Intelligence – Intermediate course is designed for learners who already understand basic AI concepts and want to advance into practical, industry-relevant Machine Learning techniques. This mentor-led program focuses on building strong analytical and problem-solving skills through hands-on implementation of core ML algorithms and real-world projects.

The course begins with a deep dive into Supervised and Unsupervised Learning, helping learners understand how machines learn from labeled and unlabeled data. Key algorithms such as Regression, Classification, and Clustering are explained with practical use cases, ensuring conceptual clarity and application readiness.

Learners will gain expertise in Feature Engineering, one of the most critical skills in Machine Learning, to improve model accuracy and performance. The program also covers Model Evaluation techniques, enabling learners to assess, compare, and optimize ML models using industry-standard metrics.

A strong emphasis is placed on Scikit-learn, the most widely used Machine Learning library in Python. Through guided, mentor-led sessions, learners will implement algorithms, preprocess datasets, and build end-to-end ML pipelines.

To bridge the gap between theory and industry expectations, the course includes real-world projects, preparing learners for roles in AI, Machine Learning, and Data Science. Upon successful completion, participants receive multiple certifications that add significant value to resumes and job applications.

This intermediate AI course is ideal for students, graduates, and professionals aiming to upskill and move toward advanced AI and Machine Learning careers.