Machine Learning with Python (IBM) Course with Internship (Mentor-Led Learning)

The Machine Learning with Python (IBM) Course is an industry-aligned, hands-on program designed to help learners build predictive machine learning models using Python and widely-used ML libraries. This program focuses on both supervised and unsupervised learning techniques, enabling learners to develop end-to-end machine learning solutions.

Aligned with industry practices inspired by IBM, this course emphasizes real-world implementation of machine learning workflows. Learners gain practical experience with Python-based ML tools such as Scikit-learn, model evaluation techniques, and optimization strategies used in professional environments.

During the first month of training, learners focus on Python fundamentals for machine learning, core ML algorithms, model building, and evaluation metrics. The curriculum is designed to ensure conceptual clarity along with strong hands-on coding exposure.

The second month is internship-focused, where learners work on a real-world machine learning project, perform cross-validation and hyperparameter tuning, and understand the basics of model deployment. This project-driven approach helps learners gain practical experience and build a job-ready ML portfolio.

By the end of this program, learners will be able to:

• Build machine learning models using Python

• Apply supervised and unsupervised learning techniques

• Evaluate, tune, and optimize ML models

• Understand end-to-end ML workflows and deployment basics

This course is ideal for students, freshers, and professionals aiming to start a career in Machine Learning, Data Analytics, or Python Development.