ML concepts, supervised learning, and AI product thinking
Non-mathy introduction to ML — regression, classification, metrics, and when to use AI.
This roadmap is designed from fresher to professional level: you start with fundamentals, move to guided implementation, and finish with production-grade workflows.
Supervised vs unsupervised, bias, datasets.
Hands-on focus: ML basics, Datasets.
Regression, classification, validation.
Hands-on focus: Training, Metrics.
LLMs vs ML, ethics, roadmaps.
Hands-on focus: LLM, Ethics.
Python scikit-learn and notebooks.
Hands-on focus: scikit-learn, Labs.
Developers and learners targeting AI & ML growth at Beginner level with practical, mentor-guided learning.
Live Online delivery with 6 Weeks schedule, structured modules, and real project implementation support.
Hands-on portfolio work, interview-oriented practice, and an industry-aligned syllabus designed for hiring readiness.
Sandeep Pal
Senior Software Engineer & Mentor
