CMU Course Reviews
Carnegie Mellon University
| Code | Name | Overall | Easiness | Interest | Usefulness | Reviewssorted descending |
|---|---|---|---|---|---|---|
| MLG 10701 | Introduction to Machine Learning (PhD) | 0 | 0 | 0 | 0 | 0 |
| MLG 10335 | Art and Machine Learning | 0 | 0 | 0 | 0 | 0 |
| MLG 10403 | Deep Reinforcement Learning & Control | 0 | 0 | 0 | 0 | 0 |
| MLG 10414 | Deep Learning Systems: Algorithms and Implementation | 0 | 0 | 0 | 0 | 0 |
| MLG 10418 | Machine Learning for Structured Data | 0 | 0 | 0 | 0 | 0 |
| MLG 10520 | Independent Study | 0 | 0 | 0 | 0 | 0 |
| MLG 10605 | Machine Learning with Large Datasets | 0 | 0 | 0 | 0 | 0 |
| MLG 10607 | Computational Foundations for Machine Learning | 0 | 0 | 0 | 0 | 0 |
| MLG 10613 | Machine Learning Ethics and Society | 0 | 0 | 0 | 0 | 0 |
| MLG 10617 | Intermediate Deep Learning | 0 | 0 | 0 | 0 | 0 |
| MLG 10620 | Independent Study: Research | 0 | 0 | 0 | 0 | 0 |
| MLG 10315 | Introduction to Machine Learning (SCS Majors) | 0 | 0 | 0 | 0 | 0 |
| MLG 10707 | Advanced Deep Learning | 0 | 0 | 0 | 0 | 0 |
| MLG 10712 | Fairness, Explainability, and Accountability for Machine Lea... | 0 | 0 | 0 | 0 | 0 |
| MLG 10714 | Deep Learning Systems: Algorithms and Implementation | 0 | 0 | 0 | 0 | 0 |
| MLG 10716 | Advanced Machine Learning: Theory and Methods | 0 | 0 | 0 | 0 | 0 |
| MLG 10721 | Philosophical Foundations of Machine Intelligence | 0 | 0 | 0 | 0 | 0 |
| MLG 10730 | Advanced AI and Brain Seminar | 0 | 0 | 0 | 0 | 0 |
| MLG 10745 | Scalability in Machine Learning | 0 | 0 | 0 | 0 | 0 |
| MLG 10805 | Machine Learning with Large Datasets | 0 | 0 | 0 | 0 | 0 |
| MLG 10920 | Graduate Reading and Research | 0 | 0 | 0 | 0 | 0 |
| MLG 10935 | Practicum | 0 | 0 | 0 | 0 | 0 |
| MLG 10713 | Machine Learning Ethics and Society | 0 | 0 | 0 | 0 | 0 |
| MLG 10417 | Intermediate Deep Learning | 0 | 0 | 0 | 0 | 0 |
| MLG 10500 | Senior Research Project | 0 | 0 | 0 | 0 | 0 |
| MLG 10601 | Introduction to Machine Learning (Master's) | 0 | 0 | 0 | 0 | 0 |
| MLG 10606 | Mathematical Foundations for Machine Learning | 0 | 0 | 0 | 0 | 0 |
| MLG 10611 | MS DAP Research | 0 | 0 | 0 | 0 | 0 |
| MLG 10615 | Art and Machine Learning | 0 | 0 | 0 | 0 | 0 |
| MLG 10618 | Machine Learning for Structured Data | 0 | 0 | 0 | 0 | 0 |
| MLG 10697 | Reading and Research | 0 | 0 | 0 | 0 | 0 |
| MLG 10703 | Deep Reinforcement Learning & Control | 0 | 0 | 0 | 0 | 0 |
| MLG 10708 | Probabilistic Graphical Models | 0 | 0 | 0 | 0 | 0 |
| MLG 10405 | Machine Learning with Large Datasets (Undergraduate) | 0 | 0 | 0 | 0 | 0 |
| MLG 10715 | Advanced Introduction to Machine Learning | 0 | 0 | 0 | 0 | 0 |
| MLG 10718 | Machine Learning in Practice | 0 | 0 | 0 | 0 | 0 |
| MLG 10725 | Convex Optimization | 0 | 0 | 0 | 0 | 0 |
| MLG 10737 | Creative AI | 0 | 0 | 0 | 0 | 0 |
| MLG 10777 | Historical Advances in Machine Learning | 0 | 0 | 0 | 0 | 0 |
| MLG 10910 | PhD DAP Research | 0 | 0 | 0 | 0 | 0 |
| MLG 10930 | Dissertation Research | 0 | 0 | 0 | 0 | 0 |
| MLG 10940 | Independent Study | 0 | 0 | 0 | 0 | 0 |
| MLG 10301 | Introduction to Machine Learning | 0 | 0 | 0 | 0 | 0 |
MLG 10701
Introduction to Machine Learning (PhD)
MLG 10335
Art and Machine Learning
MLG 10403
Deep Reinforcement Learning & Control
MLG 10414
Deep Learning Systems: Algorithms and Implementation
MLG 10418
Machine Learning for Structured Data
MLG 10520
Independent Study
MLG 10605
Machine Learning with Large Datasets
MLG 10607
Computational Foundations for Machine Learning
MLG 10613
Machine Learning Ethics and Society
MLG 10617
Intermediate Deep Learning
MLG 10620
Independent Study: Research
MLG 10315
Introduction to Machine Learning (SCS Majors)
MLG 10707
Advanced Deep Learning
MLG 10712
Fairness, Explainability, and Accountability for Machine Lea...
MLG 10714
Deep Learning Systems: Algorithms and Implementation
MLG 10716
Advanced Machine Learning: Theory and Methods
MLG 10721
Philosophical Foundations of Machine Intelligence
MLG 10730
Advanced AI and Brain Seminar
MLG 10745
Scalability in Machine Learning
MLG 10805
Machine Learning with Large Datasets
MLG 10920
Graduate Reading and Research
MLG 10935
Practicum
MLG 10713
Machine Learning Ethics and Society
MLG 10417
Intermediate Deep Learning
MLG 10500
Senior Research Project
MLG 10601
Introduction to Machine Learning (Master's)
MLG 10606
Mathematical Foundations for Machine Learning
MLG 10611
MS DAP Research
MLG 10615
Art and Machine Learning
MLG 10618
Machine Learning for Structured Data
MLG 10697
Reading and Research
MLG 10703
Deep Reinforcement Learning & Control
MLG 10708
Probabilistic Graphical Models
MLG 10405
Machine Learning with Large Datasets (Undergraduate)
MLG 10715
Advanced Introduction to Machine Learning
MLG 10718
Machine Learning in Practice
MLG 10725
Convex Optimization
MLG 10737
Creative AI
MLG 10777
Historical Advances in Machine Learning
MLG 10910
PhD DAP Research
MLG 10930
Dissertation Research
MLG 10940
Independent Study
MLG 10301
Introduction to Machine Learning