Approved Courses

The following courses are normally approved by the graduate committee:

Purdue Computer Science courses:

• CS courses at the 500 level or above, when taught by a faculty member whose primary appointment is in the CS department (except CS 50100, 50010, 50011, 50023, 50024, 50025 and certain CS 59000, 59200 and 59300 courses).

Other Purdue courses (not approved on doctoral plans of study under the 2016 rule set):

• BIOL 517: Molecular Biology: Proteins -- if taken for the Computational Life Sciences concentration
• BIOL 541: Molecular Genetics of Bacteria -- if taken for the Computational Life Sciences concentration

• CHM 696: Quantum Information and Computation

• ECE 51012: Electromechanics
• ECE 547: Introduction to Computer Communication Networks -- must also include CS 536 on plan
• ECE 563: Programming Parallel Machines
• ECE 565: Computer Architecture
• ECE 570: Artificial Intelligence
• ECE 600: Random Variables and Signals
• ECE 629: Introduction to Neural Networks
• ECE 637: Digital Image Processing
• ECE 661: Computer Vision
• ECE 673: Dist Computer System
• ECE 60872: Fault-Tolerant Computer System Design (previously ECE 695B)

• IE 535: Linear Programming
• IE 538: Nonlinear Optimization Algorithms and Models
• IE 547: Programming Languages for Artificial Intelligence (ECE 570)
• IE 580: Systems Simulation
• IE 635: Theoretical Foundation of Optimization
• IE 674: Computer And Communication Methods For Production Control I

• LING 593: Natural Language Knowledge Representation

• MA 511:  Linear Algebra with Applications -- if taken at Purdue as a prerequisite for CS 515
• MA 514: Numerical Analysis -- when cross-listed with CS
• MA 518: Advanced Discrete Mathematics
• MA 520: Boundary Value Problems of Differential Equations
• MA 523: Introduction to Partial Differential Equations
• MA 525: Introduction to Complex Analysis
• MA 532: Elements of Stochastic Processes (aka STAT 532)
• MA 575: Linear Graph Theory
• MA 585: Mathematical Logic I
• MA 586: Mathematical Logic II
• MA 598: Elliptic Curves & Cryptography
• MA 598: Mathematical Aspects of Neural Networks
• MA 611: Methods of Applied Mathematics I
• MA 615: Numerical Methods For Partial Differential Equations I -- when cross-listed with CS

• ME 535: Product and Process Design -- when cross-listed with CS

• STAT 519: Introduction to Probability
• STAT 522: Sampling and Survey Techniques
• STAT 526 Advanced Statistical Methodology
• STAT 528: Introduction to Mathematical Statistics
• STAT 529: Bayesian Applied Decision Theory
• STAT 529K: Bayesian Applied Decision Theory
• STAT 532: Elements of Stochastic Processes (aka MA 532)
• STAT 546: Computational Statistics (was STAT 598D)
• STAT 598A: Introduction to Machine Learning
• STAT 598SK: Probabilistic Graphical Models
• STAT 695A.F11: Bayesian Statistical Modeling
• STAT 695C: Bayesian Statistics
• STAT 695T: Data Visualization
• STAT 695W: Bayesian Nonparametrics

Other courses, including courses at other institutions, may be approved on an individual basis. For more info.

The following courses are generally NOT approved by the graduate committee:

• Courses cross-listed as graduate and undergraduate courses, or offered for both graduate and undergraduate credit, unless primarily taken by graduate students

The following Purdue courses:

• CNIT 58100-CFM: Cyberforensics of Malware
• CPT 581F: Introduction to Computer Forensics (meets with 499F)
• ECE 608: Computational Models and Methods
• MA 511: Linear Algebra with Applications
• STAT 501: Experimental Statistics I
• STAT 502: Experimental Statistics II
• STAT 511: Statistical Methods
• STAT 512: Applied Regression Analysis
• STAT 545: Introduction to Computational Statistics
• STAT 695: D&R Big Data High Comp Cmplxty