Doctor of Pharmacy
The Pharm-D program at Superior develops experienced, employed registered pharmacists into effective researchers while providing them with numerous opportunities for community outreach, hands-on training, and research in the field. Through extensive involvement in advocacy projects and the dedication of a highly qualified faculty, Superior graduates have inspired the pharmacy practice and created positive change that is founded on a commitment to a rigorous and well-rounded education.
FSc (Pre-Medical) with 60% marks
- Course Duration: 5 Years
- Total Credit Hours: 201
- Semester: 10
Semester 1
| Course | Credit Hours |
|---|---|
| Artificial Intelligence | 3 |
| Semantic Web | 3 |
| Data Science | 3 |
| Big Data Analytics | 3 |
| Advanced Topics in Social Network Analysis | 3 |
| Advanced operating system | 3 |
| Advance Software Project Management | 3 |
| Theory of Computation | 3 |
| Total | 24 |
Semester 2
| Course | Credit Hours |
|---|---|
| Group Theory | 3 |
| ODEs And Computational Linear Algebra | 3 |
| Elective-I | 3 |
| Elective-I | 3 |
Semester 3
| Course | Credit Hours |
|---|---|
| Functional Analysis | 3 |
| Integral Equations | 3 |
| Elective-III | 3 |
| Elective-IV | 3 |
Semester 4
| Research Thesis | 3 |
Semester 5
| Course | Credit Hours |
|---|---|
| Geometry | 3 |
| Mathematical Techniques | 3 |
| Partial Differential Equations | 3 |
| Integral Equations | 3 |
| Cosmology | 3 |
| Relativistic Astrophysics | 3 |
| Classical Field Theory | 3 |
| Fluid Dynamics | 3 |
| Introduction To Bio Mathematics | 3 |
| Plasma Physics | 3 |
| Theory of Spline Function-I | 3 |
| Theory of Spline Function-II | 3 |
| Subdivision Schemes | 3 |
| Approximation Theory | 3 |
| Numerical Solutions Of PDEs | 3 |
| Minimal Surfaces | 3 |
| Rings and Modules | 3 |
| Operator Theory | 3 |
| Lie Algebras & Lie Groups | 3 |
| Field Extensions And Galois Theory | 3 |
| General Topology | 3 |
| Topological Groups | 3 |
| Linear Groups And Group Representations | 3 |
| Introduction To Fuzzy Systems | 3 |
| Fuzzy Graph Theory | 3 |
Semester 6
| Course | Credit Hours |
|---|---|
| Probability Distributions | 3 |
| Survey Sampling | 3 |
| Elective-I | 3 |
| Elective-I | 3 |
Semester 7
| Course | Credit Hours |
|---|---|
| Statistical Inference | 3 |
| Statistical Analysis by R | 3 |
| Elective-III | 3 |
| Elective-IV | 3 |
Semester 8
| Course | Credit Hours |
|---|---|
| Research Thesis 6 | 6 |
Semester 9
| Course | Credit Hours |
|---|---|
| Advanced Regression Analysis | 3 |
| Advanced Bayesian Inference | 3 |
| Advanced Categorical Data Analysis | 3 |
| Advanced Design of Experiments | 3 |
| Advanced Distribution Theory | 3 |
| Advanced Multivariate Analysis | 3 |
| Advanced Operations Research | 3 |
| Advanced Statistical Methods in Quality Control | 3 |
| Applied Smoothing Techniques | 3 |
| Applied Stochastic Models | 3 |
| Bayesian Inference | 3 |
| Causal Inference | 3 |
| Convergence in Probability | 3 |
| Decision Trees | 3 |
| Ecological Statistics | 3 |
| Environmental Statistics | 3 |
| Financial Stochastic Models | 3 |
| Generalized Linear Mixed Models | 3 |
| Generalized Linear Models | 3 |
| Inference in Stochastic Processes | 3 |
| Linear Models | 3 |
| Logical Reasoning and Research Method | 3 |
| Longitudinal Data Analysis | 3 |
| Meta Analysis | 3 |
| Multilevel Modeling | 3 |
| Optimization Techniques | 3 |
| Regression Models for Count Data | 3 |
| Spatial Data Analysis | 3 |
| Statistical Genetics | 3 |
| Statistical Methods for Clinical Trials | 3 |
| Structural Equation Models | 3 |
| Survival Data Analysis | 3 |
| Time Series Analysis and Forecasting | 3 |
Semester 10
| Course | Credit Hours |
|---|---|
| Advanced Topics in Social Network Analysis | 3 |
| Artificial Intelligence | 3 |
| Semantic Web | 3 |
| Data Science | 3 |
| Big Data Analytics | 3 |
| Requirement Engineering | 3 |
| Advance Software Project Management | 3 |
| Advance Software Quality Assurance | 3 |
| Advanced Software Architecture | 3 |
| Total | 27 |
To accommodate modern trends, Institute may reserve the right to change course requirements, fees, course classifications, course contents, class schedules, venues, faculty and the like, whenever it deems appropriate
