BP101TSemester 12 creditsTheoryKEY SUBJECT
Basics of Python Programming for Pharmaceutical Sciences
Complete unit-wise syllabus for BP101T as per the PCI B.Pharm NEP 2020 curriculum (Semester 1 — Python + Core Sciences Foundation).
URL:
https://pharmacode.vercel.app/syllabus/semester-1/bp101t-basics-of-python-programming-for-pharmaceutical-sciences/Unit-wise Syllabus
5 Units1
Introduction to Python Programming6 Hours- Installing Python and an IDE (Jupyter Notebook, PyCharm, VS Code); advantages of IDEs over text editors
- Python variables and data types (integers, floats, strings, booleans); type casting; basic operators (arithmetic, comparison, logical); input/output operations
- Basic string operations and manipulation techniques
- Introduction to standard libraries and third-party libraries; installing and uninstalling libraries
2
Control Structures & Functions6 Hours- Conditional statements: if, if-else, if-elif-else, nested conditions
- Loops: for loop, while loop; break and continue statements
- Defining and calling functions; passing arguments and returning values
- Writing modular programs for pharmaceutical applications — dosage calculation and BMI calculation
3
Data Structures & File Handling6 Hours- Lists, tuples, and dictionaries; indexing and slicing; basic operations on lists and dictionaries; string manipulation techniques
- Introduction to NumPy arrays; basic operations using NumPy (array creation, arithmetic operations)
- Reading and writing CSV files; understanding structured healthcare datasets
- Importing small pharmaceutical datasets and performing basic data access and manipulation tasks
4
Data Handling with Pandas6 Hours- Introduction to Pandas library; Pandas Series and DataFrame structures
- Reading CSV and Excel files — PK study datasets and ADR reports
- Inspecting datasets using head(), tail(), info(), describe(); data cleaning and handling missing values
- Filtering and selecting data based on conditions; grouping data and performing aggregation functions
5
Data Visualization with Matplotlib6 Hours- Introduction to Matplotlib; creating line plots, histograms, scatter plots, and box plots
- Labeling axes, titles, and legends
- Visualizing pharmaceutical datasets — concentration-time curves for oral and IV administration, ADR reporting rates, dissolution profiles
- Scientific interpretation of plots
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What's coming next on this page
- Reference textbooks and recommended reading list
- Previous year question papers (PYQ)
- Topic-wise short notes and revision summaries
- Suggested external resources and video tutorials
Other subjects in Semester 1
BP102TGeneral PharmacyBP103THealthcare Psychology and Communication SkillsBP104THuman Anatomy, Physiology and Pathophysiology IBP105TIntroduction to PharmacognosyBP106TPharmaceutical Inorganic and Analytical ChemistryBP107P–BP111PPracticals — General Pharmacy, Healthcare Psychology, Anatomy, Pharmacognosy, Inorganic Chemistry