🔹Week 01 – Python Fundamentals: DPP 01 – 04
- Built a strong foundation in Python syntax and core programming concepts
- Practiced variables, data types, input/output operations
- Worked extensively with conditional statements (if–else, nested conditions)
- Implemented loops (for, while) for repetitive logic and pattern-based problems
- Strengthened logical thinking and problem-solving skills
- Focused on writing clean, readable, and efficient Python code
🔹Week 02 – Data Structures: DPP 01 – 02
- Hands-on implementation of Lists, Tuples, Sets, and Dictionaries
- Performed CRUD operations on data structures
- Used built-in methods for searching, sorting, and aggregation
- Solved real-world problems using data structure manipulation
- Understood mutability vs immutability
🔹Week 03 – Functions & Advanced Logic: DPP 01 – 05
- Designed user-defined functions with parameters and return values
- Used default arguments and keyword arguments
- Applied lambda functions for concise logic
- Improved modular coding practices
- Solved multi-step problems using function decomposition
- Strengthened understanding of scope and reusability
🔹Week 04 – Error Handling & File Operations: DPP 01 – 04
- Implemented exception handling (try–except–else–finally)
- Learned how to handle runtime errors gracefully
- Worked with file handling (read, write, append modes)
- Processed external data using text files
- Built more robust and fault-tolerant Python programs
🔹Week 05 – Python for Data Analysis: DPP
- Introduced NumPy for numerical computations
- Used Pandas for data loading, cleaning, and manipulation
- Worked with Series and DataFrames
- Performed filtering, aggregation, and transformation operations
- Built confidence in handling real-world datasets
🔹Week 06 – Statistics & Hypothesis Testing: DPP 01 & Hypothesis Testing 02
- Implemented descriptive statistics using Python
- Understood mean, median, variance, standard deviation
- Performed hypothesis testing (Z-test, t-test concepts)
- Interpreted statistical results for data-driven decisions
- Applied statistics to real-world analytical scenarios
🔹Week 07 – Applied Problem Solving: DPP 01 – 02
- Solved end-to-end analytical Python problems
- Combined data structures, functions, and logic
- Focused on efficient code design
- Practiced real interview-level Python questions
- Strengthened confidence in writing production-ready code
🔧Tech Stack Used: Python NumPy Pandas Statistics Jupyter Notebook