Course

Syllabus

Introduction to Python, variables, data types, objects and object oriented programming, classes, inheritance, lists and indices, loops, conditional statements, functions, script files, loading and using modules

Numpy arrays , Data analysis using pandas, plotting using Matplotlib, programming with spatial data

Skills acquired : Basics of python programming

Learning Objectives 

LO1: Understand and apply core Python programming concepts

LO2: Develop foundational skills in data analysis and visualization

Course Outcomes 

CO1: Develop problem-solving skills. Modularize a complex task and formulate a program structure with defined subtasks

CO2: Apply fundamental programming constructs such as logical flow control, loops, functions

CO3: Apply python specific data structures and concepts of object-oriented programming

CO4: Create programs with python modules, packages and libraries

1. Downey, A. (2015). Think Python. ” O’Reilly Media, Inc.”.
2. McKinney, W. (2012). Python for data analysis: Data wrangling with Pandas, NumPy, and IPython. O’Reilly Media, Inc.
3. https://www.earthdatascience.org/courses/intro-to-earth-data-science/
4. Lutz, M. (2013). Learning python: Powerful object-oriented programming. ” O’Reilly Media.