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Python Programming – A Practical Approach

Python Programming – A Practical Approach

Python Programming – A Practical Approach

About the course

Professor Amey Karkare, a faculty of the Department of Computer Science and Engineering, at the Indian Institute of Technology, Kanpur has designed this course from the bottom up, assuming that the user doesn’t have any prior programming knowledge and experience. Dr. Karkare has worked with our development team to create the quality course content which can be easily followed by the all sections of learners ranging from an average learner to a proficient one. The most unique thing about this course is that, each concept has been covered from the basic level and is well supported with practical hands on practice. This course comprises of video lectures which can be viewed online and offline as per the convenience of the user. It also includes hands on practice exercises, which makes it all together a complete package.

This course has been designed keeping in mind, the needs of learners, who wish to learn Python and build desktop and web based applications using Python. In this course, the user will be able to learn to write programs in Python using the loops, conditional statements etc. The user will also understand about the other building blocks of programs such as functions or methods. In addition to this, the user will learn about exceptions, classes, file handling and operations, and many other important topics related to Python programming. In addition to this, the user will be able to learn some advanced programming concepts which are object oriented programming concepts including inheritance. The other topics include introduction to iterators, recursion, concept of searching, sorting, and the Tower of Hanoi. The users taking this course will be benefited because they'll deal with the most fundamental as well as some advanced and complex topics in Python programming which will eventually enhance their thinking and problem solving skills. Python is the most useful language for many application domains. This language has a wide application area which includes desktop GUIs, and web development. It is also used in scientific and numeric computing. It is one of the best language for teaching programing at the beginner and advanced levels. So, this is an evergreen language for software programmers.



Advantages of learning this course
Target Audience
Why learn Python?
Course Features
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Other Information


*CGPA to percentage conversion formula:

Equivalent Percentage = CGPA obtained X 9.5 X (10/CGPA Scale)
Example: If CGPA obtained is 8.00 on the scale of 10, then Equivalent
percentage will be 8.00 X 9.5 X (10/10) = 76%,
or If CGPA is 3.7 out of 4, then Equivalent percentage will be 3.7 X 9.5 X (10/4) = 87.88%


We urge you to provide correct information to your best knowledge. Certificates will be withheld if found that you have misrepresented any data / information.


  1. Introduction

  2. The Programming Cycle for Python

  3. Interacting with Python Programs

  4. Elements of Python

  5. Type Conversion

  6. Expressions

  7. Assignment Statement

  8. Arithmetic Operators

  9. Operator Precedence

  10. Boolean Expression

  11. Conditionals

  12. Conditionals (Continued)

  13. Expression Evaluation

  14. Float Representation

  15. Loops

  16. Loops (Continued)

  17. For Loop

  18. Nested Loops

  19. Break and Continue

  20. Function

  21. Parts of A Function

  22. Execution of A Function

  23. Keyword and Default Arguments

  24. Scope Rules

  25. Strings

  26. Indexing and Slicing of Strings

  27. More Slicing

  28. Tuples

  29. Unpacking Sequences

  30. Lists

  31. Mutable Sequences

  32. List Comprehension

  33. Sets

  34. Dictionaries

  35. Higher Order Functions

  36. Sieve of Eratosthenes

  37. File I/O

  38. Exceptions

  39. Assertions

  40. Modules

  41. Importing Modules

  42. Abstract Data Types

  43. Classes

  44. Special Methods

  45. Class Example

  46. Inheritance

  47. Inheritance and OOP

  48. Iterators

  49. Recursion

  50. Simple Search

  51. Estimating Search Time

  52. Binary Search

  53. Estimating Binary Search Time

  54. Recursive Fibonacci

  55. Tower Of Hanoi

  56. Sorting

  57. Selection Sort

  58. Merge List

  59. Merge Sort

  60. Higher Order Sort

  61. Python Programming - Final Quiz