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                   Python is an Open-source and Object-Oriented Programming Language It is a simple and easy to read programming language and doesn’t require any license to utilize it.  New developments in Python Language happens very frequently as it is backed by various Communities which are diverse in programming skills. Python Language is extensively used in Web Development, Gaming, Scientific Applications, GUI Development, Web Scraping, Artificial Intelligence (Data Science), Machine Learning and Deep Learning etc.

Course Content:

Core Python:

1. Introduction to Languages

2. Introduction to Python

3. Python Software

4. Python Language Fundamentals

5. Different Modes of Python

6. Python Variable

7. Operators

8. Input and Output Operator

9. Control Statements

10. Data Structures or Collections

11. Strings

12. List Collection

13. Tuple Collection

14. Set Collection

15. Dictionary Collection

16. Functions

Advanced Python:

1. Python Modules

2. Packages – Pip


4. Method Overloading

5. Construct Overloading

6. Operator Overloading Exception                  Handling and Types of Errors

7. Regular Expression

8. File and Directory Handling

9. Python Logging

10. Date and Time Module

11. Os Module

12. Multi Threading and Multi                            Processing

13. Garbage Collection

14. Python Data Base                        Communication

15. Python- Network                        Programming

16. Tkinter and Turtle

15. Data Analytics Modules

16. Django

17. Pandas

18. Pandas Introduction

19. Pandas Environment

20. Pandas – Introduction to Data                         Structures

21. Series

22 . Data Frames

23. Panel

24. Basic Functionality

25. Descriptive Statistics

26. Function Application

27. Re indexing

28. Iteration

29. Sorting

30. Working with Text Data

31. Options and Customization

32. Indexing and Selecting Data

33. Statistical Function

34. Window Function

35.  Aggregation

36. Missing Data

37. Group by

38. Merging / Joining

39. Concatenation

40. Date Functionality

41. Time Delta

42. Categorical Data

43. Visualization

44. IO Tools

45. Sparse Data

46. Caveats and Gotchas

47. Comparison with SQL



Environment  Setup

ND Array Object

Data Types

Array Attribute

Array Creation Routines

Array from Existing Data

Arrya from Numerical Ranges

Indexing and Slicing

Advanced Indexing


Iterating over Array

Array Manipulation

Binary Operators

String Function

Mathematical Function

Arthimetic Operator

Statistical Function

Sort, Search and Counting Function

Byte Swapping

Copies and Views

Matrix Library

Linear Algebra

Matplot Lib

Histogram using Matplot Lib

I/o with Numpy