Python

The most sought-after general-purpose high-level programming language that we use today is Python. In 1991 Guido van Rossum initially designed this programming language and later the Python Software foundation developed it. The emphasis was mainly on the code readability, and one can express the code in fewer lines.

You can easily work and integrate the systems more efficiently. In our discussions we will include both Python 2 and Python 3 but more emphasis will be given on Python 3 as it is the latest one and most commonly used.

But before moving on to the course we need to know why we should learn Python.

  1. It is the language which is highly in demand.
  2. It is easy to learn and is user friendly compared to other programming languages.
  3. There are a huge number of libraries in Python which makes it shorter and easier to code.
  4. It is the language used in almost all of the tech giants like Amazon, Microsoft, Google, Facebook, Instagram, etc.
  5. Python is the one used for Machine learning, Scientific Computing, Web scraping, Image processing, etc.
  6. At last in this world of Data Science Python is the one which is in demand and its knowledge can provide us with a very good career in Data Science.

Basics

  1. Python Language Introduction
  2. Python 3 Basics
  3. Python the New Generation Language
  4. Important Difference Between Python 2.x and Python 3.x with Examples
  5. Important Keywords in Python - Set 1
  6. Important Keywords in Python - Set 2
  7. Namespaces and Scope in Python
  8. Statement, Indentation and Comment in Python
  9. Structuring Python Programs
  10. How to Check if a String is Valid Keyword in Python
  11. Assigning Values to Variables in Python and Other Languages
  12. Printing Without Newline in Python
  13. Making decisions in Python (if, if else, nested if, if-elif)
  14. Basic Calculator Program using Python
  15. Python Language Advantages and Applications

INPUT/OUTPUT

  1. Taking Input in python
  2. Taking Input from Console in Python
  3. Taking Multiple Inputs from Users in Python
  4. Python Input Methods for Competitive Programming
  5. Vulnerability in input() Function - Python 2.x
  6. Python Output Using print() Function
  7. Python End Parameter in print()
  8. Python Separate Parameter in print()
  9. Python Output Formatting

DATA TYPES

  1. Introduction to Data Types
  2. Python Strings
  3. Python Lists
  4. Python Tuples
  5. Python Sets
  6. Python Dictionary
  7. Arrays in Python - Set 1
  8. Arrays in Python - Set 2

VARIABLES

  1. Python Variables, Expressions and Functions
  2. Maximum possible value of an integer in Python
  3. Global and Local variables
  4. Packing and Unpacking Arguments in Python
  5. End parameter
  6. Type Conversion in Python
  7. Byte Object vs String
  8. Printing Single and Multiple Variables
  9. Swapping Two variables in a Single Line
  10. Private Variables in Python
  11. __name__(Special Variable)

OPERATORS

  1. Basic Operators in Python
  2. Logical and Bitwise Not Operator on Boolean
  3. Ternary Operator in Python
  4. Division Operator in Python
  5. Operator Overloading in Python
  6. Any and All in Python
  7. Inplace vs Standard Operator in Python
  8. Operator Functions in Python - Set 1
  9. Operator Functions in Python - Set 2
  10. Important Inplace Operators
  11. Some Important Inplace Operators
  12. Logic Gates
  13. Some Important Points in Python
  14. Membership and Identity Operators

CONTROL fLOWS

  1. Loops in Python
  2. Techniques for Looping
  3. Difference Between range and xrange
  4. Printing Pattern in Python
  5. Chaining of Comparison Operators
  6. else Condition statement with for Looping
  7. Switch case in Python
  8. Coroutine
  9. Use of iterations in Python
  10. Python iterators
  11. Useful iterator Functions in Python - 1
  12. Useful iterator Functions in Python - 2
  13. Converting Object into an Iterator
  14. Difference in iterator and iterable in Python
  15. Generators in Python
  16. Generator Expressions

FUNCTIONS

  1. Functions in Python
  2. Class Method vs Static Method
  3. Writing an Empty Function Using Pass Statement
  4. Cases Where we use Yield instead of Return
  5. Returning Multiple Values
  6. Partial Functions
  7. First Class Functions
  8. Precision Handling
  9. args and kwargs
  10. Closures in Python
  11. Function Decorators
  12. Decorators with Parameters
  13. Memoization using Decorators
  14. Help Function
  15. Import Function
  16. Range Function does not Return iterators
  17. Decorators
  18. Using bit Function on int

OBJECT ORIENTED CONCEPTS

  1. Intermediate Level Topics in Python
  2. Object Oriented Programming Set 1
  3. Object Oriented Programming Set 2
  4. Object Oriented Programming Set 3
  5. Polymorphism
  6. Class or Static Variable
  7. Changing Class Methods
  8. Constructors in Python
  9. Destructors in Python
  10. str vs repr
  11. Metaprogramming and Metaclasses
  12. Class and Instance Attributes
  13. Reflection in Python
  14. Barrier Objects
  15. Timer Objects
  16. Garbage Collectors

EXCEPTION HANDLING

  1. Python Set 5 Exception Handling
  2. User Defined Exceptions
  3. Built-in Exceptions
  4. Defining Clean Up Actions
  5. NZEC Errors
  6. 404 Error Handling in Flask
  7. try and Except

MODULES IN PYTHON

  1. Modules in Python
  2. Mathematical Functions in Python Set- 1
  3. Mathematical Functions in Python Set- 2
  4. Mathematical Functions in Python Set- 3
  5. Mathematical Functions in Python Set- 4
  6. Calendar Module
  7. Calendar Functions Set- 1
  8. Calendar Functions Set- 2
  9. Complex Numbers Set- 1
  10. Complex Numbers Set- 2
  11. Complex Numbers Set- 3
  12. Time Functions Set- 1
  13. Time Functions Set- 2
  14. Random Numbers
  15. struct Module
  16. Urllib Module
  17. pprint
  18. eval Function
  19. Fraction module
  20. Mouse and Keyboard Automation
  21. Generating QR Code using pyqrcode

WORKING WITH EXCEL

  1. Using Python to Read Excel File
  2. Using Python to Write in an Excel Sheet
  3. Using openpyxl Module to Read Excel Files
  4. Writing to an Excel file using openpyxl Module
  5. Adjusting the Rows and Columns of Excel
  6. Plotting Charts in Excel using openpyxl Module - Set 1
  7. Plotting Charts in Excel using openpyxl Module - Set 2
  8. Plotting Charts in Excel using openpyxl Module - Set 3
  9. Arithmetic Operations using openpyxlin Excel
  10. Trigonometric Operations using openpyxl in Excel
  11. Plotting Pie Charts in Excel using XlsxWriter Module
  12. Plotting Area Charts in Excel using XlsxWriter Module
  13. Plotting Radar Charts in Excel using XlsxWriter Module
  14. Plotting Bar Charts in Excel using XlsxWriter Module
  15. Plotting Doughnut Charts in Excel using XlsxWriter Module

LIBRARIES AND FUNCTIONS

  1. Timeit Library in Python
  2. NumPy Library in Python - Set 1
  3. NumPy Library in Python - Set 2
  4. Get and Post Request in Python
  5. Regular Expressions in Python - Set 1
  6. Regular Expressions in Python - Set 2
  7. OS Module in Python
  8. Deep and Shallow Copy in Python
  9. Import Module
  10. Reloading Modules in Python
  11. Deque in Python
  12. Namedtuple in Python
  13. Heap Queue
  14. enum in Python
  15. Theano in Python
  16. Statistical Functions in Python - Set 1
  17. Statistical Functions in Python - Set 2
  18. Bisect Algorithm Functions
  19. Python Math Library Gamma Functions
  20. Python Math Library expm1 Function
  21. Decimal Functions in Python - Set 1
  22. Decimal Functions in Python - Set 2
  23. NetworkX
  24. getpass() and getuser() in Python
  25. Reading and Generating QR Codes using QR tools
  26. fnmatch
  27. Matplotlib
  28. Unicodedat
  29. Textwrap
  30. Secret Module
  31. Pickle - Python Object Serialization
  32. Python pickling with Example
  33. Copyreg - Register Pickle Support Functions
  34. Python GUI Tkinter

DATA ANALYSIS

  1. Data Visualization using Bookeh Mode
  2. Exploratory Data Analysis
  3. Data Visualization Using Different Charts
  4. Data Analysis and Visualization - Set 1
  5. Data Analysis and Visualization - Set 2
  6. Math operators for Data Analysis
  7. Jupyter Notebook

NumPy

  1. Python NumPy
  2. NumPy ndarray
  3. NumPy Array Creation
  4. NumPy Data Type Objects
  5. Indexing in NumPy
  6. Iterating Over Array in NumPy
  7. Binary Operations in NumPy
  8. NumPy Mathematical Functions
  9. String Operators in NumPy
  10. Linear Algebra in NumPy
  11. Sorting, Searching and Counting in NumPy
  12. Multiplication of Two Matrices Using Single Line in NumPy
  13. Printing Check board Pattern of n x n Using NumPy

PANDAS

  1. Pandas Dataframe in Python
  2. Creation of Pandas DataFrame
  3. Rows and Columns in Pandas DataFrame
  4. Indexing and Selecting Data Using Pandas
  5. Boolean indexing in pandas
  6. Conversion Functions in pandas
  7. Iterating over rows and Columns in Pandas
  8. Working with Missing Data in pandas
  9. Working with Text Data in Pandas
  10. Working with Date and Time in Pandas
  11. Merging, Joining and Concatenation in Pandas
  12. Pandas Series
  13. Creation of Pandas Series
  14. Accessing Elements of Pandas Series
  15. Data Analysis Using Pandas
  16. Reading a csv File using Pandas
  17. Merge, Join and concatenate using Pandas
  18. Deleting Rows/Columns from DataFrame using Pandas
  19. Data Comparison and Selection in Pandas

MACHINE LEARNING WITH PYTHON

  1. Linear Regression
  2. Linear Regression Using Tensorflow
  3. Understanding Logistic Regression
  4. K means Clustering
  5. Analyzing Test Data using K means Clustering
  6. Multidimensional Data Analysis
  7. Image Classification using Keras
  8. Implementation of Movie Recommender System
  9. Decision Tree Regression using sklearn
  10. Principal Component Analysis
  11. Implementation of Polynomial Regression
  12. Boston Housing Kaggle Challenge with Linear Regression
  13. Applying Convolution Neural Network on mnist Dataset
  14. Saving a Machine Learning Model
  15. NLP Analysis of Restaurant Review
  16. Classification of Data Using Support Vector Machines
  17. Principal Component Analysis in Machine Learning
  18. Implementation of K nearest neighbour
  19. Learning Model building in Scikit
  20. Tokenizing Text in NLTK in Python
  21. Removal of Stop Words using NLTK
  22. Lemmatization With NLTK
  23. Stemming Words With NLTK
  24. Getting Synonyms and Antonyms from NLTK Wordnet
  25. Parts of Speech Tagging with Stop Words using NLTK
  26. Implementation of Artificial Neural Network Training Process
  27. Conversion of Text to Speech
  28. seq2seq Model in Machine Learning
  29. Classification of Data Using Support Vector Machines 2
  30. Introduction to Convolutions Using Python
  31. Single Neuron Neural Network
  32. Creation of A Simple Machine Learning Model
  33. How and Where to Apply Feature Scaling?
  34. Identifying Handwritten Digits Using Logistic Regression in PyTorch

MISCELLANEOUS

  1. Ten Essential Python Tips and Tricks
  2. Amazing Hacks in Python
  3. Python input Method for Competitive Programming
  4. Optimization Tips in Python Code
  5. Process to Input Multiple Values from Users in One Line in Python
  6. Command Line and Variable Argument in Python
  7. Interesting Facts about Python
  8. Importing Star in Python
  9. Python is Best Suited for Competitive Coding
  10. Python Tricks for Competitive Coding
  11. Python for Data Science
  12. Calling a C Function in Python
  13. Selenium Python Tricks
  14. Text Analysis in Python 3
  15. Context Manager in Python
  16. Code Introspection in Python
  17. Permutation and Combination in Python
  18. Command Line Interface Programming
  19. JSON Format in Python
  20. Quine in Python
  21. Cristian’s Algorithm
  22. Address Calculation Sort using Hashing
  23. Introduction to Web Development using Flask
  24. Using for loop in Flask
  25. Finding the First Non- Repeating Character from a Stream of Characters
  26. Finding Mean, Median and Mode without Libraries
  27. Short Circuiting Techniques in Python
  28. Formatted Text in Linux
  29. Understanding Code Re-use and Modularity in Python 3
  30. Diffrence between Various Implements in Python
  31. Program for Calculating the Round Trip Time
  32. Program for Generating One Time Password
  33. Langton’s Ants
  34. Barnsley Fern in Python
  35. Koch Curve or Koch Snowflake
  36. Coding Style Guide in python
  37. Scope Resolution in Python
  38. Writing Own len() Function
  39. Using CX Freeze in Python
  40. Program to Print Own Name as Output

APPLICATIONS & PROJECTS

  1. Program for Crawling a Web Page and Getting the most Frequent Words
  2. Creation of a Proxy Web Server Set - 1
  3. Creation of a Proxy Web Server Set - 2
  4. Facebook Login using Python
  5. Sending Message to Facebook Friends in python
  6. Creation of C/C++ Formatting Tool Using Clang Tool
  7. Finding Live Running Status and PNR of a Train using Railway API
  8. Extraction of Tweets using Tweepy
  9. Finding Weather of any City using Openweather API
  10. Flask- Creation of First Simple Application
  11. Website Blocker in Python
  12. Fetching Text from the Infobox of Wikipedia in python
  13. Page Rank Algorithm and its Implementation
  14. Conversion of Text to Speech using Win32com
  15. Designing a Keylogger in Python