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Python Masterclass

Python Masterclass

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September 20, 2021

Course Description

Python is one of the most supported languages nowadays, it has a long list of open source libraries available for all the users. That’s a key factor that gives a strong push for Python at all, and in the data science, data analytics too. If you’re involved in the field, more than likely, you are acquainted with such libraries such as Pandas, Numpy, Matplotlib, Seaborn and other libraries that are intensively utilized in the data science community

Fundamental Knowledge of Python will be delivered on first session, thereafter you will learn the power of pandas, numpy, matplotlib and be an expert in the domain of Data Science. This Course does not demand any prior Programming Knowledge. We will analyze different kind of dataset from various Domain like, IPL, Ttanic, cloud Kitchen and many more.

Classes

Session-I: Monday, Thursday and Session-II: Wednesday, Saturday

From 6:30 pm

to 8:30 pm

Fees

INR. 8999/- Only

Duration

50 Hours

( 2 Classes Per Week )

Our Course Features
1
Entire course is 100% LIVE , Instructor Led program.
2
Life time access of the study Materials.
3
This Course is designed for all students who are inexperience in coding.
4
Powerful Libraries like, numpy, matplotlib, seaborn, pandas will be at your fingertips.
5
Hands-on experience are more prioritize rather than Theory elaboration.
6
More than 150 real world programming and 5+ Real Dataset will be used for coding and Analysis during entire sessions.
7
Industry related Project will be demonstrated at the end of learning, which will assist all Final year students to Build the Major Project (which is a part of their regular study) by their own.
Python Masterclass Course Content

Session-I (32 Hours)

Module 1: Introduction to Python
Fundamental of Python
  • Why Python and Use of Python in different domains such as Data science, Cyber security, Machine Learning, Various discipline of Engineering, Food Technology, Finance & Controlling, Management etc.
  • Introduction of ‘Python code writing’ Environment and different IDEs.
Python Setup
  • Installation of Anaconda in windows and LINUX.
  • Activating Jupyter Notebook and spider.
  • First Programming on Python (Hello World).
Operator and Variable
  • Hands-on illustration of Different type of Operator (Relational, Logical, Bitwise etc.), Different Data Type available in python and Type conversion.
  • Fundamental of Variable and its use in Program.
  • Display Input and Output- Accept input from User and Display on Console.
Programming, Assignment and MCQs.
Module 2: Boolean and Conditional Statement
  • Introduction of ‘If statement’.
  • if-else statement.
  • if-elif-else statement.
  • Difference of = and == operator.
  • Implementation of Nested conditional statement and Ternary operator.
  • Programming, Assignment and MCQs.
Module 3: Iteration
  • ‘while’ Loop- syntax and use in code.
  • Range() and ‘for’ Loop- syntax and use.
  • break, continue and pass statement.
  • Use of Nested Loop.
  • Programming and Assignments along with MCQs.
Module 4: String Operation
  • String Indexing and String Slicing.
  • Build-in function on String.
  • Split, Partition and Joining of String.
  • String Manipulation.
  • Programming, Assignments and MCQs
Module 5: Functions
  • Programming, Assignments and MCQs
  • User-Defined Function- How to pass Parameters and use of ‘return’ statement.
  • Functions of a Function- return, yield, Function call using variable, Pass function as arguments, Positional and keyword arguments.
  • Use of main()- Wrap up entire functions into a module and call only this module.
  • Recursion with multiple programming illustration.
  • lambda(), map(), reduce(), filter()
  • Programming, Assignment and MCQs.
Module 6: Mutable and Immutable Elements or Container
  • List- How to create List, How to Access List Elements, Deletion of List Elements, Implementation of copy() and deep copy().
  • How to create 1-D List, 2-D List and 3-D List in python.
  • Various Matrix operation, Search (Linear and Binary) operation in python.
  • Illustration of various Data structure using List in python (e.g.- Stack, Queue and Sort (Bubble).
  • Introduction of SETS and Functions on Sets.
  • Tuple and it’s Use.
  • Dictionary- Addition, Deletion and Updation of element in Dictionary.
  • Functions on Dictionary.
  • Programming, Assignment and MCQs.
Module 7: Module, Packages and namespace
  • Scope
  • LEGB Rule
Module 8: Object Oriented Python
  • Introduction of Class and Object and use of Private, Public and protected data members.
  • What are Constructor and Destructor and it’s use in coding.
  • vars() and dir().
  • User Input on Employee Management System.
  • Use of Operator Overloading, Function Overloading in python.
  • Programming, Assignment and MCQs.
Module 9: Code Re-Using Mechanism
  • Introduction of Containership and composition.
  • Calling super() method.
  • What is Inheritance and types of Inheritance such as- Simple, Multilevel, Multiple, Hybrid (With Hands-On implementation)
  • What is Diamond Problem and How to overcome this problem in python.
  • Abstract Class.
  • Programming, Assignment and MCQs.
Module 10: Input/output (I/O), File Handling and Exception Handling in Python
  • I/O functions- open(), read() and write().
  • Some Build-in Functions for file handling in python like-seek(), tell() etc.
  • Read json file and work on the file.
  • Handle with Directory Management System using python.
  • What are the different types of Errors and Exceptions in python.
  • How to Handling the exceptions?
  • Programming, Assignment and MCQs.
Module 11: Some Advanced Concept
  • How to Connect MySQL Database with python?
  • Insert data into MySQL table, Fetch data from MySQL table using python
  • Email with Python.
  • Iterator and Generator.
  • zip()
Module 12: Project
  • Introduction of PyQt5 Library in python and Develop an interactive Application using user interface and Deployment of MySQL database at the backend.
  • Introduction of “PyQt5 Designer” and Building graphical user interface on HRIS (Human Resource Management System). Feature of the application-
    • Using Python design- input text box, combo box, radio button, Menu Bar, Form and many more.
    • Elementary concept building on DBMS for insertion, Updation, Deletion creation Database/table and Fetching Data from DB.
    • Using python data insertion, deletion, modification, Fetching of data from MySQL database are incorporated.

Session-II (18 Hours)

Module 13: Introduction of Numpy Library
  • Introduction of Array in numpy, Creation of Array (1D,2D,3-D and Boolean) using Numpy.
  • Perform different Operation on Array and fundamentals of different Data Types for Array
  • Implementation of zeros(), ones(), arange() and empty().
  • Scaler and Vector Operation on Array in numpy.
  • Indexing of Array
    • Boolean Indexing.
    • Fancy Indexing
  • Slicing of Array
  • Conditional If-else statement on Numpy array.
  • Use of Loop on Numpy array.
  • Use of Conditional Logic and Loop on Array Operations
  • Universal Functions (ufunc) or Universal Methods in numpy array.
  • Familiar with available Build-in ufunctions such as – Arithmetic Uniary ufunc, Arithmetic Binary ufunc, Statistical ufunc, Boolean ufunc in numpy.
  • How to Handle File with Numpy.
Module 14: Numpy Project on Live Dataset (Collected from Live Questionnaires across India) to analyze the dataset.
Module 15: Data Visualization using python, an introduction to matplotlib and seaborn Library
  • Introducing matplotlib and seaborn libraries in python.
  • Using Matplotlib Library Draw Line Chart, Bar Chart, Pie Chart, Histogram, Scatter Plot, Box Plot on different Dataset.
  • Using Seaborn Lbrary implement distplot(), Seaborn Jointplot (), Seaborn Kernel Distribution, Seaborn Heatmap.
Module 16: Introduction of pandas Library
  • Introduction to the Different Pandas data structure like Series and Dataframe.
  • How to create Series, Access Series elements and different Operation on Series elements.
  • Let us Dataframe in pandas.
  • Import our first CSV file using import and read_csv () method and Inspection of datafile.
  • Key features of Jupyter Notebook for pandas library.
  • Data selection from CSV File-
    • All Rows all Columns
    • All Rows selected Columns.
  • Use of loc() and iloc() functions in pandas.
  • iloc()- for Row selection (Used for Rows Selection).
    • Selected Rows and selected Columns.
    • Selected Rows and Selected column using loc().
  • How to Index and Re-index a loaded CSV file.
Module 17: Condition Based Data Filtering in pandas Library
  • Hands-on Filtering Dataframe using one condition.
  • Hands-on Different Operator and Filtering Dataframe using Multiple conditions
  • Removing Elements from Dataframe
    • Removing Columns
    • Removing Complete Rows
  • How to Add New Columns in Dataset (Adding Scaler Values, Create a new column).
  • Creating a New Dataframe from scratch.
Module 18: Joining and Merging using pandas syntax
  • Use of append() and concat()
  • Implementation of Outer Join using merge()
  • How to inner Join Dataframe.
  • Left Join & Right Join of Dataframe.
  • Joining on Different column name.
  • Group by on Dataframe.
Module 19: Dataframe Manipulation (BONUS Module)
  • Statistical functions on DataFrame.
  • String Operations on pandas.
Module 20: Dataset Pre-processing using pandas (Useful for Readiness of dataset for Build a Model using Machine Learning Classifiers)
Section-A (Data Cleansing)
  • Anomalies need to be taken care to handle Data Cleansing, but not limited to-
    • Removing inconsistent data from the dataset.
    • Dealing Missing Values and Removing Missing Values from the dataset.
    • Dealing Duplicate Values and Removing Duplicated Values.
    • Deal with Outliner and how to handle dataset outliners.
Section-B (Feature Extraction)
Module 21: Project on Pandas

We will perform the Data Analysis on the IPL Auction Dataset or any other suitable Dataset using pandas library.

  • Why Python and Use of Python.
  • Introduction of Python code writing Environment and different IDEs.
  • Installation of Anaconda and Activating Jupyter Notebook and spider.
  • First Programming on Python (Hello World).
  • Different Operator,Variable and its use in Program.
 
  • Conditional Statement (If statement, if-else statement, if-elif-else statement).
  • Iteration- while Loop, for Loop, Nested Loop.
  • String Indexing, String indexing, Slicing.
  • Build-in function on String.
  • Split, Partition and Joining of String.
  • Built-in Functions, Statistical Function, User-Defined Function
  • Functions of a Function- return, yield, Function call using variable, Pass function as arguments, Positional and keyword arguments.
  • Use of main (), Recursion, lambda (), map ()
  • List- Creation of List, Access of List Elements, Deletion of List Elements,
  • Matrix operation
  • SETS, Functions on Sets.
  • Tuple
  • Dictionary- Addition, Deletion and Updation of Dictionary.
  • Module 6: Class and Object
  • Class and Object, Private, Public and protected data members.
  • Constructor and Destructor.
  • Class and Object, Private, Public and protected data members.
  • Constructor and Destructor.
  • Inheritance- Simple, Multilevel, Multiple, Hybrid.
 
  • DBMS Connectivity (MySQL connection string, Insert data into MySQL table, Fetch data from MySQL table using python).
  • Introduction of PyQt5 Designer and Building form on EmployeeManagement System.
  • Using Python design- input text box, combo box, radio button, Menu Bar, Form and many more.
  • Deployment of MySQL database at the backend
  • Elementary concept building on DBMS for insertion, Updation, Deletion creation Database/table and Fetching Data from DB.
  • Using python data insertion, deletion, modification, Fetching of data from MySQL database are incorporated.
 
  • Introduction of Array, Creation of Array (1D,2D,3-D and Boolean)
  • Operation on Array, Data Types for Array
  • zeros(), ones(), arange() and empty()
  • Scaler and Vector Operation on Array
  • Indexing of Array
  • Boolean IndexiNG
  • Fancy Indexing
  • Slicing of Array
  • If-else statement on Numpy array
  • Loop on Numpy array
 
  • Use of Conditional Logic and Loop on Array Operations
  • Universal Functions (ufunc) or Universal Methods in numpy array
  • Build-in ufunctions (Arithmetic Uniary ufunc, Arithmetic Binary ufunc, Statistical ufunc, Boolean ufunc)
  • File Handling with Numpy.
 
  • Matplotlib (Line Chart, Bar Chart, Pie Chart, Histogram, Scatter Plot, Box Plot
  • Seaborn distplot(), Seaborn Jointplot (), Seaborn Kernel Distribution,Seaborn Heatmap.
 
  • Pandas data structure: Series and Dataframe.
  • Series creation, Access Series elements, Operation on Series.
  • Fundamental of Dataframe.
  • Import first csv file using import and read_csv () method and Inspection of datafile.
  • Key features of Jupyter Notebook for pandas library.
  • Data selection- All rows all Columns, All Rows selected columns.
  • iloc()- for Row selection (selected Rows).
  • Selecting Rows and Specific column using loc()
  • Index and Re-index.
 
  • Filtering Dataframe using one condition.
  • Different Operator and Filtering Dataframe using Multiple conditions
  • Removing Elements from Dataframe (Removing Columns, Removing Complete Rows).
  • Adding New Columns in Dataset (Adding Scaler Values,Create a new column).
  • Creating New Dataframe.
 
  • Append() and concat()
  • Outer Join using merge()
  • inner Join
  • Left Join
  • Right Join
  • Joining on Different column name.
 
  • Sorting DataFrame, Rank Creation.
  • Statistical functions on DataFrame.
  • String Operations on pandas.
  • Group by on Dataframe.
 
  • Removing inconsistent data.
  • Dealing Missing Values and Removing Missing Values.
  • Dealing Duplicate Values and Removing Duplicated Values.
  • Deal with Outliner.
 
data analysis using python

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