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Program Overview

What you'll learn


Python is an interpreted, high-level, general-purpose programming language.


Pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series.


NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

Jupyter Notebook

Project Jupyter is a nonprofit organization created to "develop open-source software, open-standards, and services for interactive computing across dozens of programming languages"

Scikit learn

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy


Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects

Introduction to Python
  • What is Python and brief history
  • Discussion on Python 2 and 3
  • Unique features of Python
  • Discussion on various IDE’s
  • Demonstration of practical use cases
  • Python use cases using data analysis
Setting up and installations
  • Installing python
  • Setting up Python environment for development
  • Installation of Jupyter Notebook
  • How to access our course material
  • Write your first program in python
Python object and data structures operations
  • Introduction to Python objects
  • Number objects and operations
  • Variable assignment and keywords
  • String objects and operations
  • Print formatting with strings
Python statements
  • Introduction to Python statements
  • If, else-if and else statements
  • Comparison operators
  • Chained comparison operators
  • What are loops?
  • For loops
  • While loops
File and exception handling
  • Process files using python
  • Read/write and append file object
  • File functions
  • File pointer and operations
  • Introduction to error handling
  • Try, except and finally
Object oriented programming
  • Implement object oriented with Python
  • Creating classes and objects
  • Creating class attributes
  • Installing apache tomcat with puppet
  • Creating methods in a class
  • Inheritance
  • Polymorphism
Data Analysis with Python
  • Introduction to data analysis
  • Why Data analysis?
  • Data analysis and Artificial Intelligence Bridge
  • Introduction to Data Analysis libraries
  • Data analysis introduction
Data analysis using Numpy
  • Introduction to Numpy arrays
  • Creating and applying functions
  • Numpy Indexing and selection
  • Numpy Operations
  • Exercise and assignment challenge
Pandas and advanced analysis
  • Panda’s series
  • Introduction to Data Frames
  • Missing data
  • Group by
  • Merging, joining and concatenating
  • Operations
  • Data Input and Output
Data visualization with Python
  • Plotting using Mat plot lib
  • Sea born visualization
  • Pandas built-in data visualization
  • Project


Executive Program in Data Science with Python Technology Certified By Microsoft


Certification by Microsoft


Certification by Vepsun

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Data Science with Python


Inclusive of all Taxes

  • arrow 4 Session/ classes
  • arrow Online - live Classes

Data Science with Python


Inclusive of all Taxes

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  • arrow Single Certification
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Data Science with Python


Inclusive of all Taxes

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  • arrow Dual Certification
  • arrow Online - live Classes
  • arrow No Cost EMI Available

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Frequently Asked Questions

Python is capable of scripting, but in general sense, it is considered as a general-purpose programming language..
An interpreted language is any programming language which is not in machine level code before runtime. Therefore, Python is an interpreted language.
A namespace is a naming system used to make sure that names are unique to avoid naming conflicts.
Indentation is necessary for Python. It specifies a block of code. All code within loops, classes, functions, etc is specified within an indented block. It is usually done using four space characters. If your code is not indented necessarily, it will not execute accurately and will throw errors as well.
Pickle module accepts any Python object and converts it into a string representation and dumps it into a file by using dump function, this process is called pickling. While the process of retrieving original Python objects from the stored string representation is called unpickling.
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