Python is a widely used high-level, general-purpose, interpreted, dynamic programming language.Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than possible in languages such as C++ or Java.The language provides constructs intended to enable writing clear programs on both a small and large scale.

Duration : 30 hrs

Fees : 23,000/-

Key Takeaways from this course:

In class Assignments

Practical training on tool

Case Studies

Master Classes

Alumni Support

Course Modules:


Candidates are given with initial introduction to the programming languages. Practical experience of installation and preparing the environment to start with python

  • Why Python
  • Python comparison with other languages
  • Installation and setup

Python Basics

A clear understanding of architecture and functionality of scripting language. Kick start of python language starting with basic concepts, handling data structures and OOPS concepts. End of this module candidate will gain experience in python.

  • Architecture
  • First Program
  • Basic Operations , Decision Making
  • Loops
  • Handling Data Structures in python (Lists , Tuples , Dict)
  • Functions and Exception Handling
  • Python classes / Objects
  • Regular Expressions

Handling Data in Python

This is the important module where it covers handling data from different data sources. All possible data sources are covered so that it makes easier for a person to start working with data and will help in basic I/O operations.

  • Reading Data from text files , csv files.
  • Writing data into csv files , text files
  • Handling json data
  • Data Scraping (HTML , XML)
  • Interacting with Data Bases (Mongo DB, SQL)

Data Wrangling

This module covers data engineering part. Important job of a data analyst is to prepare data and import features out of it. Summarizing data with initial basic descriptive analysis other important part which is covered in this module.

  • Numpy Basics
  • Getting started in Pandas
    • Intro to Pandas
    • Summerizing& Computing Descriptive statistics
  • Handling missing data
  • Removing duplicates
  • Replacing Values
  • String manipulation

Plotting and Visualization

Pictures talk more than words. This module covers bringing up the descriptive analysis in the form of graphs. All important graphs which are mostly used in the industry are covered in this module

  • Introduction to matplotlib
    • Colors, line styles , subplots
    • Labels , legends
    • Saving plots to files
  • Plotting function in Pandas
    • Line plots , Bar plots
    • Histograms , Scatter plots

Business Use cases

Practical and real world experience is preferred when it comes to programming languages. One use case which covers all the concepts which are learned is given which helps candidates in building their profile

Advanced Analytics in Python

Duration : 30 hrs

Fees : 23,000/-

Data Analysis

This data analysis course is an introduction to machine learning and algorithms. This will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics.

  • Introduction to Scikit-Learn
  • Supervised Models
    • Naïve Bayes
    • Logistic Regression
    • Neural Networks
    • SVM
    • Decision Trees
  • Clustering

Text Mining in Python

Text mining is a method for drawing out content based on meaning and context from text. It is a method for gathering structured information from unstructured text. This module covers different algorithms and tools that can be used to bring meaning from the text.

  • Introduction to Text Mining , Natural Language Processing
  • Regular Expressions
  • Sentence segmentation
  • Base form of a word (Lemma , Stem)
  • Stop words
  • Dependency Parsing
  • Topic Modeling
  • Word Cloud
  • tf-Idf

Business Use cases

One use case which covers all the concepts which are learned is given which helps candidates in building their profile