42 Hours of Online Live Instructor-led Classes.
Weekend class: 14 sessions of 3 hours each and
Weekday class : 21 sessions of 2 hours each.

Python Training for Data Science

Python course helps you gain expertise in Quantitative Analysis, data mining, and the presentation of data to see beyond the numbers by transforming your career into Data Scientist role. You will use libraries like Pandas, Numpy, Matplotlib, Scikit and master the concepts like Python Machine Learning Algorithms such as Regression, Clustering, Decision Trees, Random Forest, Naïve Bayes and Q-Learning and Time Series. Throughout the Course, you’ll be solving real-life case studies on Media, Healthcare, Social Media, Aviation, HR and so on. 

Course Curriculum

Python Intro

Learning Objectives: You will get a brief idea of what Python is and touch on the basics.
  • Overview of Python
  • The Companies using Python
  • Different Applications where Python is used
  • Discuss Python Scripts on UNIX/Windows
  • Values, Types, Variables
  • Operands and Expressions
  • Conditional Statements
  • Loops
  • Command Line Arguments
  • Writing to the screen
Hands On/Demo:
  • Creating “Hello World” code
  • Variables
  • Demonstrating Conditional Statements
  • Demonstrating Loops
  • Fundamentals of Python programming

Learning Objectives: Learn different types of sequence structures, related operations and their usage. Also learn diverse ways of opening, reading, and writing to files.
  • Python files I/O Functions
  • Numbers
  • Strings and related operations
  • Tuples and related operations
  • Lists and related operations
  • Dictionaries and related operations
  • Sets and related operations
Hands On/Demo:
  • Tuple – properties, related operations, compared with a list
  • List – properties, related operations
  • Dictionary – properties, related operations
  • Set – properties, related operations


  • File Operations using Python
  • Working with data types of Python

Learning Objectives: In this Module, you will learn how to create generic python scripts, how to address errors/exceptions in code and finally how to extract/filter content using regex.
  • Functions
  • Function Parameters
  • Global Variables
  • Variable Scope and Returning Values
  • Lambda Functions
  • Object-Oriented Concepts
  • Standard Libraries
  • Modules Used in Python
  • The Import Statements
  • Module Search Path
  • Package Installation Ways
  • Errors and Exception Handling
  • Handling Multiple Exceptions
Hands On/Demo:
  • Functions – Syntax, Arguments, Keyword Arguments, Return Values
  • Lambda – Features, Syntax, Options, Compared with the Functions
  • Sorting – Sequences, Dictionaries, Limitations of Sorting
  • Errors and Exceptions – Types of Issues, Remediation
  • Packages and Module – Modules, Import Options, sys Path


  • Error and Exception management in Python
  • Working with functions in Python

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