Python for Data Analytics


About This Course

  • 40 hours Live Sessions
  • 25+ hours of offline
  • Assignments for continuous learning after the course completion
  • 30+ hours of Hands-on with Python
  • Includes 3 Live Projects

Welcome to the course “Python for Data Analytics”. It is designed to equip you with the ability to apply knowledge and life skills of Python as a programming language and to understand how this is important in Data Analytics and Data Science space. Python is one of the most-used programming languages adopted by developers. You learn the key aspects of Python from scratch even if you don’t have any background in python programming.

  • Analyse and translate business requirements of software into multiple functions
  • Write programmes and codes that are aligned with business requirements
  • Draft and design overall coding frameworks as a guide for organising codes
  • Select appropriate programming languages for business use cases
  • Code solutions using required programming languages
  • Assess written codes to identify errors and gaps to be addressed
  • Test and debug codes to ensure workability
  • Incorporate improvements and make corrections to programmers and codes to achieve desired outcomes
  • Document programming and coding updates and changes for business and technical professionals

We are confident that at the end of the workshop, you should be able to:

  • Understand on Fundamentals of Python and apply its installation knowledge
  • Understand data types and string manipulation for python along with to apply
    knowledge on different Variable
  • Understand logic and control statements and evaluate their outcomes
  • Apply programming techniques with Object Oriented Concepts with design and documentation
  • Understand Dictionary, Array, List and other User defined data types along with their applications
  • Understand File handling techniques and Data Extraction with database connectivity
  • Apply knowledge of Exception handling techniques and evaluate efficiency of program codes
  • Learning Numpy, Pandas and Python Module
  • Learning Data Visualization using Python
  • Working with Financial data use case. Live presentation of Financial Case study solution preparation.
Module 1: Introduction to Python & Installation
  1. 40 hours Live Sessions
  2. 25+ hours of offline
  3. Assignments for continuous learning after the course completion
  4. 30+ hours of Hands-on with Python
  5. Includes 3 Live Projects
Module 2: Python Data Types & Variables
Python Data Types & Variables
  • Introduction to Jupyter Notebook
  • Setting up the working directory in Jupyter Notebook
  • Variable
  • Datatypes
  • TypeCasting
  • Print Statement
  • Exercise
Module 3: Operators & Control Statement
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Module 4: String Manipulation
Accordion Content
Module 5: List &Tuple
Accordion Content
Module 6: Dictionary & Sets
Accordion Content

Learning Objectives

Apply best practices and knowledge to think through a problem rather than try to memorise the solution.
Be able to identify many electrical and mechanical machines.
Apply engineering concepts across multiple engineering disciplines.

Target Audience

  • Anyone who is keen to learn the fundamentals of data science programming.
  • Aspiring Data Science Professionals
  • No prior experience or background in coding is required


6 Lessons40h

Module 1: Automotive Engineering

1: Introduction to Python & InstallationPreview
Test pdf
Draft Lesson
first lesson

Module 2: Python Data Types & Variables

Module 3: Operators & Control Statement

Your Instructors


8 Courses
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1 Student
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Duration 40 hours
6 lectures
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