About the course

Does your profession require you to deal with large data on a regular basis?  

Do you wish you could be better at dealing with those numbers?  

This course brings about a solution for you by teaching you how to manipulate and analyse the data in the most basic language, Python.

This course doesn’t only seek to teach you about data analysis but also helps you learn how to apply it in real-life situations. Apart from detailed programs on learning the basics of Python and the art of data analysis using Python, the course provides you with five projects that are real-life case studies.

Starting with the basics of Python, learn how to analyse big data, visualise them, and become an entry-level data analyst.

Here is an outline of what we'll cover through the entire course:

  • Preparing your environment and software installation
  • Logical and looping constructs
  • Dealing with functions
  • Modules and packages
  • Dealing with file I/O in Python
  • Working on different data types such as CSV, JSON, RDBMS, and Excel
  • Dealing with non-relational database management systems
  • Dealing with web-related data
  • Data analysis and visualisation using DataNitro


Real-Life Project Work was done with Python:

Once we've got a grip of Python and data analysis, it'd be great if we could get some hands-on experience by trying out what we've learned, right? So here are some projects that we'll work on:

  • Project: Data management system using RDBMS  
    Problem statement: A company XYZ sales deals in solar products and they sell their products all across a country to their customers. So far they have been storing their data in an Excel file. But since their growth has exceeded and in sync with the sales, they need a concrete data management system with an organised data structure
  • Project: Store data from a CSV file to RDBMS.  
    Problem statement: Take Yahoo finance data in the CSV format and store the data into an RDBMS.
  • ·Project: Dealing with Web Data  
    Problem statement: Dmoz is a website, which is an open directory for various websites regarding different categories. We can go to the sports section and get related websites. However, websites keep getting added. So, we need to create a web scraper that automatically fetches all the links in the particular category and stores the data in a CSV format on the file system.
  • Project: Data Analysis and Visualization 
    Problem statement: UIDAI (Unique Identification Authority of India) is an Indian authority responsible for creating biometric data-based identification cards for the Indian citizens. They provide data based on state, gender, and rejection and acceptance of the identification cards in the form of a CSV file. We need to create a helpful visualisation to explore which state, age range, or gender got how much percentage of cards rejected or accepted.
  • Project: DataNitro  
    Problem statement: Yahoo finance hosts financial data for different companies. We need to implement a solution that can get finance data of different companies and make charts based on the fetched data. We also take you through DataNitro 
    [It lets you run any Python script or library - right in your spreadsheet]. I'm in love with this tool :) [Disclosure - I'm not their affiliate and make no money from their sales]

Important information before you join:

  • Once enrolled, you have unlimited, lifetime access to the course!
  • You will have instant and free access to any updates I'll add to the course.
  • I will give you my full support regarding any issues or suggestions related to the course.
  • Guided practice - over worksheets included for immediate practice
  • Access to all videos 24 x 7 - learn online from anywhere


If you have read this far, next action is JOINING this course. Invest 6 hrs. for a benefit of the lifetime.

Who Should Attend?

  • Software professionals, ETL developers, and Project Managers
  • Advanced Excel users who want exposure to Big Data
  • Fresh IT/Engineering graduates who are willing to add resourceful knowledge for their better career prospects

Lesson 1: What is Programming? Why should you care?
Lesson 6: Modules & Packages
Lesson 10: What are the other data sources out there
Lesson 11: Dealing with Non-Relation database management systems
Lesson 14: Data Nitro
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