The students of Business Analytics got the opportunity to have hands-on training experience for the most popular programming language “Python”. The teaching was undertaken by Mr. Manish Agarwal who is well versed with Python programming and having a healthy experience in the industry. Python is an interpreted high-level general-purpose programming language. Its design philosophy emphasizes code readability with its use of significant indentation. Its language constructs as well as its object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects. You can do coding in Python and the coding is much simpler and much easier than the old school coding languages like Java , C and C++ . As the coding consist of simple English words it’s easy for a newbie or a Java developer to get along with Python. 

The topics she has covered were

  • Introduction to Python
  • String Indexing and functions
  • Operators
  • List , Dictionary and Tuple
  • If – else - elif
  • While loop and For loop
  • Functions
  • OOPS
  • Class – Methods and inheritance
  • NumPy – Arrays
  • Pandas – Series and Data Frame
  • Pandas - Data cleaning and conditional formatting
  • Matplotlib.


Analytics is a constantly evolving field where we deal with large sets of unstructured data. The process requires transferring, analysing, manipulating, and visualizing the data. So , using Python programming is one of the best tools we can use to clean data and perform various operation on data . 

Key Take away from the workshop:

  • Idea about Python programming.
  • Improved observation skill towards data.
  • How to use Jupyter notebook and importing data.
  • Conventional and user-friendly programming language.
  • Efficient in dealing with large data sets.
  • Widely used for Importing , Cleaning and analysing data .
  • Supports different file formats like Excel ,Csv, etc.
  • Innovative and immersive which helps in effective visualizations and analysis.
  • Helped us strengthen our programming skills and helped develop our data analysis skill.


The workshop consisted of both graded and practice assignments which helped us know our strength and weakness. Healthy doubt solving sessions also had a positive impact on our understanding. Real-world datasets like the IPL dataset we had for the presentation, gave fruitful insights to explore through real world datasets, to ask the right questions from the datasets and take different conventional and unconventional approach towards one problem.