Foundations of Python

The aim of the module is to get the participants familiar with the basics of the Python integrated development environment, the nuances of python scripting, basic operational functionalities and control structure used. This is an integral part of Python since it lays the foundation for participants to be able to code simple and complex programs.

• Getting Ready – Install all required software and libraries and understand the Python IDE
• Basics of Python Scripting
• Data Types (Numbers, String, List, Tuple, Dictionary, Set, Data frames)
• Operators (Arithmetic, Compound, Comparison, Membership, Logical, Identity)

Functions and Control Flow

This module deals with conditional statements and control flow which helps in creating programs with decisions. Having modular code is one of the best practices of any programming language, especially Python. In this module you will also learn how to create modular code using functions.

• Functions (Function syntax, Return value, Return multiple values, Passing argument values, Default argument values, Variable argument sequence)
• Control Structure (Conditional, Loop, Iterating Over Multiple Sequences, Break & Continue)

Object Oriented Programming Concepts and Working with Files

The objective of the module is to get the participants familiar with the OOP concepts within Python and working with files. Through this the participants will learn how to work with external data sources, be it files or databases and also to write reusable codes on Jupyter and how it is useful as a presentation tool.

• Classes, Methods, Attributes
• File I/O and the Operations on Files Regular Expressions

Practice Project and Presentation

Python Libraries, Web Scraping and Dealing with APIs

This module will help you understand two of the most important libraries in python which are required for most operations: numpy (numerical python) and pandas (data manipulation). These libraries will help you code more complex programs. It will also cover an important concept which involves use of scrapers to source data from the www and using APIs which are a critical part of any programming language.

• Basics of Numpy and Pandas
• Operations using Numpy and Pandas
• Basics of Web Scraping
• Using APIs to get and use data

Understanding Data

To learn how to get data from external sources into the Python environment and manipulate and analyze data. Before any data analytics project, it is very important to use statistical algorithms and methods to analyze data as part of the data analytics process.

• Introduction to python packages for data manipulation
• Importing and exporting data
• Importing datasets and understanding data
• Basics of analyzing the data

Data Wrangling

To learn about how python libraries can be leveraged to deal with data inconsistencies, issues with data and making them fit for data analytics. This is where 80% of today’s data scientists and engineers spend their time and it if very important to know how to do it.

• Dealing with data issues and preparation in Python
• Data Formatting and conversions in Python
• Data Wrangling
• Working with Pandas in detail

Practice Project and Presentation

Model Development for Analysis

This module gives the participants the very first steps towards forming hypothesis and doing predictive analytics. It aims to equip participants with the basics of how supervised machine learning models work and how evaluation and optimization can be carried out.

• Hypothesis Testing
• Linear Regression and Multiple Regression Models
• Model Evaluation Methods
• Model selection

Data Visualization

The objective of this module is to understand basic metric and KPIs (Key Performance Indicators) of different business cases and plotting advanced interactive visualizations for data analysis to gain insights from data.

• Understanding basic metrics and KPIs
• Visualizations using Python (Seaborn, Folium)

Practice Project and Presentation

Each participant will be awarded a certificate of completion at the end of the bootcamp.