Data Analytics using Python

Training Milestones

Book Counselling Session

Module 01:- Introduction to Programming

Why Learn to Program? Discover how programming serves as a gateway to solving real-world problems. Learn why Python is the chosen language for data scientists worldwide.

    Essentials Covered:-

  1. 1. The Computer: More than just hardware; it's your canvas for creating solutions.
  2. 2. Programming Languages: From human thoughts to machine operations.
  3. 3. Why Python? Simplified syntax, vast community, and an ocean of libraries.
Module 02:- Basic Programming Concepts

Building Blocks of Python Programming: Master the fundamentals that form the backbone of any software application.

    Essentials Covered:-

  1. 1. Variables and Data Types: Your toolkit for data manipulation.
  2. 2. Operators and Expressions: The grammar of Python.
  3. 3. Data Structures: Organizing data with Lists, Tuples, Dictionaries, and Sets.
Module 03:- Control Statements

Steer Your Code: Control the flow of your programs using logical structures.

    Essentials Covered:-

  1. 1. Decision-Making: Crafting the decision tree.
  2. 2. Flow Control: Navigating through the code.
  3. 3. Loops: Doing more with less; automate repetitive tasks.
Module 04:- Functions and Their Types

Modular Programming: Learn to write reusable pieces of code that make programming more efficient and organized.

    Essentials Covered:-

  1. 1. Functions: The building blocks for reusable code.
  2. 2. Parameters and Arguments: Customize how functions behave.
  3. 3. Recursion: Solving problems by solving smaller instances of the same problem.
Module 05:- Python Libraries

Tools of the Trade: Unleash the power of Python's data libraries to handle, analyze, and visualize data.

    Essentials Covered:-

  1. 1. File handling.
  2. 2. NumPy: The cornerstone for numerical computing.
  3. 3. Pandas: Data manipulation at your fingertips.
  4. 4. Matplotlib & Seaborn: Painting data in visual form.
  5. 5. Linear Algebra: Dive deep into data structures and manipulations.

By now you will have all the necessary tools to start working on your internship.

The following will be covered in the internship period.


Module 06:- Object-Oriented Programming (OOP)

Blueprints of Complexity: Dive into the OOP paradigm to manage more complex data systems with ease.

    Essentials Covered:-

  1. 1. Classes and Objects: The nuts and bolts of OOP.
  2. 2. Inheritance: Streamlining code through hierarchical arrangements.
Module 07:- Machine Learning Algorithms

The Intelligence Layer: Explore how algorithms can discover patterns and make decisions with minimal human intervention.

    Essentials Covered:-

  1. 1. PCA: Reducing dimensions.
  2. 2. K-Means, DBSCAN, Hierarchical Clustering: Grouping data.
Module 08:- Industry-grade-projects using Streamlit

Learning to collaborate, Deploying Your Applications, and turn your scripts into shareable web apps using Streamlit.

    Essentials Covered:-

  1. 1. Git and GitHub.
  2. 2. Setup and Elements: Building blocks of Streamlit apps.
  3. 3. Deployment: Share your insights with the world.
Module 09:- Databases

    Essentials Covered:-

  1. Introduction to Databases: SQL