Training Milestones
Book Counselling Session
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. The Computer: More than just hardware; it's your canvas for creating solutions.
2. Programming Languages: From human thoughts to machine operations.
3. Why Python? Simplified syntax, vast community, and an ocean of libraries.
Building Blocks of Python Programming
Master the fundamentals that form the backbone of any software application.
Essentials Covered:-
1. Variables and Data Types: Your toolkit for data manipulation.
2. Operators and Expressions: The grammar of Python.
3. Data Structures: Organizing data with Lists, Tuples, Dictionaries, and Sets.
Steer Your Code
Control the flow of your programs using logical structures
Essentials Covered:-
1. Decision-Making: Crafting the decision tree.
2. Flow Control: Navigating through the code.
3. Loops: Doing more with less; automate repetitive tasks.
Modular Programming
Learn to write reusable pieces of code that make programming more efficient and organized.
Essentials Covered:-
1. Functions: The building blocks for reusable code.
2.Parameters and Arguments: Customize how functions behave.
3. Recursion: Solving problems by solving smaller instances of the same problem.
Tools of the Trade
Unleash the power of Python's data libraries to handle, analyze, and visualize data.
Essentials Covered:-
1. File handling.
2. NumPy: The cornerstone for numerical computing.
3. Pandas: Data manipulation at your fingertips.
4. Matplotlib & Seaborn: Painting data in visual form.
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.
Blueprints of Complexity
Dive into the OOP paradigm to manage more complex data systems with ease.
Essentials Covered:-
1. Classes and Objects: The nuts and bolts of OOP.
2. Inheritance: Streamlining code through hierarchical arrangements.
The Intelligence Layer
Explore how algorithms can discover patterns and make decisions with minimal human
intervention.
Essentials Covered:-
1. PCA: reducing dimensions.
2. K-Means, DBSCAN, Hierarchical Clustering: Grouping data .
Learning to collaborate
Deploying Your Applications
Turn your scripts into shareable web apps using Streamlit
Essentials Covered:-
1. Git and GitHub.
2. Setup and Elements: Building blocks of Streamlit apps.
3. Deployment: Share your insights with the world.
1. Introduction to Databases: SQL