Course Description
This beginner-friendly Deep learning course is designed to make coding accessible to everyone. You'll learn by doing - writing real Deep learning programs from the very first class. We focus on practical skills you can use immediately, whether for automation, data analysis, or building your first app.
What You'll Learn
- Working with lists, dictionaries, and tuples
- Variables, data types, and operators
- Error handling and debugging
- Object-Oriented Programming (OOP) concepts
- Automate boring tasks (file management, data entry)
- Build simple games and utilities
- Problem-solving strategies
- Where to find free learning resources
Course Curriculum
- Deep learning Installation & Setup (Anaconda, Jupyter Notebook)
- Basic Syntax (Print, Indentation, Comments)
- Variables & Data Types (int, float, str, bool)
- User Input (input() function)
- Type Conversion (str to int, float to int, etc.)
- Project: Simple calculator
- Conditional Statements (if, elif, else)
- Logical Operators (and, or, not)
- Loops (for, while, range)
- Loop Control (break, continue, pass)
- Nested Loops
- Project: Number guessing game
- Defining Functions (def, parameters, return)
- Lambda Functions (Anonymous functions)
- Built-in Functions (len(), sum(), max())
- Importing Modules (math, random)
- Creating Custom Modules
- Project: Dice rolling simulator
- Lists (Indexing, Slicing, Methods)
- Tuples (Immutable lists)
- Dictionaries (Key-value pairs)
- Sets (Unique elements, operations)
- List Comprehensions
- Project: To-Do List Manager
- Reading Files (open(), read(), readlines())
- Writing Files (write(), append)
- CSV Files (csv module)
- Exception Handling (try, except, finally)
- Working with JSON
- Project: Student gradebook system
- Classes & Objects
- Attributes & Methods
- Inheritance (Parent-child classes)
- Polymorphism (Method overriding)
- Encapsulation (Private variables)
- Project: Bank account simulator
- NumPy Basics (Arrays, operations)
- Pandas Intro (DataFrames, Series)
- Matplotlib (Line plots, bar charts)
- Requests Module (HTTP requests)
- DateTime Module
- Project: Weather data analyzer
- Problem Statement (Real-world problem)
- Planning & Pseudocode
- Implementation (Writing code)
- Debugging & Testing
- Presentation
- Final Project: Personal finance tracker
Requirements
- Basic computer skills
- No prior programming experience needed
- A computer with Windows, Mac or Linux
- Internet connection
Instructor
Dr. Ananya Pandey
Senior Deep learning Developer & Educator | 12+ years teaching programming
Learning should be fun! I break complex concepts into simple, relatable examples. My focus is helping you build confidence to write your own code.
Course Highlights
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60+ Hours Video
High quality video content
-
15 Projects
Hands-on practical exercises
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Mobile Access
Learn on the go
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Certificate
Upon completion
Available In
What Students Say
Aarav S
"I was scared of coding, but this course made Deep learning so easy! The step-by-step projects helped me build confidence. Now I automate tasks at my job!"
Priya R
"The Hindi explanations were a lifesaver! I run a small business and now automate invoices using Deep learning. Best investment ever!"