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Python Intermediate
Python Intermediate
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Classes and OOP Basics
Python Advanced
Python Advanced
Advanced Functions
Advanced Functions
Python Closures
Python Decorators
Higher Order Functions
Lambda Functions
Partial Functions: functools.partial
Function Annotations and Type Hints
Parameter Unpacking: *args, **kwargs
Variable Scope and nonlocal Keyword
Callable Objects: __call__
Object Oriented Programming
Object Oriented Programming
@property Decorators
Abstract Base Classes
Class Methods and Static Methods
Dunder or Magic Methods
Encapsulation and Access Modifiers
Inheritance and Multiple Inheritance
Method Resolution Order
Polymorphism
Meta Programming
Meta Programming
Metaclasses
type() for Dynamic Class Creation
Inspect Module for Introspection
Monkey Patching
Code Generations using exec() and eval()
Class Decorators
Iterarators, Generators and Coroutines
Iterarators, Generators and Coroutines
Custom Iterators
Concurrency and Parallelism
Concurrency and Parallelism
Threading
Data Model and Customization
Data Model and Customization
Custom Containers
Functional Programming
Functional Programming
Map, Filter and Reduce
Modules and Packaging
Modules and Packaging
Creating Modules and Packages
Memory Management and Performance
Memory Management and Performance
Reference Counting
Typing and Static Analysis
Typing and Static Analysis
Type Hints and Annotations
File and Data Handling
File and Data Handling
File IO
Network and Web Programming
Network and Web Programming
HTTP Requests
Testing and Debugging
Testing and Debugging
Unit Testing
Python Internals
Python Internals
Global Interpreter Lock
Security and Safe Practices
Security and Safe Practices
Managing Secrets
New Python Features and Enhancements
New Python Features and Enhancements
New Syntax and Features
Advanced Use Cases and Applications
Advanced Use Cases and Applications
Building Command Line Interfaces
Programming
Programming
Data Structures
Data Structures
List
Linked List
Stack
Queue
Deque
Hashing
Tree
Binary Search Tree
Heap
Trie
Graph
Algorithmic Concepts
Algorithmic Concepts
Searching
Sorting
Recursion
DSA Patterns
DSA Patterns
00. Prefix Sum & Line Swipe
01. Bit Manipulation
02. Two Pointer
03. Fast and Slow Pointers
04.Sliding-Window
05. Merge Intervals
06. Greedy Algorithms
07. Divide and Conquer
08. Dynamic Programming
09. Recursion & Backtracking
10. Union Find
11. Segment Tree
12. KMP Algorithm
13. Robin-Karp Algorithm
14. Z Algorithm
15. Boyer-Moore Voting Algorithm
Design Patterns
Design Patterns
Behavioural Design Patterns
Creational Design Patterns
Structural Design Patterns
System Design
System Design
Introduction
Software Architecture Patterns
Software Architecture Patterns
Introduction
Data Analysis
Data Analysis
NumPy
Scipy
Pandas
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Visualization
Matplotlib
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Handling Images
OpenCV
PIL
Machine Learning
Machine Learning
Data Preprocessing
Data Preprocessing
Handling Missing Data
Data Cleaning
Feature Scaling
Feature Engineering
Feature Selection
Handling Categorical Data
Data Splitting
Dimensionality Reduction
Models
Models
Linear Regression
Logistic Regression
Naive Bayes
K Nearest Neighbours
Support Vector Machine
Decision Tree
Ensemble Techniques
Dimensionality Reduction
Clustering
Recommendation Systems
Model Evaluation and Validation
Model Evaluation and Validation
Cross Validation Techniques
Performance Metrics for Classification
Performance Metrics for Regression
Bias Variance Tradeoff
Hyperparameter Tuning
Deep Learning
Deep Learning
Neural Networks Basics
Optimization Algorithms
Training Deep Networks
Computer Vision
Computer Vision
CNN Architectures
CNN Architectures
1. LeNet-5
2. AlexNet
3. VGGNet
4. GoogLeNet / InceptionNet
5. ResNet
6. MobileNet
7. XceptionNet
8. SqueezeNet
9. DenseNet
10. ShuffleNet
Evolution of CNN Architectures
Object Detection
Segmentation
Keypoint Detection
Optical Flow
Natual Language Processing
Natual Language Processing
RNN
LSTM
GRU
Gen AI
Gen AI
Restricted Boltzmann Machines
Variational Autoencoders
Generative Adverserial Network
Diffusion Models
Transformers
RAGs
Agents
DevOps
DevOps
Shell
Git
package manager and virtual environment
Publishing Python Packages
Documentation, Styling and Pre commit
Logging
Build Systems
Continuous Integration
Flask
Docker
Mlflow
ZenML
AI Inference & Acceleration Stack
AI Inference & Acceleration Stack
CUDA and cuDNN: Powering the Engine of Deep Learning
Inference Optimization Engines: Speeding Up AI Models for Real-World Deployment
Inference Serving Frameworks: Deploying AI Models at Scale
Edge AI Hardware Platforms: NVIDIA Jetson vs Raspberry Pi
Data Engineering
Data Engineering
Spark
Kafka
Flink
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