Core Track
Welcome to the Core Track! This 10-week program dives deep into modern deep learning techniques and practical applications.
What You'll Learn
This track covers essential deep learning frameworks and applications:
Week 1-4: Deep Learning Fundamentals
- Neural network architectures
- Backpropagation and gradient descent
- Activation functions and optimization
- Regularization techniques
- PyTorch and TensorFlow basics
Week 5-7: Computer Vision
- Convolutional Neural Networks (CNNs)
- Image classification and object detection
- Transfer learning with pre-trained models
- Data augmentation techniques
- Real-world CV projects
Week 8-10: NLP Basics
- Text processing and tokenization
- Word embeddings (Word2Vec, GloVe)
- Recurrent Neural Networks (RNNs)
- Sequence-to-sequence models
- Sentiment analysis and text classification
Prerequisites
- Completion of Foundation Track or equivalent knowledge
- Solid Python programming skills
- Understanding of basic ML concepts
- Familiarity with linear algebra and calculus
Course Format
Each module includes: - 🧠 Deep dive into theory and architectures - 💻 Hands-on implementation from scratch - 🚀 Industry-standard framework tutorials - 📊 Real-world datasets and challenges - 🏆 Portfolio-worthy projects
Get Started
Coming Soon: Detailed lesson modules are being developed. Check back soon or watch the repository for updates!
Sample Projects
By the end of this track, you'll build:
- Image Classifier: Multi-class classification on real-world datasets
- Object Detector: Detect and localize objects in images
- Sentiment Analyzer: Classify text sentiment from reviews
- Text Generator: Generate text using sequence models
Learning Path
graph LR
A[Foundation Track] --> B[Core Track]
B --> C[Advanced Track]
style B fill:#7c4dff,color:#fffAfter completing this track, you'll be ready to advance to the Advanced Track.