ArewaDS website: https://arewadatascience.github.io
- Arewa Deep Learning with Pytorch Curriculum!
Welcome to the Deep Learning Course at Arewa Data Science Academy! This comprehensive course introduces you to deep learning, focusing on PyTorch, Natural Language Processing (NLP), and Computer Vision. Combining in-depth theoretical concepts with practical application, it's tailored for beginners and those looking to enhance their knowledge in AI.
- Master deep learning principles through PyTorch.
- Gain hands-on experience in NLP and Computer Vision.
- Develop a portfolio of real-world deep learning projects.
Application for Deep Learning Cohort 1.0 is closed, but you're welcome to join our sessions and access materials for self-study. Stay updated on future cohorts via our social media and Telegram group.
- Website: Arewa Data Science Official Website
- Email: [email protected]
- Twitter | Facebook | LinkedIn | YouTube | Telegram
Welcome to ArewaDS Deep Learning with Pytorch Cohort 1.0! Our fellowship offers a structured path to mastering both fundamentals and advanced concepts in deep learning.
- Stage 1: Deep Learning with Pytorch - Fundamental and advanced topics in Deep Learning using PyTorch.
- Stage 2: Natural Language Processing with Deep Learning - Advanced NLP techniques and applications.
To graduate, fellows must:
- Complete all curriculum modules.
- Submit all assignments and blog posts.
- Maintain a 90% attendance rate.
- Complete a capstone project approved by the ArewaDS Team.
Find below the resources for the kickoff of the fellowship.
| Component | Resource |
|---|---|
| Accepted Fellows | Accepted Fellows Page |
| Communication (Telegram) | Telegram Group Guide |
| Kickoff Recording | Kickoff Recording |
| Kickoff Slides | Kickoff Slides |
- Basic Python programming skills.
- Fundamental understanding of machine learning concepts.
Explore deep learning fundamentals using PyTorch, a leading framework for deep learning.
- Resource: Deep Learning with PyTorch
- Topics Covered:
- PyTorch Basics
- Neural Networks
- CNNs, RNNs
- Advanced Topics: GANs, Reinforcement Learning
| Date | Lesson | Exercise | Recordings |
|---|---|---|---|
| Week 0 | Introduction | Introductory Video | |
| Week 1 | PyTorch Fundamentals | Exercise 1 | Pytorch Fundamentals |
| Week 2 | PyTorch Workflow | Exercise 2 | PyTorch Workflow PyTorch Workflow - Q&A |
| Week 3 | PyTorch Neural Network Classification | Exercise 3 | PyTorch Neural Network Classification PyTorch Neural Network Classification - Q&A |
| Week 4 | PyTorch Computer Vision | Exercise 4 | PyTorch Computer Vision |
| Week 5 | PyTorch Custom Datasets PyTorch Going Modular |
Exercise 5 | PyTorch Custom Datasets PyTorch Going Modular |
| Week 6 | PyTorch Transfer Learning | PyTorch Transfer Learning | |
| Week 7 | PyTorch Experiment Tracking Capstone Project Introduction |
Capstone Project | PyTorch Experiment Tracking and Capstone Project |
| Week 8 | PyTorch Paper Replicating | Capstone Project | |
| Week 9 | PyTorch Model Deployment | Capstone Project | |