Hello!
I have been enrolled at Stanford and have been taking their courses online. Here are my few cents on the ones I have taken so far.
CS224n – Natural Language Processing with Deep Learning (Prof. Manning)
- Difficulty: 4/5 (Moderate)
- What to expect:
- Get exposed to State-of-the-Art (SoTA) Deep Learning techniques applied to NLP. Key topics:
- Question and Answering
- Text Summarization
- Parts of Speech tagging
- Sequence-to-Sequence models
- Transformers
- Gives you a very good overview of where NLP is headed, homeworks are challenging but allow you to implement latest neural architectures to solve various language problems.
- My class project: BertQA (99* stars on github) – Won Best Project Award in the class
CS231n – Convolutional Neural Networks for Visual Recognition (Prof. Li and Justin Johnson)
- Difficulty: 4/5 (Moderate)
- What to expect:
- Extensive overview of latest trends in Computer Vision techniques across different domains and applications –
- Discriminative models
- Unsupervised techniques
- Neural Architecture layers and intutions
- Segmentation
- Generative Techniques
- Style Transfer
- Homeworks are the best part of the class which allow you to implement a variety of Neural Layers and get in-depth intuition of how deep learning actually works.
- I would suggest some familiarity with matrix calculus and probability for this course.
- My class project: Spatio-Temporal Adversarial Video Super Resolution
CS221 – Artificial Intelligence – Principles and Techniques (Prof. Liang and Prof. Sadigh)
- Difficulty: 4.5/5 (Heavy)
- What to expect:
- This is one of the most “dense” classes I have come across at Stanford. The nature of the class is such that it is trying to fit in this huge umbrella of AI topics within a quarter – which is what makes it challenging. Topics include –
- Search
- Markov Decision Process
- Reinforcement Learning (RL)
- Adversarial Games
- Constraint Satisfaction problems
- Bayesian Networks (BN)
- Amongst these, Reinforcement Learning and Bayesian Networks are conceptually heavy topics which require some extra effort.
- That being said, the topics are interesting and makes you appreciate the latest trends in AI and draw parallels from traditional techniques.
- Homeworks are weekly and can take time but are fun for the most part! You build your own Pacman game.
- My class project:
- Work in progress (to be updated shortly)
Feel free to send in any other questions you would like for me to answer.
Thank you,
Ankit Chadha