AI for Students

Get Consultation for:

(Career Guidance || Consultation || Project Planning || Mentorship)

Technologies:

1. Machine Learning
2. NLP
3. Deep Learning
4. LLM Optimisation
5. Parallel Computing Systems
6. Generative AI
7. RAG
8. Fine-tuning
9. LoRA
10. Model compression
11. Quantisation
12. Knowledge distillation and Performance optimization of LLMs.
13. Building scalable Gen-AI application on cloud.

Frameworks:

1. Sklearn
2. Keras
3. Tensorflow
4. Pytorch
5. LangChain, LangGraph, LangSmith, LangFlow
6. LLamaIndex
7. pandas
8. numpy
9. MLflow
10. Opik

MLOPs:

1. End to End Model lifecycle
2. MLflow
3. Opik.
4. ML Operations

APIs and web development:

1. Flask
2. Django
3. REST APIs.

System Design:

1. Load Balancer,
2. Caching
3. Hashing
4. Load Routing
5. API dev
6. Radis
7. Nginx
8. Gunicorn
9. Master slave
10. Sharding
11. Rate limiter
12. Scalable deployment architecture.

Cloud:

1. AWS
2. Azure
3. GCP