Email : samridhi1269@gmail.com

9990816060

Instagram Youtube Facebook Telegram
Data Science and AI
  1. Introduction to AI
  2. Overview of AI applications
  3. Machine Learning
  4. Machine Learning(Basic to Advanced)
  5. NLP
  6. NLP(Basic to Advance)
  7. Deep Learning
  8. Deep Learning (basic to Advance)
  9. All Algorithms Overview
  10. Linear Regression
  11. Classification
  12. Understanding the Problem
  13. Imbalanced Classes
  14. Importance of Precision, Recall, etc.
  15. Model Development
  16. Base Model Selection
  17. Data Preprocessing
  18. Feature Engineering
  19. Training and Hyperparameter Tuning
  20. Diversity Among Models
  21. Ensemble Methods
  22. Model Evaluation
  23. Validation and Evaluation
  24. Challenges and Solutions
  25. Interpretability
  26. Deployment and Maintenance
  27. Monitoring and Maintenance
  28. Database and Technical Language
  29. SQL for Data Science
  30. Python for Data Science
  31. MongoDB (DB Mongo)
  32. Project
  33. Machine Learning , NLP & DL on Real-time Data
  34. Additional Tool
  35. Language Models (LLM)
  36. Interview Preparation
  37. Interview Questions
Practice Sessions
COURSES
Python
Oracle
React JS
Springboot & MicroServices

COURSES

Linux
Kubernetes
Core Java

COURSES

Docker
Angular
Amazon Web Services

USEFUL LINKS

Home
About Us
Contact Us