Certificate Course on AI-ML @ CDAC

1. Introduction to AI

2. How AI is affecting on real life?

5. Knowledge Representation in AI

4. Advantages and Disadvantages of AI

5. Knowledge Representation in AI

6. Different Branches of AI

 7. First Order Logic

8. Numerical Python

9. Tensorflow

10. Introduction to Computer Vision

11. Video Basics

12. Image Transformation

13. Smoothing and Blurring

14. Thresholding

15. Edge Detection

16. Histogram

17. Thresholding

18. Edge and Contour detection

19. Machine Learning Algorithms

20. Datasets

21. Data Analysis with Pandas

22. Data Visualization for AI

23. Data Cleaning

24. Feature Scaling Techniques

25. Data Encoding

26. Feature Selection

27. Principal Component Analysis

28. t-SNE

29. Linear Regression 

30 .Cross validation techniques

31 .Regression Performance Evaluation

32. Multiple Regression

33. Polynomial Regression

34. Classification

35. Logistic Regression

36. Decision Tree

37. K-Nearest Neighbor

38. Naive Bayes Classifier

39. AUC and ROC

40. Support Vector Machine

41. Ensemble Learning 

42. Overfitting and Underfitting

43. Unsupervised Learning and k-means clustering

44. DBSCAN Algorithm

45. Association Rule Mining

46. FP-Growth Algorithm 

47. Outliers or Anomaly Detection

The programs are available here: