The course can be taken by:
Students: All students who are pursuing professional graduate/post-graduate courses related to computer science / Information Technology.
Teachers/Faculties: All computer science teachers/faculties who wish to acquire new skills.
Professionals: All working professionals, who wish to enhance their skills.
- 24X7 Access: You can view lectures as per your own convenience.
- Online lectures: ~8 hours of online lectures with high-quality videos.
- Hands-on practice: Includes source code files for hands-on practice.
- Updated Quality content: Content is latest and gets updated regularly to meet the current industry demands.
Test & Evaluation
1. During the program, the participants will have to take all the assignments given to them for better learning.
2. At the end of the program, a final assessment will be conducted.
1. All successful participants will be provided with a certificate of completion (except for demo courses).
2. Students who do not complete the course / leave it midway will not be awarded any certificate.
Topics to be covered
This is only a demo course. The full course can be bought here
- Linear regression
- Maximum likelihood estimation
- Regularization/Maximum a posteriori estimation
- Logistic regression/ Classification
- Gradient Descent
- Multiclass classification
- Support Vector Machine
- Hard/Soft margin SVM
- K-means Hard / Soft
- Expectation Maximization
- Principal Component Analysis
- Singular value decomposition
- Decision trees, Nearest Neighbours (on transformed features)
- Neural networks
- CNN, RNN
- Kernel learning
- regression, SVM, k-means, k-NN
- Boosting and Bagging
- Adaboost, Random Forest, Gradient boosting