NPTEL Machine Learning Course Certification Experience

Hey Beginner!

Embarking on the NPTEL course “Essential Mathematics for Machine Learning” was a pivotal moment in my academic journey. As an aspiring Data Scientist, acquiring a robust mathematical foundation is critical, and this 12-week course provided me exactly that. The journey culminated in a final certification exam, where I was thrilled to achieve an overall score of 78, earning me the Elite + Silver certificate from NPTEL.

Preparation Phase:

I enrolled in the course at the start of June 2022, with classes beginning in July. To get a head start, I previewed the course content available on YouTube, which included around 61 videos.

Starting from July, 2022, NPTEL would unlock each week’s lectures gradually. I maintained a Notebook from the start and maintained notes for future reference. Understanding the importance of the weekly assignments, I dedicated myself to completing them diligently, knowing that the top 8 would significantly impact my final score. Additionally, I used online resources like w3wiki to supplement my learning and clarify complex concepts.

Weekly Course Structure:

The course was meticulously structured into weekly modules, each focusing on a different aspect of mathematics crucial for machine learning:

• Week 1: We delved into vectors, the basics of matrix algebra, vector spaces, subspaces, basis, and dimension.
• Week 2: Topics included linear transformations, norms and spaces, orthogonal complement and projection mapping, eigenvalues and eigenvectors, and special matrices.
• Week 3: We explored spectral decomposition, singular value decomposition (SVD), low-rank approximations, and their Python implementations.
• Week 4: Focus shifted to principal component analysis (PCA), linear discriminant analysis (LDA), and their practical applications in Python.
• Week 5: We tackled least square approximation, minimum norm solutions, linear and multiple regression, and logistic regression.
• Week 6: This week covered classification metrics, the Gram-Schmidt process, polar decomposition, minimal polynomial, Jordan canonical form, and matrix applications in machine learning.
• Week 7: Basic calculus concepts such as gradient, Jacobian, chain rule, and change of variables were introduced.
• Week 8: We learned about calculus in Python, convex sets and functions, and an introduction to optimization.
• Week 9: Numerical optimization techniques, including gradient descent and other algorithms, were the focus.
• Week 10: Optimization using Python was revisited, along with a review of probability, Bayes theorem, random variables, expectation, and variance.
• Week 11: We studied discrete and continuous distribution functions, joint probability and covariance, introduction to SVM, and error minimizing LPP.
• Week 12: The final week covered the Lagrangian multiplier method, concepts of duality, hard and soft margin classifiers, and SVM implementation in Python.

The Exam Day:

30th October 2022, was the D-Day marked on my calendar with a mix of anticipation and anxiety. The admit card was in hand, and the examination venue was selected with care. The three-hour exam consisted of 50 questions, blending assignment-based problems and conceptual queries. Each question was of 2 Marks. The strict invigilation at the center ensured a fair testing environment.

Exam Experience:

Despite facing some challenging questions, I approached each with determination, drawing on the solid foundation built through weekly assignments and intensive preparation. The best part was there was no Negative Marking, so you can make a guess for some questions. Completing the exam was a moment of triumph, knowing that regardless of the results, I had gained invaluable knowledge and skills.

Criteria to get an NPTEL Course Completion Certificate:

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.

Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Tips for Future Aspirants:

• Start early to familiarize yourself with the curriculum and expectations.
• Leverage free preview materials, such as YouTube videos, to gain preliminary insights into the course content.
• Prioritize weekly assignments as they are crucial for reinforcing concepts and significantly impact your final score.
• Use additional online resources like w3wiki to clarify complex topics and enhance your understanding.
• Engage in active learning by taking notes, practicing coding exercises, and discussing concepts with peers.
• Plan your study schedule effectively, balancing new material and revision.
• Practice with mock exams and past assignment questions to familiarize yourself with the exam format and difficulty level.
• Ensure you have all necessary documents and choose a convenient exam venue. Review key concepts and strategies but avoid last-minute cramming.

Conclusion:

Reflecting on my journey through the NPTEL Essential Mathematics for Machine Learning course, I am grateful for the experience. It has not only solidified my mathematical foundation but also prepared me for future endeavors in the field of machine learning. The knowledge and skills gained are invaluable, and regardless of the final outcome, I feel more equipped and confident in my academic and professional pursuits.

Enroll in this Course if you can, I am sure you won’t regret it!