Intro to Machine Learning with PyTorch

Intro to Machine Learning with PyTorch admission requires the candidate to undergo the following steps-

Step 1- Visit the official website of the programme https://www.udacity.com/course/intro-to-machine-learning-nanodegree--nd229

Step 2- Click on Enroll Now button on the top of the page.

Step 3- You will be directed to a page wherein both payment options namely, Pay Upfront and Pay as you go is given. 

Step 4: Choose the desired plan. Regular users will have ‘Regular Student’ button on their page while new users will have ‘Quick Checkout’ as option. 

Step 5: Select Quick Checkout and then sign up with your Google or Facebook ID.

Step 6: Then a page will come wherein all the details of fee payment will be given. If you have coupon code then apply it and click on checkout or else directly click on continue with checkout. 

Step 7: The payment will be made by the user with debit card, credit card, net banking and others. 

Step 8: After doing the payment, a transaction slip will be shared. Then you will be able to check the course and access it. 

Participants applying for Intro to Machine Learning with PyTorch classes can do so by visiting the link https://udacity.zendesk.com/hc/en-us/categories/360002443511-Scholarship-Programs. The candidate needs to then see whether he/she is eligible for scholarship. Hence, it is essential to sign up and submit the information after clicking ‘Notify Me’. Post this, the candidates will be regularly sent notifications for the scholarships posted on the website. 

The demand for machine learning engineers is far more than the supply. Health care sectors, finance to market predictions, and many other industries are changed by machine learning. A candidate with appropriate knowledge of the same will have great career advancements. 

This Intro to Machine Learning with PyTorch certification benefits by helping the learner to know about the foundational machine learning skills which can be applied in the real world. The machine learning techniques taught in the course can be applied to various tasks such as image classification and customer segmentation. Several learning algorithms applications learnt in the duration of the course will enable the learner to demonstrate skills in a better manner. It will help enhance the practical skills needed to start.