Deep Reinforcement Learning Expert

There are no admission criteria for the Deep Reinforcement Learning course and any candidate can avail of the course irrespective of his background provided he fulfils the formalities. Udacity offers the option to pay the course fee in whole or in instalments payable each month.

The following steps must be carried out for registering in the programme-

Step 1: Go to the homepage of the Deep Reinforcement Learning course.

Step 2: Click on the ‘Enroll Now’ option.

Step 3: Select a payment plan depending upon your preference 

Step 4: Depending on whether you are enrolling for the first time or whether you are a regular course-taker, you may choose between ‘Quick Checkout’ and ‘Returning Student’ respectively.

Step 5: Clicking on Quick Checkout will require you to sign up via your Google or Facebook account. In the case of the latter option, you must sign up from your Udacity account.

Step 6: The webpage shall now display the e-bill specifying the base price, bundle discount, and the total amount chargeable.

Step 7: You may enter the discount coupon code if you have one. Else, click on ‘Continue With Checkout’ to finalise your plan.

Step 8: You are then supposed to put in your billing details

Step 9: You will be provided immediate access to the classroom after the payment is successful.

Exhaustive details on scholarship programmes by Udacity are available on the course page. After visiting the link, candidates must sign up for the programme by entering relevant information under the “Notify Me” section. Post-sign-up, they will be eligible for scholarships and will also be entitled to receive notifications regarding present and future scholarships. 

The webpage features a “Learn More” tab which would redirect a prospective candidate to the webpage concerning scholarship programmes suited to his/her needs.

Deep Reinforcement Learning has immense industrial significance given the fact that software giants like Apple, Facebook, and Google are investing in it. Engineers having a strong hand over the field can expect handsome job opportunities and packages. This programme prepares the candidates for the outside world in this aspect. Building a robust portfolio of the projects undertaken by the students is one step in that direction.

The highly interactive mode of learning through personal career coaching, mentor support, knowledge portal and other features makes the course engaging and understandable. Pedagogy also aims at preparing the candidates for interviews and preparing their resume to perfection.

The lessons have been crafted so that candidates become able enough to write their own implementation of classical solution methods and apply the architectural framework to functioning tasks. Creation of an agent which navigates a virtual world from sensory data is also a major benefit of the course. From studying the theory behind evolutionary algorithms and policy-gradient methods to deploying it in designing algorithms for manipulating a robotic arm, this programme teaches it all.