- Deep Learning
- Minimizing the Error Function with Gradient Descent
- Introduction to Neural Networks
- Training Neural Networks
Intermediate
Online
61 Hours
Quick facts
particular | details | |
---|---|---|
Medium of instructions
English
|
Mode of learning
Self study, Virtual Classroom
|
Mode of Delivery
Video and Text Based
|
Course overview
Today’s digital era has enabled the technologies to flourish exponentially. Computer systems are now able to derive more accurate results by analysing huge amounts of structured as well as unstructured data, commonly known now as ‘big data’. These advancements have assisted companies in reducing risks and identifying more profitable opportunities. The role of deep learning in this technology-driven era has assumed great significance. Deep Learning makes use of algorithms to enable automatic learning through absorption of information and data.
Being a specialized form of machine learning, deep learning enables end-to-end automatic learning using all the relevant features from the data provided. Many big brands and large organisations are extensively making use of deep learning to facilitate automation in their operations. This has led to a rise in demand for deep learning practitioners around the world.
The Deep Learning nanodegree programme course online offered by Udacity will enable you to master fundamentals of deep learning which will aid you in building a career in deep learning as well as pursue in-depth studies in the field of AI. The programme comprises 5 courses and 5 real-world projects to showcase your skills in the deep learning domain.
The highlights
- 5 courses with 5 real-world projects
- Programme content co-created with AWS
- Certification by Udacity
- Line by line code reviews
- 2000+ project reviewers having 4.85/5 rating
- Support for technical queries by 1000+ mentors
Program offerings
- Real-world projects
- Co-created content with aws
- Self-paced learning
- Project submissions
- Personalised career guidance
- Project feedback
- Technical support from mentors.
Course and certificate fees
The fee for Deep Learning is summarized as follows:
Fees components | Amount |
Annual fees | Rs. 20,500 |
Monthly fees - pay as you go | Rs. 10,250 /month |
certificate availability
certificate providing authority
Eligibility criteria
Work Experience
The Deep Learning nanodegree programme accepts all the applicants, irrelevant of their professional background or past work experience.
Education
It is expected that the participants of the programme must possess intermediate-level knowledge on Python Programming including Pandas and NumPy. The participants must have a necessary working knowledge of algebra, maths, calculus, special derivatives and matrix multiplication, in specific. It is also expected that the participants should be able to communicate professionally and fluently in spoken as well as written English.
Certification Qualifying Details
The Deep Learning programme consists of 5 real-world projects. All the participants will be required to pass in each of the 5 projects. The project reviewers will provide constructive feedback to the participants in case of unpassed projects. In order to avail the certification, it will be mandatory for all the participants to pass in each of the 5 projects. Udacity will not issue certification to participants with un-passed projects, under any circumstances.
What you will learn
Upon successfully completing the Deep Learning nanodegree programme, the participants will be able to:
- Build neural networks using Python and NumPy
- Implement gradient descent using NumPy matrix multiplication
- Build and test deep learning models using PyTorch
- Identify patterns in images using Convolutional Neural Networks
- Build autoencoders using PyTorch
- Generate new words, characters and text bodies using RNN
- Generate realistic images using generative adversarial network
- Use Amazon SageMaker on AWS to train and deploy PyTorch sentiment analysis model
Who it is for
Admission details
The Deep Learning nanodegree programme accepts all applicants, regardless of their work experience or professional background. In order to enrol for the programme, applicants of the programme should follow the process mentioned below:
Step 1: Candidates need to visit the programme URL
Step 2: Click on the Enrol Now Tab and then choose the payment options- Pay Upfront and Pay as you go.
Step 3: Once the plan is chosen, those who are regular users of Udacity will click on the ‘Returning Student’ tab while new users will click on Quick Checkout.
Step 4: If you log on to Quick Checkout then you will require to sign up via Facebook or Google.
Step 5: Then the user will land on the page which will have detailed information regarding base fees, bundle discount and total amount to be paid.
Step 6: If there is a coupon code, then enter that and checkout. If you do not have a coupon code then directly continue and proceed for checkout.
Step 7: The candidate can then make payment via debit card, credit card or any other mode.
Step 8: Once the payment is received at Udacity, a payment receipt will be mailed. Post this, the candidate can access the course.
The syllabus
Introduction to Deep Learning
Course 1
Convolutional Neural Networks
Course 2
- Introduction to CNNs
- CNN Concepts
- CNNs in Depth
- Transfer Learning
- Autoencoders
- Object Detection and Segmentation
RNNs & Transformers
Course 3
- Long Short-Term Memory Network
- Recurrent Neural Networks
- Fine Tuning RNN Models
- Implementation of RNN & LSTM
- Seq2Seq Architecture
- The Limitations of RNNs
Building Generative Adversarial Networks
Course 4
- Generative Adversarial Networks
- Training a Deep Convolutional GANs
- Image to Image Translation
- Modern GANs
Scholarship Details
Go to the course page for seeking scholarship details. Candidates need to be eligible for the scholarship. To check eligibility, candidates need to sign up. Then click on ‘Notify Me’. The candidate will start getting notifications for the scholarship. The details will be published on the website as well.
How it helps
Deep learning applications surround us in our daily lives, and its use is expected to grow more rigorously. Be it automated driving, medical research, electronics, aerospace, defence or industrial automation, deep learning applications form an integral component in these areas. The Deep Learning nanodegree programme will enable the participants to advance in their careers through the application of deep learning technology in their employer organisations.
Deep learning being the central technology behind a variety of innovations like voice control, automated driving, hands-free speakers and many more, the participants of this programme will benefit a great deal by gaining knowledge on cutting-edge topics like generative adversarial network, neural networks, cloud computing and cloud deployment. Learning from this programme will also assist the participants in taking up advanced studies in fields of machine learning and AI.
The Deep Learning nanodegree programme by Udacity will assist the participants in launching a strong career in the deep learning domain. Participants will benefit substantially from the insights shared by working professionals and industry experts as well as from the practical skills imparted by instructors during the course of the programme. Participants completing the programme can launch their careers as software engineers, data engineers, data analysts, software developers, analytics managers and assume many more roles as deep learning practitioners for well-reputed organisations and brands.
Instructors
Mr Erick Galinkin
Researcher
Freelancer
Mr Giacomo Vianello
Data Scientist
Freelancer
FAQs
Participants will be required to pass in each of the 5 projects through project reviews by Udacity reviewer network. No certification will be given to those participants who do not pass in each of the 5 projects.
The Deep Learning nanodegree programme accepts all applications, regardless of the applicant’s past work experience or professional background.
The Deep Learning nanodegree programme is designed to impart basic skills in deep learning to its participants. The programme will not prepare you for a specific job, but it will assist you in mastering your deep learning skills for career advancement.
The programme will require the participants to have access to a 64-bit computer system with minimum 8GB RAM. It is recommended that the participants have Jupyter Notebooks and Python 3 installed in their computer systems.
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