With Deep learning systems taking over a range of artificial intelligence tasks — right from machine translation, image recognition, speech recognition and now autonomous driving — there is a huge market for machine learning specialists and analysts. The demand for AI practitioners has soared and leading tech giants are now deploying Deep Learning at scale. Consequently, there is an ever increasing demand within the industry for individuals proficient in Deep Learning.
Globally, AI is set to create 2.3 million jobs by 2020. The AI industry in India is currently estimated to be $230 million in revenue, up from $180 million a year ago. Deep Learning Professionals with 5+ years of experience command a salary of Rs. 40 to 45 lacs per annum in the industry. The profiles in demand for aspiring Deep Learning professionals include Deep Learning Engineer, NLP Engineer, AI specialist, Machine Learning Engineer among many others.
Recruiters expect potential candidates to not just know the fundamental concepts of deep learning, including neural networks for supervised and unsupervised learning but also to have knowledge of deep learning libraries such as Keras, PyTorch, and TensorFlow which can be applied to industry problems. More importantly, practitioners are expected to be able to apply deep learning to real-world scenarios such as computer vision, image recognition, object recognition, image and video processing, text analytics, NLP and even recommender systems.
Deep Learning has emerged as a highly sought after skill in AI, and there is a need for a well-rounded applied deep learning course that will allow professionals to transition to this highly lucrative field. Great Learning’s intensive 3-month Deep Learning Certificate programme covers the foundation of deep learning, neural network, computer vision, NLP and other core areas. The hands-on 3-month programme will equip students with the most in-demand skills needed to start a career in the growing and lucrative field of deep learning.
“Deep Learning is an exciting area that has the potential to significantly impact the world we currently live in. There is a growing need for developers who not only know AI and Deep Learning but can also apply their skills to solve complex industry problems. Our expert faculty coupled with a hands-on learning approach is what makes this program ideal for people looking to build a career in this field,” says Hari Nair, Co-Founder, Great Learning.
One of the best advantages of this Deep Learning program is that students will get a chance to learn from IIT-Bombay faculty — Dr. Amit Sethi and Dr. Arjun Jain who have also worked extensively with industry and widely contributed to popular deep learning frameworks like Theano and Torch. While Dr. Jain worked with Yann LeCun, a founding father of Convolutional Neural Networks (used extensively in Image recognition) during his Postdoc at NYU, Dr Sethi worked with ZS Associates in Chicago, a leading US management consulting firm.
What You Will Learn from Great Learning’s Comprehensive Deep Learning Program
- With 80+ hours of learning, hands-on projects and an excellent faculty, Great Learning is uniquely positioned to offer one of the most in-depth programmes in a structured learning format. Also, students can learn from a world-class faculty, including members from IIT-Bombay who have worked in the area of computer vision and image processing. Students will gain practical knowledge of building and deploying ML models.
- By the end of the three-month course, learners would have understood the fundamental concepts of neural networks and deep learning, its applications in Computer Vision (face recognition), NLP (detection of fake news) among other applications.
- In terms of tools, students will gain hands-on experience with popular deep learning frameworks such as TensorFlow, Keras, PyTorch. In addition, they will also learn Python for data science and understand optimization techniques, for example, gradient descent. The course will cover Python’s popular data visualization library Matplotlib, TensorBoard and other libraries used in deep learning workflow such as Pandas, Numpy, Scipy, Scikit-learn.
- When it comes to resources, students will have access to a GPU-enabled lab that will help them learn and solve problems effectively. Students do not need to invest in any computing infrastructure.
- A key takeaway from the program is that students will be able to learn deep learning methodologies and its applications in the real world. By the end of the program, they will be able to apply DL techniques not just to image-based datasets but also unstructured text and numbers.
- Experiential learning has always been a core part of Great Learning’s programs and during this program, students will be encouraged to build a portfolio on GitHub that will showcase the deep learning projects they have built over a period of three months. This portfolio will enable participants to showcase their skills to potential recruiters giving them a competitive edge in the market.
Course Name: Deep Learning Certificate Program
EXPLORE TOP EDUCATION
- TOP 10 DATA SCIENCE TRAINING INSTITUTES IN INDIA
- TOP 10 PART-TIME DATA SCIENCE COURSES IN INDIA
- TOP 10 FULL-TIME DATA SCIENCE COURSES IN INDIA
- TOP 10 COURSES AND TRAINING PROGRAMS ON ARTIFICIAL INTELLIGENCE IN INDIA
- TOP 10 CYBERSECURITY COURSES IN INDIA
Duration: 3 months
Tools: Deep Learning frameworks Keras, TensorFlow, TensorBoard and NLTK library
Language: Python and Python libraries
Home » Master Deep Learning With This Program Designed By IIT-Bombay Faculty And Great Learning
Pre-Requisites: At least two years of programming experience and familiarity with statistics, algebra, probability and exposure to data analysis is preferred.
You can read more about the program here
Provide your comments below
Richa Bhatia is a seasoned journalist with six-years experience in reportage and news coverage and has had stints at Times of India and The Indian Express. She is an avid reader, mum to a feisty two-year-old and loves writing about the next-gen technology that is shaping our world.