Career Opportunities in Deep Learning-List of Job Roles

Original article was published by Divyas S on Artificial Intelligence on Medium

Career Opportunities in Deep Learning-List of Job Roles

Artificial Intelligence was first coined in the early 20th century. From there, there is a tremendous development in the field. Artificial Intelligence now encompasses everything from Machine Learning, Deep Learning, Natural Language Processing, Image and Vision Processing to Humanoid robots and Neural Networks. These terms are used interchangeably but have a subtle difference between them. In this post, we’ll talk about deep learning in specific.

Introduction to Deep Learning

The deep learning process involves educating humanoid robots or machines to work like humans. This process is not that simple, it involves complexity in the following areas:

  • Statistics
  • Calculus
  • Linear algebra
  • Probability
  • Programming

This involves other branches of AI such as NLP, and Image processing. Further, includes recognition of speech and text, machine Learning and Neural Networks. Deep Learning is a combined study of all of this. The below diagram shows how the Deep Learning algorithm finds the correct word from the picture that is given as an input.


In a simple representation, Deep Learning consists of initially learning from the inputs and then storing them. Then comes the actual tests when the picture is again shown along with other pictures, it correctly recognizes the picture.

It consists of an input array, the hidden things which are the processor, and then the output array.

Guide to switch career in Deep Learning

There are various ways to learn Deep Learning.

  1. Videos — There are a lot of YouTube videos that you can refer to for this. These videos are for beginners as well as for experts and have been uploaded by the Deep Learning research and other DL engineers.
  2. Blogs — Search in Google where you can find a lot of blogs where the authors and Deep Learning enthusiasts have written them.
  3. Training Institute — There are a lot of reputed institutes, one such institute for getting the DL and AI course training is “Great Learning
  4. E-books — Lot of e-books can be found some of them are free and available in pdf’s for download from the web
  5. Hard Copy Books — You can purchase the hard copy books from sites like Amazon and Other publishers.
  6. Websites — Some websites publish articles and writings on Deep Learning you can find them in google search.

Why it’s Important to Practice Deep Learning

As we have seen a lot of ways to source out the Deep Learning materials, now you must download software which helps you program deep learning. Then download the examples and datasets available on the web to give practice to the deep learning software. The data sets are required so that you know how the software works, what is the precision and how to fine-tune the software. You may need knowledge in complex programming using languages such as Java, Python, etc, and other knowledge on mathematics, probability, calculus, linear algebra, and statistics. You may also need to brush up the skills and learn other branches of AI such as ML, NLP, Image and Vision Processing, Neural Networks and Text & Speech recognition, etc.

One of the other best ways is to practice the lab sessions after the theory in a training institute such as “Great Learning”. Great Learning provides a lot of practice sessions with the live, real-time simulation software with the data sets.

Getting started with a career in Deep Learning

You must first think to start and that is the first step to get into a deep learning career. Then automatically come your interest, commitment, and zeal.

  1. Kind attention freshers to deep learning — Get hold in programming and then search online for some inputs about AI and DL. Read books, but the quickest way is to enroll in an AI certificate course and training which has Deep Learning also. We recommend AI online courses in “Great Learning” which teaches beginners and advanced level experts, they have excellent faculties with them.
  2. If you have programming knowledge — It is easy to transition to Deep Learning and AI with some hard efforts. Learn the basics and go for the AI e-learning course with “Great Learning” Brush your skills in mathematics, algorithms, and statistics. Also, practice on the job more on ML and AI.
  3. If you are an undergrad in computer science, then begin your DL journey by learning AI, understand the AI software and different data sets. You can even try doing your Master’s degree followed by a Ph.D. in Computer Science or Mathematics with a specialization in AI. A simple way is to enroll with “Great Learning” to get more skills and do research in AI.
  4. If you have a Master’s or Doctorate in CS or Mathematics — We recommend trying to find some job in ML, AI, or DL to ignite the engine. Work on your programming skills and brush your mathematics, advanced algorithms, and statistics skills. Alternatively, enroll in “Great Learning” to acquire advanced skills in AI and DL. During your study in Master’s or Ph.D. do some research in ML, DL, and AI.

Learning path for a career in Deep Learning in detail

  1. Get started — First thing is to get started, there are various online resources and study materials available for you to get started. Start learning the basics of probability, statistics, and learning python.
  2. Get started with ML — The next step is to learn the fundamentals and advanced level requirements in ML. You need to learn techniques in logistic regression, regularization methods, and linear regression. You need to have skills in core concepts of calculus and linear algebra. Start practicing derivatives, vectors, and matrices.
  3. Keras and Introduction to Deep Learning — Start learning an introduction to Neural Networks and practicing programming with the Keras software.
  4. Neural Networks and Fine-tuning DL — The succession is to fine-tune the skills on models of Neural Networks and Deep Learning. You need to do some iteration in DL to get the desired output, so doing the only iteration will not give the results. Try to do hyperparameter tuning, preprocessing images, and transfer learning to improve the DL models.
  5. Get the knowledge of CNN’s — CNN stands for Convolutional Neural Networks, they are the building blocks of any DL models to get the maximum and precision outputs.
  6. Learning DL modules and debugging — One of the most effort oriented tasks is to debug the DL modules and find out where the things are going wrong.
  7. NLP — One of the important steps next is to learn the basics of NLP. NLP consists of image, vision, text, and speech processing techniques. NLP is making machine or DL modules understand the human languages.
  8. GAN — One of the most done research work in DL is Generative Adversarial Networks (GAN) where things like creative writing and creative artworks are done.
  9. Sequence Models — This includes make the machine do Long Short Term Memory Analysis (LSTM), Recurrent Neural Networks (RNNs) and Gated Recurrent Unit (GRU) techniques.
  10. Unsupervised Learning — One of the relatively easiest methods in DL is to do supervised learning. However one of the challenging tasks and getting a lot of attention in the research communities is to do unsupervised learning.

Deep Learning Career Path

  1. Deep Learning Engineer — They are experts who work on Neural Networks and have experience in software engineering, software development, source control, testing, and continuous integration. They work with advanced DL modules that mimic the human brain.
  2. Deep Learning Scientist — They work on advanced DL modules and NLP to make the machine understand the language what human understand. This is done what humans do that is to learn by examples.
  3. Deep Learning Research Engineer — do path-breaking research in the field of AI and DL. Especially working on various advanced mathematics, advanced AI, and advanced algorithms.

2020 Deep Learning Jobs

2020 has promising job opportunities in IT giants like Microsoft, Wipro, Google, Adobe, Amazon, Accenture, Robert Bosch, and JP Morgan Chase. The demand for AI and DL skills is very high and leaps to increase in the future. The AI and Deep Learning jobs are very niche skills jobs and they are bound to have skills gap Vs demand gap.

Jobs created by AI would surpass the jobs vanished by AI in the next 5 years. Deep Learning scientists and engineers have great command in the industry when compared to all other roles across the job market. In 2020 the average salary for DL engineers is approximately USD 82,000 annually.

Concluding thoughts about AI courses

The demand for Deep Learning engineers and scientists has touched exponential proportions. Start early in this journey and grab the opportunity to obtain the necessary skills in AI. Learn from Great Learning’s free certificate courses in AIML or enroll for the PGP in Artificial Intelligence and Machine Learning.

For inquiry and more details visit Great Learning’s website today.