In this article, we will look at 15 Deep Learning Courses for High Salary Jobs. We will also discuss the innovations and intelligence of deep learning along with companies that are making huge contributions in the industry.  If you want to skip our detailed analysis, head straight to 5 Deep Learning Courses for High Salary Jobs.

At its core, deep learning is a subfield of artificial intelligence that focuses on building and training neural networks capable of performing complex tasks through pattern recognition and data processing. These neural networks consist of multiple layers of interconnected artificial neurons, mimicking the interconnectedness of the human brain’s neural network. By using vast datasets to adjust the network’s parameters, deep learning models can adapt and improve their performance over time that translate into increasingly accurate predictions and outputs.

Deep Learning Can Now Predict Political Ideologies

As an example of this, in a recent study conducted in Denmark, scientists used deep learning algorithms to predict the political ideology (left- or right-wing) of politicians based on their facial characteristics. The study involved using machine learning techniques on photographs of Danish politicians’ faces, and the algorithm achieved an accuracy rate of 61% in its predictions. The researchers found that right-wing politicians were more likely to have happy facial expressions, while neutral expressions were more common among left-wing politicians. Additionally, the study revealed that women with pleasant facial expressions were more likely to be right-wing, while those with serious expressions were more likely to be left-wing representatives.

The study used a dataset of 5,230 facial photographs of politicians from the 2017 Danish Municipal elections, with various exclusions made to ensure accurate predictions. The algorithm achieved better-than-chance accuracy in predicting ideology based on a facial photograph in both male and female candidates.

However, the study has limitations, such as a lack of information about the percentage of right-wing and left-wing politicians in the sample and its focus on Danish politicians, which may not generalize to other populations.

Is Deep Learning in Demand?

With an average salary of $162,073 per year in the US, the demand for deep learning engineers is on the rise. Their demand is being driven by two main factors: the increasing complexity of machine learning within the tech industry and the growing accessibility of machine learning tools in various business domains. As machine learning technology evolves, the need for specialized engineers who can navigate and optimize complex machine learning solutions becomes crucial.

For mature machine learning companies, such as large tech and fintech firms, the demand stems from the need to process real-time or near-real-time inferences from massive and dynamic data sources. Meeting these stringent processing constraints requires fine-tuning hardware and engineering advanced technology solutions, which machine learning engineers and deep learning specialists are adept at handling.

One of the key skill requirements for a deep learning engineer is being well versed in different programming languages like Python and R for machine learning and statistics. You can also check out our article about the highest paying programming languages in USA and top programming languages for AI and Natural Language Processing for more insights.

AI and the Big Giants

Alphabet Inc (NASDAQ:GOOG) has largely contributed to deep learning though its open-source initiatives, and cloud services. By releasing TensorFlow in 2015, Alphabet Inc (NASDAQ:GOOG) democratized access to powerful machine learning tools that enabled developers and businesses around the world to harness the potential of deep learning for their projects.

Moreover, Google Colab, which is a cloud-based Jupyter notebook environment, provides free access to computing resources that makes it much more convenient for students, and researchers to experiment with and learn about artificial intelligence and machine learning. This move not only promotes education and innovation but also positioned Alphabet Inc (NASDAQ:GOOG) as a leading player in the global AI and cloud computing market.

On the other hand, Meta Platforms Inc (NASDAQ:META) has significantly contribtued to the field of deep learning through the development and continuous improvement of the PyTorch project. PyTorch is an open-source deep learning framework which was originally started by Meta Platforms Inc (NASDAQ:META) and has become one of the most widely used technologies for Machine Learning training. Over the years, Meta Platforms Inc (NASDAQ:META)’s engineering teams have dedicated efforts to enhance PyTorch’s capabilities by introducing new features and optimizations to support state-of-the-art transformer models, which are foundational for generative AI.

Our Methodology

We have listed the Best Deep Learning Courses for High Salary Jobs based on the quality of the courses. We have included courses that are for individuals already at the intermediate level. While some of these may be the best deep learning courses for beginners as they start with the basics, but they eventually lead to very advanced teaching. We have gauged the quality of the courses through reviews, ratings, and the curriculum design of the courses, along with their applicability of learned concepts in the real world. We have used platforms like Reddit and LinkedIn to solidify our rankings further.

Here is a list of 15 deep-learning courses for high-salary jobs:

15. PyTorch for Deep Learning: Zero to Mastery

Offered by Udemy Inc (NASDAQ:UDMY), PyTorch for Deep Learning in 2023 is a highly acclaimed course with a 4.6 rating based on 1,321 reviews, making it a bestseller. This comprehensive course covers everything from the fundamentals of PyTorch to building real-world models and deploying custom-trained neural networks. By mastering deep learning with PyTorch, individuals would have the opportunity to become top candidates for high-paying Deep Learning Engineer positions, with potential salaries exceeding US$100,000 per year. The course also highlights the benefits of PyTorch as a fantastic starting point in machine learning, making it an ideal choice for those seeking lucrative job opportunities.

14. Complete Tensorflow 2 and Keras Deep Learning Bootcamp

Like the previous course, this one is also offered by Udemy Inc (NASDAQ:UDMY), the Complete Tensorflow 2 and Keras Deep Learning Bootcamp is a highly rated course with a 4.6 rating based on 7,516 reviews and a student enrollment of over 45,000 globally. This comprehensive bootcamp teaches students how to effectively use Python for Deep Learning, with a focus on Alphabet Inc (NASDAQ:GOOG)’s latest Tensorflow 2 library and Keras API. Learners get to gain expertise in a range of topics, from image classification with CNNs to medical imaging, time series forecasting with RNNs, GANs for image generation, style transfer, NLP, serving models through APIs, and GPU-accelerated deep learning.

13. Deep Learning A-Z, 2023

Deep Learning A-Z, 2023 is a best-selling course with a 4.6 rating based on 43,513 reviews and an impressive enrollment number of 359,887 students on Udemy Inc (NASDAQ:UDMY). Taught by two expert instructors, this course covers the fundamentals of Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Self-Organizing Maps, Boltzmann Machines, and AutoEncoders. It will help individuals gain practical experience in applying these deep learning algorithms in Python, with included templates to aid their learning journey. It is one of the best deep learning courses for high salary jobs.

12. IBM AI Engineering Professional Certificate

The IBM AI Engineering Professional Certificate offers a detailed curriculum with 5 courses, covering machine learning, deep learning, neural networks, and advanced AI techniques using popular libraries like Keras, PyTorch, and TensorFlow on Coursera Inc (NYSE:COUR). With endorsements from industry experts and a recognized IBM certificate, completing this program would showcase technical proficiency and in-demand skills to position learners for high-paying AI engineering jobs where they can provide valuable business insights from big data using machine learning and deep learning techniques.

11. Generative Adversarial Networks – GANS Intro (Deeplizard)

Generative Adversarial Networks (GANs) course offers advanced knowledge in GANs on DeepLizard that, in turn, empowers individuals to excel in high-paying job roles. By covering GAN components, adversarial nature, discriminative/generative models, and training processes with PyTorch and TensorFlow, learners gain valuable expertise. Understanding BCE loss, Deep Convolutional GANs, and neural network computational graphs prepares them for complex AI projects. With this comprehensive course, individuals can showcase their proficiency in GANs which will help them increase their chances of securing lucrative jobs in deep learning and AI.

10. Mathematics for Machine Learning and Data Science Specialization

The Mathematics for Machine Learning and Data Science Specialization course, by DeepLearning.AI, is one of  the best deep learning courses for beginners where learners gain a deep understanding of the math behind machine learning algorithms. Even though it covers all the advanced areas, with easy-to-follow visualizations, the courses cover topics such as linear algebra, calculus, Bayesian statistics, and mathematical optimization. Hence, graduates are likely to possess essential skills employers require and be prepared for machine learning interviews and high-demand job opportunities. It is one of the top deep learning courses for high-salary jobs.

9. Applied AI with Deep Learning

The course is part of Advanced Data Science with IBM Specialization and offers invaluable insights into Deep Learning models and popular frameworks like Keras, TensorFlow, PyTorch, and DeepLearning4J. With real-life examples from various domains, learners master Anomaly Detection, Time Series Forecasting, Image Recognition, and Natural Language Processing. The course covers scaling models using Kubernetes, Apache Spark, and GPUs.

8. CS231n Convolutional Neural Networks

CS231n, by Standford, is highly regarded as an exceptional online course for learning deep learning-based computer vision. Andrej Karpathy, a renowned expert in the field, teaches the course. The course offers comprehensive and well-structured content which covers not only computer vision concepts but also serves as an excellent introduction to the basics of deep learning.

7. Deep Neural Networks with PyTorch

Deep Neural Networks with PyTorch is part of the IBM AI Engineering Professional Certificate. It offers a comprehensive course on developing deep learning models using PyTorch. It covers fundamental concepts, including Linear Regression, logistic/softmax regression, and Feedforward deep neural networks. Learners will explore activation functions, normalization, dropout layers, Convolutional Neural Networks, Transfer learning, and other deep learning methods. By the end of the course, students will confidently apply their knowledge to build powerful Deep Neural Networks using PyTorch and Python libraries for various machine learning applications.

6. Probabilistic Deep Learning with Tensorflow 2

The Probabilistic Deep Learning with TensorFlow 2 course is part of the TensorFlow 2 for Deep Learning Specialization on Coursera Inc (NYSE:COUR). It focuses on quantifying noise and uncertainty in deep learning using probabilistic approaches. Individuals are made to work with TensorFlow Probability library, developing models like Bayesian neural networks, normalizing flows, and variational autoencoders. The prerequisites include a strong foundation in probability and statistics. It is one of the best deep-learning courses for high salary employment.

Click here to see 5 Deep Learning Courses for High Salary Jobs.

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Disclosure: None. 15 Deep Learning Courses for High Salary Jobs is originally published on Insider Monkey.