Google Deep Mind : Deep Learning Specialization



Deep Learning is a subset of Machine Learning and Artificial Intelligence that teaches computers to process data in a way that resembles the human brain. It is a specialization of Data Science and Machine Learning. This blog post will review the Deep Learning Specialization Certificate by Andrew Ng( DeepLearning.AI). It will explore:

  • What is deep learning specialization?
  • Who is the Deep Learning Specialization for?
  • Can I learn deep learning without machine learning?
  • What is the cost of the Deep learning course?
  • Can you audit the courses?
  • How long does it take to complete deep learning specialization?
  • What Skills will you gain?
  • Is deep learning in demand?
  • What is the salary of a Deep Learning expert?
  • The Pros and the Cons
  • Is the deep learning specialization worth it?
  • Does deep learning have a future?
  • What to do after deep learning specialization?

It will also consider other things you need to know that may be relevant in your career as a Deep Learning Learning expert.

What is deep learning specialization?

Deep Learning Specialization

The Deep Learning Specialization is a training program from DeepLearning.AI to teach you practical skills to understand the capabilities, consequences, and challenges of Deep Learning, AI, and ML. It teaches skills that will help you navigate job opportunities in the AI tech space.

The Program consists of 5 training courses. The courses are as follows;

  1. Course 1: Neural Networks and Deep Learning – Contains 4 modules (Introduction to Deep Learning, Neural Networks Basics, Shallow Neural Networks, Deep Neural Networks) Course Duration is 24 hours.
  2. Course 2: Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization – comprises 4 Modules (Practical Aspects of Deep Learning, Optimization Algorithms, Hyperparameter Tuning, Batch Normalization and Programming Frameworks). The course duration is 23 hours.
  3. Course 3: Structuring Machine Learning Projects – 2 Modules on Machine Learning strategy; duration is 6 hours
  4. Course 4: Convolutional Neural Networks – Contains 4 modules; Foundations of Convolutional Neural Networks, Deep Convolutional Models: Case Studies, Object Detection, Special Applications: Face Recognition and Neural Style Transfer. The course duration is 35 hours.
  5. Course 5: Sequence Models – Consists of 4 modules; Recurrent Neural Networks, Natural Language Processing and Word Embeddings, Sequence Models and Attention Mechanism, Transformer Network. The course duration is 37 hours.

Who is the Deep Learning Specialization for?

This certificate is for early-career Software Engineers, Data Scientists, and Technical Professionals who want to master fundamental concepts and practical skills in Deep Learning and Machine Learning. It is ideal for people who already know some ML/Data Science concepts.

The program is for the intermediate level. You will need a good grasp of Python (intermediate level) programming language and maths for ML/Data Scientists.

What is the cost of the Deep learning course?

The cost of the certification is through a Coursera subscription of $39 per month (US/Canada $49, UK £47 per month). The total of what you will pay will depend on how long it takes you to complete the certificate program. There are no additional fees for obtaining the certificate.

Can you audit DeepLearning.AI courses?

You can audit the courses, including all the courses that make up this certificate program. This allows you to access these courses for free. You will however not be eligible for the certificate upon completion.

How long does it take to complete deep learning specialization?

The duration for completing the certificate program is about 3 months. It is fully online and self-paced, some persons may complete it sooner, depending on personal schedules. The entire specialization program is a 125-hour course series content.

What Skills will you gain?

The certificate program includes practical hands-on and real-world Deep Learning applications. You will learn the following skills;

  • TensorFlow
  • Recurrent Neural Network
  • Convolutional Neural Network
  • Artificial Neural Network
  • Transformer

Is Deep Learning in demand?

Deep Learning is one of the fastest-growing fields in Data Science. There are currently over 23,000 Artificial Intelligence startup companies looking for experts with Deep Learning, Machine Learning, Neural networks, and related skills. This is in addition to the Big Tech companies heavy on AI and ML technologies.

The Deep Learning Specialization certificate is a good fit to access some of these demands.

What is the salary of a Deep Learning expert?

Completing the Specialization program can qualify you to work as a Deep Learning expert. You may be employed under any of the different professional roles. Some of these and their salaries are as follows;

  • Deep Learning Engineer – $107,473 to $137,018 (In the UK, £ 70,000 to 85,000) per year.
  • Deep Learning Software Engineer – $138,945 per year
  • Deep Learning Scientist – $140,037 per year.
  • Natural Language Processing Engineer (NLP) – $101,474 per year

The Pros and the Cons

The Pros

  1. The tutor of the Certificate program is a world-renowned expert on the subject. Andrew Ng
  2. Great overview of Deep Learning concepts with good foundations to understand all current AI models
  3. It has a lot of hands-on practice and exercises to help you build Deep Learning skills
  4. You get a certificate you can share on LinkedIn for companies hiring for Deep Learning skills
  5. You are getting premium Deep Learning skills at very reduced costs – compared to boot camps and college degrees.

The Cons

  1. The course content presentations are predated.
  2. You lose access to the course materials when you stop paying for the subscription.

Is the deep learning specialization worth it?

It is certainly worth it. There are certainly more upsides to taking the certificate program. First, it is cheap. You get to learn in-demand skills in Deep Learning from the most prominent tutor on the subject, a shareable certificate, and the opportunity to potentially land some of the best jobs in a data-driven career.

Other thoughts about Deep Learning you should Know

Besides the certificate, it is important to know that Deep Learning is a pretty intense career, and is subject to much research. Some common questions on the subject are as follows;

What to do after Deep Learning Specialization?

The best approach is usually to put into good use what you learned from the training. Build a good portfolio of projects that will help you land a job. If you already have one and are interested in further certifications, you may want to consider the following certs.

  • Tensorflow Developer Professional Certificate
  • TensorFlow: Advanced techniques specialization
  • Tensorflow Data and Deployment Specialisation
  • NLP specialization

Can I learn deep learning without machine learning?

Deep Learning is a subset of Machine Learning, while it is possible to learn the former without the latter, you will likely struggle with some concepts as they are sometimes intertwined. Deep Learning is used for solving complex problems.

You will do better to first take a Machine Learning training, before niching down to Deep Learning. An example will be to complete the Machine Learning Specialization Certificate (by Andrew Ng) before the more advanced Deep Learning Specialization certificate we just reviewed.

Does Deep Learning have a future?

The job outlook for a Deep Learning specialist is impressive. Job Statistics suggest that the demand for the skill will grow by 40 percent between 2023 and 2027. There is a future for the career path.

Do I need to know deep learning as a data scientist?

Short answer -no, however, in a world where there is so much by way of Collaboration, it is good to pick up some of those skills. It can make your work much easier. Moreso, Deep Learning is a crucial aspect of Data Science.

See the review of Machine Learning Specialization Certificate: What You Should Know

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