- The Best Deep Learning Training Courses
- Go To edX Deep Learning Training Course
- Go To edX Deep Learning Course Online
- Go To Coursera Deep Learning Specialization course
- Go To Coursera Neural Networks and Deep Learning course
- Go To Simplilearn Deep Learning Course with TensorFlow
- Final Thoughts
The Best Deep Learning Training Courses
I know why you are here! Learning how to design and use machine learning and artificial intelligence technologies is what interests you. That is what deep learning, a machine learning sub-field, prepares you to do. You must be considering enrolling in a course that will give you an in-depth understanding of these most sought-after specializations. You are in the right place. Read on.
First, let me share with you a few statistics on machine learning and artificial intelligence (AI). According to Indeed.com, the demand for AI related experts by employers has steadily risen over the years. In fact from June 2015 to June 2018, the demand rose by about 100%, while the searches for these jobs rose by around 182%.
And that’s not all. Indeed.com says that Data scientists, data analysts, data engineers, and machine learning engineers, among others are now among the most highly paid tech professionals in the US with annual salaries of up to $140,837. Glassdoor.com puts the average annual pay at $139, 840. Yes, you read it right.
Now, let’s check out the best Deep Learning courses around to help you make the right decision on which one to go for. Let’s dive in right away, while taking a look at what each course includes, the cost, and the course duration.
1. edX Deep Learning Training Course
- Course Creators: Microsoft
- Prerequisites: requires learners to have intermediate experience in machine learning before beginning the course. The course, however, is not currently accessible to students from Cuba, Iran and Crimea in Ukraine.
- Training fee: The course is free but you would be required to pay $99 for each course for you to get verified certificates. edX offers financial aid to anyone who may not afford the fee for the course and verified certificates.
- Duration: The self-paced course will take you 6 weeks if you learn 4-8 hours a week.
- Languages: English
- What does the course include?
Deep Learning Explained course delves into the use of computers to build complex models used by machines to solve real-world challenges while using intelligence similar to human. The process adopts the use of “Microsoft Cognitive Toolkit” in harnessing this intelligence. The course is one of those included in the comprehensive Microsoft AI course.
The topics you will cover are:
- Deep Learning and Machine Learning Introduction
- Use of logistic regression to build a simple but multi-class classification model
- How to detect digits in a digit-image that is hand-written, beginning with a simple end-end model to a deep neural network
- How to improve the hand-written digital recognition using convolution network
- How to build a model that forecasts time data with the use of recurrent network
- How to build an application called text-data with recurrent Long Term Short Memory (LTMS) units.
The course with quizzes and hands-on labs is part of the Microsoft Professional Program (MPP). This means that once you successfully meet the required specifics, you will earn a completion certificate.
2. edX Deep Learning Course Online
- Course Creators: IBM
- Prerequisites: To begin this course, you must have some intermediate knowledge of machine learning techniques using python programming. Knowledge in Jupyter and Python notebooks is also recommended. Learners from Cuba and Iran cannot access this course
- Training fee: It will cost you $445.50. edX offers financial aid to anyone who may not afford the course
- Duration: It is self-paced and has 5 courses that will take you 5-6 weeks each.
- Languages: English
- What are the details of the course?
EdX Deep learning course takes you through the concepts you required in building a “deep learning model” with the use of Keras, PyTorch and TensorFlow libraries. They include the applications and rewards of deep learning skills, the aspect of convolution and recurrent networks and autoencoders. It also equips you with knowledge needed in applying deep learning to situations like object recognition as well as Computer Vision, video and image processing, text analytics, NLP (Natural Language Processing), and other classifiers.
The course includes the following topics:
- Deep Learning with Python and Pytorch
- Deep Learning with TensorFlow
- Using GPUs to Scale and Speed-up Deep Learning, and
- Applied Deep Learning Capstone Project
This course’s peak is the capstone project which gives you a chance to showcase your skills in a real-world situation. Once you meet all the conditions, you are eligible for a certificate.
3. Coursera Deep Learning Specialization course
- Course creators: The course is created by deeplearning.ai and offered in partnership with Deep Learning Institute.
- Prerequisites: It is designed for those who already have an intermediate experience in machine learning.
- Training fee: The course allows you a 7-day trial period in which you can audit a few video lessons and content for free. You will then be required to pay a monthly subscription fee of $49 which you are automatically billed once the trial period elapses. In case you don’t wish to proceed with the training, you must cancel it before the 7 days elapse. If you can’t afford the course, you can apply for financial aid here.
- Duration: It consists of 5 courses that will take you around 16 weeks/4 months. You can choose to take any one of the 5 courses alone should you wish to.
- Languages: The video transcripts are available in English. The subtitles can be in English, Chinese (Simplified), Japanese, Turkish, Chinese (Traditional), Korean, Portuguese (Brazilian), and Ukrainian.
- What does the course include?
The course takes you through the basics all the way to becoming a master in providing deep learning solutions. You will learn how to implement a neural in the TensorFlow framework.
These are the 5 lessons that you are required to cover:
- Neural Networks and Deep Learning
- Improving Deep Neural Networks
- Structuring Machine Learning projects
- Convolution Neural Networks, and
- Sequence Models
You are allowed to proceed to course 2 if you already have a verified “Neural Networks and Deep Learning” certificate. Also taking any of the courses individually is allowed. However, it would be more appropriate to progress through the courses beginning from the first. This is because each course builds on the knowledge and experience of the one preceding it. There are quizzes and assignments for each course.
The final course consists of a machine translation programming assignment provided by deeplearning.ai in partnership with DLI (NVDIA Deep Learning Institute). You get an opportunity of building a project on deep learning.
4. Coursera Neural Networks and Deep Learning course
- Course creators: Created by deeplearning.ai and offered in partnership with Deep Learning Institute.
- Prerequisites: Intermediate experience is a must. It targets professionals with basic programming knowledge in Python and who can effectively work with use of data structures.
- Training fees: Learners have a free 7-day trial period. Once this elapses, you will be required to pay a monthly subscription of $49 which you are billed immediately the trial period ends. For anyone who can’t afford the training fee, they can apply for financial aid through this link.
- Duration: This is course 1 of Coursera “Deep Learning Specialization” course and takes you 4 weeks studying 3-4 hours per week.
- Languages: It is available in English. The subtitles are in Chinese (Simplified), Korean, Chinese (Traditional), Portuguese (Brazilian), Turkish, Japanese and Ukrainian.
- What does the course cover?
The course takes you through the basic concepts of deep learning that include the following topics:
- Understanding the major technologies that drive Deep Learning
- Building, training and application of deep neural networks that are fully connected
- Knowledge in implementing an effective vectorized neural network
- Understanding of the key or major parameters within neural networks
The 4-week long course consists of video lectures, readings from an interactive coursework book, and graded assignments at the end of each week. These training resources and assignments are only available to you once you enrol and pay the required fee. However, there are some few video lessons and content that you can audit for free within the 7-day trial period. Once you meet the course requirements, you will have an access to an electronic certificate that’s added to your own Accomplishments page.
5. Simplilearn Deep Learning Course with TensorFlow
- Course creators: Simplilearn
- Prerequisites: It targets professionals who already have an intermediate to advanced skills. Basic knowledge in Python programming, statistics and machine learning is a must. It is recommended for data scientists, data analysts, software engineers and statisticians interested in deep learning.
- Training fee: $599
- Duration: The compact course consists of up to 9 modules that take you 40 hours. Once you enrol, you will have a 90-day access to the instructor-led course and a 180-day access to the self-paced online learning course. Weekend classes are also available.
- Languages: English
- What does the course include?
The course uses the open-source TensorFlow software library developed by Google and created for the purpose of conducting deep neural and machine learning network research. At the end of the course, you should be able to understand TensorFlow, its concepts, functions, operations, and execution pipeline.
You must be in a position to implement the algorithms of deep learning, troubleshooting and provision of deep learning model solutions, and demonstrate your knowledge in building your own project on deep learning. You should also be able to tell the difference between deep learning, artificial intelligence, and machine learning, among other things.
It covers the topics below (you can download the syllabus here):
- Introduction to TensorFlow
- Activation Functions
- Artificial Neural Networks
- Gradient Descent & Backpropagation
- Optimization & Regularization
- Introduction to Convolution Neural Networks
- Intro to Recurrent Neural Networks, and
- Applications of Deep Learning
The course consists of video lessons, quizzes and hands-on projects. To qualify for the certification, you must attend a complete batch, and complete and satisfy the evaluation process of any of the given projects. You must also pass a simulation exam consisting of 144 questions. You are given up to 3 attempts in the exam. The certification is valid for life.
So, what next from here? Now that you are familiar with what the courses entail, it’s time to decide on which deep learning course works best for you. Here you’ve got all you need to help you make that decision. Remember, AI and machine learning technology is where the present and the future are. So you better be part of these innovations that are taking the world by storm, and are here to stay.