07-30-2019, 04:13 AM
I want to write a review about Artificial Intelligence and Machine Learning E Degree. The overall observation of the learning platform where the E degree is provided is this:
1. The video and audio quality are great and there is no issue at all in understanding anything
2. A very user-friendly platform, easy to navigate and get through
3. Videos are hosted on a fast streaming server, I faced no lagging in playing them. Although, some people with weak connections might face issues.
4. Quality of video and speed is adjustable as I like to play learning videos on 1.5x speed.
5. Apart from that, there are subtitles available which makes the understanding even better for people who are used to subtitles.
Talking about the instructor:
1. Instructor is a native English speaker, which is a big plus point.
2. The instructions are very clear and the outline is well thought
3. Instructor has explained topics in great depth and with enough details that even beginners can understand. Most videos are over 20 minutes long so that people can grasp the concepts.
4. Video lectures are somewhat similar to the programming lectures given in a university.
5. For the python basics course, if you already know python, then the videos might be too long for you or too much detail as the instructor has made them beginner friendly. But you can skip through whatever you want.
Talking about what will be taught:
This E degree is a combination of 6 highly structured courses comprising of 300+ lectures and 55+ hours of video lectures. Apart from that, there are projects in every course that you need to complete to move on to the next course which is great way to check whether you have grasped the necessary concepts or you need to review some of the lectures in the course. In total there are 7 projects. So as you complete the course you can start filling your github with the projects that you do.
The curriculum is very suitable and well structured. In the first course python basics will be taught. After that the interesting stuff starts which includes Pandas, Scipy, Matplotlib, seaborn, SkLearn and Tensorflow / Keras. These libraries are so powerful and so in demand that I believe just by completing the second course of the series you are already ahead of the game. After that in the third course, a little boring stuff, yet very useful, you’ll learn mathematics for Data Science and AI using R programming language. After that a deep dive will be taken into Machine Learning using python. All the necessary concepts like Linear Regression, Support Vector Machines (SVM) will be taught. You’ll also implement Naïve Bayes Classifier, different validation techniques, K-nearest neighbors, K-means clustering. In addition to all this, Hidden Markov Model, Gaussian Mixture model and collaborative filtering will be studied. Although, there is less detail on the concepts of machine learning, but the practical work is immense and it will clear all the concepts as you go through. At first I suspected that the less details for the ML concepts might cause issues for people who are just starting with ML and have not taken any other course, but it would be just fine. For those having any issues should take a look at Machine Learning course of coursera, it will enhance the theoretical concepts which can later be applied in the practical work of this E degree course. After this Deep learning is covered briefly and not a lot of details are given for that. There could have been a more in depth study of Deep learning in this E degree, but there were less details than I expected.
Anyhow, the last course is surely worth it. There are very interesting things like:
1. Anomaly Detection using Deep Learning and Autoencoders
2. Production line performance Data Science project
3. Credit Card Fraud Detection
4. Deep Learning with Keras in R
5. ML or predictive models in IoT (Internet of Things)
6. Music Recommendation System Project using Python and R
7. ML for Cancer Treatment
8. Predicting Census income using Deep Learning Models
This last course is truly tremendous and the practical projects are going to given a good grip on the concepts of how ML and AI projects in the real world are done.
My Conclusion:
I would give this E Degree 9 / 10 because of how practical it is. The number of projects done in this E Degree are much more than any other course I’ve seen so far. So it is a big plus point. Native English speaking instructor, clear instructions, user-friendly platform, certificate of completion everything adds up to making it a worth taking course. Although, there could have been more details on the theoretical part, but I guess It was made by keeping practical aspects in consideration.
One thing that I found missing is separate certification for all the courses. Like on coursera, if you enroll in a Specialization, you get certificate for each course and later for the specialization itself. This thing is missing in this E degree and only certification you get is when you complete the E degree. Although, I will suggest the Eduonix team to change it.
Some questions:
is it newbie friendly? Yes, people with no prior experience can take it and if they put enough effort into it, they will succeed.
Will this E degree make you an expert in AI and ML? Not necessarily an expert, but you’ll definitely know much more than most of the people and it would be a starting point for advance learning of AI and ML
1. The video and audio quality are great and there is no issue at all in understanding anything
2. A very user-friendly platform, easy to navigate and get through
3. Videos are hosted on a fast streaming server, I faced no lagging in playing them. Although, some people with weak connections might face issues.
4. Quality of video and speed is adjustable as I like to play learning videos on 1.5x speed.
5. Apart from that, there are subtitles available which makes the understanding even better for people who are used to subtitles.
Talking about the instructor:
1. Instructor is a native English speaker, which is a big plus point.
2. The instructions are very clear and the outline is well thought
3. Instructor has explained topics in great depth and with enough details that even beginners can understand. Most videos are over 20 minutes long so that people can grasp the concepts.
4. Video lectures are somewhat similar to the programming lectures given in a university.
5. For the python basics course, if you already know python, then the videos might be too long for you or too much detail as the instructor has made them beginner friendly. But you can skip through whatever you want.
Talking about what will be taught:
This E degree is a combination of 6 highly structured courses comprising of 300+ lectures and 55+ hours of video lectures. Apart from that, there are projects in every course that you need to complete to move on to the next course which is great way to check whether you have grasped the necessary concepts or you need to review some of the lectures in the course. In total there are 7 projects. So as you complete the course you can start filling your github with the projects that you do.
The curriculum is very suitable and well structured. In the first course python basics will be taught. After that the interesting stuff starts which includes Pandas, Scipy, Matplotlib, seaborn, SkLearn and Tensorflow / Keras. These libraries are so powerful and so in demand that I believe just by completing the second course of the series you are already ahead of the game. After that in the third course, a little boring stuff, yet very useful, you’ll learn mathematics for Data Science and AI using R programming language. After that a deep dive will be taken into Machine Learning using python. All the necessary concepts like Linear Regression, Support Vector Machines (SVM) will be taught. You’ll also implement Naïve Bayes Classifier, different validation techniques, K-nearest neighbors, K-means clustering. In addition to all this, Hidden Markov Model, Gaussian Mixture model and collaborative filtering will be studied. Although, there is less detail on the concepts of machine learning, but the practical work is immense and it will clear all the concepts as you go through. At first I suspected that the less details for the ML concepts might cause issues for people who are just starting with ML and have not taken any other course, but it would be just fine. For those having any issues should take a look at Machine Learning course of coursera, it will enhance the theoretical concepts which can later be applied in the practical work of this E degree course. After this Deep learning is covered briefly and not a lot of details are given for that. There could have been a more in depth study of Deep learning in this E degree, but there were less details than I expected.
Anyhow, the last course is surely worth it. There are very interesting things like:
1. Anomaly Detection using Deep Learning and Autoencoders
2. Production line performance Data Science project
3. Credit Card Fraud Detection
4. Deep Learning with Keras in R
5. ML or predictive models in IoT (Internet of Things)
6. Music Recommendation System Project using Python and R
7. ML for Cancer Treatment
8. Predicting Census income using Deep Learning Models
This last course is truly tremendous and the practical projects are going to given a good grip on the concepts of how ML and AI projects in the real world are done.
My Conclusion:
I would give this E Degree 9 / 10 because of how practical it is. The number of projects done in this E Degree are much more than any other course I’ve seen so far. So it is a big plus point. Native English speaking instructor, clear instructions, user-friendly platform, certificate of completion everything adds up to making it a worth taking course. Although, there could have been more details on the theoretical part, but I guess It was made by keeping practical aspects in consideration.
One thing that I found missing is separate certification for all the courses. Like on coursera, if you enroll in a Specialization, you get certificate for each course and later for the specialization itself. This thing is missing in this E degree and only certification you get is when you complete the E degree. Although, I will suggest the Eduonix team to change it.
Some questions:
is it newbie friendly? Yes, people with no prior experience can take it and if they put enough effort into it, they will succeed.
Will this E degree make you an expert in AI and ML? Not necessarily an expert, but you’ll definitely know much more than most of the people and it would be a starting point for advance learning of AI and ML