Learning Machine Learning In Preparation for the Fourth Industrial Revolution | by Sumayah Alzamil


Relevant supplies on ML and AI programs

Machine studying — Photo from freepik

This article will discover opinions and different related supplies on ML and AI programs. I’ve ranked them based mostly alone expertise. Also, I included all the helpful supplies that I keep in mind, hyperlinks to some web sites that I discovered very useful.

The fourth industrial revolution will usher in a very new enterprise panorama. Promising to alter the method we work together with ourselves and the atmosphere

This industrial revolution transcends past a technology-powered change. It is definitely about the start of latest processes, applied sciences, and enterprise fashions which are poised to disrupt companies.

Fourth Industrial Revolution (4IR) is comprised of a number of fields, together with:

  • Internet of Things (IoT)
  • Robotics
  • Data Science
  • Machine Learning
  • Artificial intelligence
  • 3-D printing
  • Business Analytics
  • And many different applied sciences.

One of the key elements of the Fourth Industrial Revolution is a considerable amount of information. Every day, colossal quantities of information are saved and picked up. Machine studying and AI algorithm can optimize and automate a number of analytics processes, which is able to give rise to revolutionary advances in enterprise.

With the exponential development of information, accompanied by speedy advances in expertise, there’s a sturdy want for us to be information literates. With this in thoughts, I structured a couple of growth programs related to the area of information science.

Data Science goals to extract as a lot perception and knowledge from information that can be utilized to unravel advanced enterprise processes and support choice making.

With information science, one can uncover unknown patterns and developments in information that have been by no means earlier than imagined. Data science is efficient and helpful when there’s a considerable amount of information that may be analyzed to offer extra correct outcomes.

Machine Learning (ML) is a subset of AI. It is the science of enabling computer systems to hold out and study duties that aren’t explicitly programmed to do. Machine Learning is used to find patterns in information and make predictions.

Machine studying and Artificial Intelligence fields have intrigued me with all their potentialities. The thought of an impending technical revolution is one thing that I want to be part of. Therefore, studying and constructing my expertise in Artificial Intelligence and Machine Learning was important.

I need to share my suggestions on a few of the programs I accomplished not too long ago. I attended some offline lessons, however studying on-line gave me the choice to study no matter I would like at any time when I would like.

There are a couple of stipulations that may aid you higher perceive the ideas. These are areas that it’s good to study earlier than persevering with:

  • Basic information of calculus
  • Linear algebra
  • Probability and statistics
  • Algorithms and Python are additionally stipulations for machine studying

Helpful Resources/Suggestions

  • Mathematics for Machine Learning Specialization — Coursera

This course is taught by Imperial College London. I have to point out that they’re cumbersome programs that can require lots of dedication and energy to finish. But it’s very important that you simply study the ideas defined in it earlier than studying ML.

  • StatQuest with Josh Starmer — YouTube

This course is superb for studying ML ideas and statistics. This course breaks down very advanced ML and statistics ideas into easy-to-understand bits which are easy to know. I wager you’ll love this course, particularly the enjoyable singing half.

  • Python for Everybody — Coursera

This course was straightforward to comply with and perceive. It can also be a wonderful newbie course for studying Python and would educate most of what it’s good to know earlier than you begin taking the ML programs.

  • Jupyter Notebook for Beginners Tutorials by Dataquest

I didn’t take this course. But because it’s extremely really useful, you must give it a attempt.

Once your Python expertise are good, you’ll need to get snug working with and manipulating information. NumPy, pandas, and Matplotlib are some useful assets that can assist you get began.

  • Data Analyst Nanodegree — Udacity

So many individuals have really useful this course, and happily, Udacity not too long ago partnered with the Saudi MSK academy. Thus, I registered for this Nanodegree. If you like practicals to theories, then you must take extra programs on Udacity. Their programs are very practical-oriented. But I discovered this course to be simpler than the others. If you’re a younger developer, this is a wonderful course, to start with.

  • CS221: Artificial Intelligence: Techniques and Principles — Stanford

I’ve no complaints about this course; the assignments and practicals have been excellent. We had attention-grabbing weekly coding assignments.

  • CS229: Machine Learning — Stanford

I enrolled on this course and CS221 final summer time at Stanford. I’ve shared my expertise The programs are additionally accessible on-line.

This course was nice. But if you happen to aren’t excellent at linear algebra, I counsel that you simply brush up on it earlier than you’re taking this course. Also, don’t take this course as your first introductory course to ML.

You could discover this cheat sheet useful. It was designed by Shervine Amidi, a Stanford Uni graduate.

  • Machine Learning — Coursera

Taught by Andrew Ng, this course is unarguably the hottest machine studying course proper now. The course may be very theoretical, so you’d recognize it extra if you happen to take some sensible programs earlier than you register for it.

  • Data science immersive — General meeting

General meeting not too long ago partnered with the Saudi MSK academy. Thus, I registered for this course. This course is an offline course however attributable to the pandemic, this course needed to be taken on-line. However, it was nonetheless an excellent one. Passing this course relying on whether or not you full the assignments and the closing undertaking. the good factor is that this course had a major quantity of coding required.

  • Deep studying specialization — Coursera

This specialization is wonderful, and I counsel you to take this course in case you have any curiosity in AI. Professor Andrew NG explains the worth of AI and the enhancements it may possibly deliver. This course is straightforward, straightforward to study, and properly outlined. If you want an awesome basis for your AI profession, then begin with this course.

  • Data Science Ethics — Coursera

This course is obtainable by the University of Michigan, and it explains a few of the moral and authorized frameworks surrounding information science. It is sweet to take it to know the ethics when utilizing the information

Machine Learning is a really sensible area of research, so the greatest approach to study is by doing. You can discover lots of tasks in Kaggle

Data Science will proceed to trigger digital disruptions because it continues for use in varied technological and enterprise processes. It is not a query of if, however when. If you don’t adapt shortly, you threat getting left behind.

Businesses should begin now to plan for the future and deal with how they will leverage the Fourth Industrial Revolution to enhance the worth that their enterprise can present to clients.


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