Guide to Learning Al/ML online
Today’s buzzword is Artificial Intelligence (a.k.a AI) and Machine Learning (or ML). AI has been instrumental in designing intuitive computer applications as well as some of the most famous robots like Lucy or Sophia (strong AI)- which has already created a stir by becoming the first robot (in the world) to attain a citizenship in Saudi Arabia. ML, on the other hand, is gaining momentum for its precision in dealing with one topic or subject at a time. With the immense spread of information across the globe, AI and ML are being crowned as the future of data integration and analysis systems of the world.
The number of requests on locating the appropriate online resources to learn or attain mastery on AI and ML has sprung up tremendously in the last few years. Of course, this trend will not fizzle off anytime soon.
Given the huge demand of learning the complexities of AI, ML and even DL (or Deep Learning), several authentic and trustworthy online channels are offering knowledge-based programs for beginners.
Who all can learn it online? What are the prerequisite skills?
There have been a lot of arguments on who can learn AI or ML. It is a no-brainer that a basic understanding of mathematics, e.g. basic algebra, is imperative to gain an understanding of the methodologies of the AI/ML algorithms. Hence, one of the most important prerequisite skills is to have a certain degree of knowledge of mathematical equations. If you are willing to try your hands on some of the most difficult coding programs, an added skill of coding and differential calculus truly acts as an armour.
Depending upon the learner’s goal, the knowledge and skillset can be limited to a few subjects or extended to a greater number of topics.
Students with a computer science background who have the knowledge of programming languages like Java, Python, C++ etc. do have an edge over others (without the knowledge of these languages).
What infrastructure and setup are needed?
The architecture-cum-infrastructure of AI, as well as ML, is quite complex owing to the composite mechanism of data analysis. AI is learnt in a broader context which includes the application of cognitive semantics to the comprehensive computing skills to solve complex cloud, IoT and other new generation technology development frameworks. Thus, the setup emphasizes on:
- having a high-performance GPU,
- a suitable cloud premise that helps optimize the AI and ML initiatives,
- a well-defined software,
- expansive data availability
Top 5 best online resources available to Learn AI/ML.
Online resources that have received accolades for being considered the best tools for both beginners and pundits alike. Some of the best online tools one can rely on are listed down as follows:
1. To find out answers to your specific AI/ML related questions, you can switch to Quora, GScholar, etc. and seek answers from Sebastian Thrun, Daphne Koller, Geoffrey Hinton, and many others.
2. One can also refer to some open resources like blogs/articles on Twitter. These include OpenAI, AWS AI, Microsoft Research, Baidu Research, etc.
3. There are several video resources that stand out as outstanding online tools to learn AI or ML courses. These include – Coursera (Machine Learning by Andrew Ng), Udacity (Machine Learning by Georgia Tech), Practical Machine Learning Tutorial with Python (by sentdex), etc.
4. There are several trustworthy YouTube channels to obtain information from, such as- sentdex, Siraj Raval, Data School, Machine Learning Recipes with Josh Gordon, and many others.
5. Tech blogs are quite popular these days. These bloggers exhibit their immense and updated knowledge in the AI/ML sphere in their blogs. A few names that one can refer to are – Andrej Karpathy, i am trask, Christopher Olah, Top Bots, WildML, etc.
Conclusion
In general, the online resources mentioned in this article are strong enough an evidence that the complexities of subjects as diverse as AI and ML can be learnt online without forsaking a job or other important activities a person may be involved in. Andrew Ng, who has been instrumental in providing information on AI/ML subjects online, has quoted that “AI is the new electricity… We have enough papers. Stop publishing, and start transforming people’s lives with technology”.