What is AI?
Artificial Intelligence (AI) refers to the intelligence revealed by machines and it is not like the ordinary intelligence displayed by humans and animals, which contains perception and emotionalism. The name Artificial Intelligence itself portrays the division from Natural Intelligence. AI is the arena devoted to building artificial living beings that is either Cognitive-based i.e., the systems capable to think like human beings, or Behavior-based i.e., the systems capable to perform like humans.
The main objective of AI is to permit computers to achieve such logical tasks as decision making, acuity, problem-solving and thoughtful human communication.
A Brief Historical Background
The history of AI was initiated many decades ago when folktales of fictitious beings powered with intelligence, attracted attention worldwide. Alan Turing introduced a computer called an Automatic Machine in 1936. This machine could find out the arithmetic model for calculations that could ultimately help in determining the rationality of any algorithm. However, the term "Artificial Intelligence" was introduced late in 1956 by McCarthy after a conference held at Dartmouth College.
Impact of AI is everywhere
AI is nearly having a great impact on the upcoming of virtually every human being and industry on the planet. It has signified a great number of developing technologies including robotics, IoT, and big data, and it is prospected to remain a technological modernizer in the future as well.
Almost every major industry is applying modern AI. This is more specifically called a "narrow AI," which accomplishes predefined roles with the help of data-trained mockups. Narrow AI falls into the categories of DL (deep learning), and ML (machine learning). At present, data collection and its analysis have geared up significantly. Thanks to AI, along with IoT connectivity, our life has become quite easy. By employing computer vision and ML, various "safety events" are detected and classified. Hence fairly small devices can help us to avoid safety violations such as determining where the driver is looking while driving, his speed, location of his vehicle and people surrounding him, and the disturbance by the other vehicles on the road. Hence AI ensures smooth and safe driving. Software by IFM detects any safety violation autonomously and warns warehouse management to take immediate action. The main purpose is to reduce the number of accidents and enhance efficiency.
Few of the segments are at the initial stage of their AI voyage, while many are expert travelers. But both groups have a long way to go. Nevertheless, the influence AI is casting on our current lives is quite difficult to overlook:
- Healthcare – In the AI-promising arena of healthcare, disease diagnosis is more rapid and efficient. AI is also helping the speedy and updated discovery of drugs. Virtual nurses look after the patients, while data analysis support creating a well-modified patient involvement.
- Conveyance – Though it could consume an era or more to make it perfect, the future of driver-less cars prevailing everywhere is all its way.
- Industry – Many industries are already having AI-powered robots working along with the human workforce to perform some tasks on assembly lines. Moreover, AI-driven predictive analytics help the industry to keep its equipment working by predictive maintenance and avoiding machine downtime.
- Media – The impact of AI on broadcasting is hard to ignore. Social media is enduring great benefits from AI. Bloomberg is using a technology that is Cyborg-like to support make a speedy understanding of intricacy.
- Education – Digital Coursebook can be said the upcoming future. With AI applications like facial analysis tools, a teacher can easily identify a student if he is bored or enjoying the lesson and hence can make adjustments according to their individual needs. According to research "The AI market of USA, Education Sector is predicted to progress at a CAGR of 47.77% during 2018 to 2022."
In what way AI transforms the learning experience
According to New York Institution professor, Yann LeCun:
“Our intelligence is what makes us human, and AI is quite an extension of that quality.”
Artificial Intelligence is based on the following three fundamental principles:
- Education: Gaining and dealing out the new skill, developing innovative behavior mock-ups.
- Auto-correction: Liberating the processes so that the most precised results are obtained.
- Cognitive: Selection of a specific algorithm to perform a specific task.
Best countries to pursue Masters in AI
AI spans a wide range of domains, including deep learning, healthcare applications, natural language processing, data analytics, and big-data mining, and many corporations are searching for experts in these areas. A professional degree in AI from a reputable university can help you launch a career in this field.
The best master's level curriculum in this subject is a Master of Science in Artificial Intelligence. MSc in Artificial Intelligence programs are available at a number of prominent universities across the world. Earning a master's degree in Artificial Intelligence while studying overseas is a good alternative since the scope and breadth of study courses are exceptional and wide. Here is our list of top countries to pursue a Master in Artificial Intelligence:
United States of America
The USA is full of the best universities that are widely known for masters in AI programs. Machine Learning and Machine Intelligence are some of the expert programs in the USA. The USA offers this program with much expensive cost and also the lifestyle expenses in the country are also not affordable to all. Endowment opportunities are provided by few universities in the USA; however, with highly competitive subjects such as AI, it is considerably difficult. English proficiency tests IELTS (6.5) or TOEFL (89) scores are also mandatory primary requirements.
One of the most reliable subjects of AI in Australia is "The statistical and deep learning”. The field of Information technology is the leading specialized subject of AI in the country. The education cost for AI in this country is cheaper than in the USA with comparatively affordable living expenses. Key requirements for admission are “Entrance exam GRE” along with “English proficiency test IELTS or TOEFL or PTE”.
When we talk about Germany, it is a leading maker in AI devices like automobiles which are one of the primary targets devices. The fee structure in German universities is the cheapest of all as the many public sector universities offer education systems that have resulted in competition in terms of admission and job opportunities in this field.
Many international students prefer the technical universities in Ireland due to the higher quality of education and also many networking companies have set their headquarters in the country. This also provides job facilities in the field. Educational expenses for masters in AI in Ireland can be expensive; however, due to the facility of student loans, individuals can enroll in the universities of Ireland. The main requirements for the program are GRE and English proficiency test IELTS or TOEFL
Most Indian students highly prefer Canada for education as the general facilities and quality of education is quite student-friendly. Masters in AI Canada programs are much-admired and are also considerably cheaper than in the USA. Canadian universities are also known to offer one of the best Computer science degrees for higher education. GRE scores and IELTS or TOEFL scores are requirements for enrolling in M.Sc. in AI program in Canada.
The UK is a highly reputed and much-liked education destination. International students majorly prefer M.Sc. Robotics and M.Sc. Artificial Intelligence programs. The fee structure for a master's in AI is comparatively cheaper than in the USA. IELTS or PTE is a mandatory requirement for international students.
Top AI Certification and Courses
- Machine learning by Stanford University (Coursera)
- Deep learning specialization by Andrew NG (Coursera)
- Professional Certificate Program in Machine Learning & Artificial Intelligence (MIT University)
- Professional Certificate in Computer Science for Artificial Intelligence (Harvard University)
- Machine Learning Certificate (Cornell University)
- Certificate in Machine Learning (University of Washington)
- Artificial intelligence A-ZTM: learn how to build an AI (Udemy)
- IBM's Applied AI Professional Certificate
- Artificial intelligence Nano Degree Program (Udacity)
- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)
Top Data Science Certification and Courses
- HarvardX’s Data Science Professional Certificate
- MicroMasters® Program in Statistics and Data Science
- Data Science Specialization (Johns Hopkins University)
- Data Scientist with R (datacamp)
- Applied Data Science with Python Specialization (University of Michigan)
- IBM Data Science Professional Certificate (Coursera)
- CAP – Certified Analytics Professional (CAP®)
- SAS® Certified Data Scientist
- AWS Certified Data Analytics
- Microsoft Certified: Azure Data Scientist Associate
Popular AI Courses, Certifications & Online Classes for 2021
Looking to learn AI skills? No doubt, learning AI is not so easy, but it has become very manageable with a variety of courses and training available online. Best AI educators, researchers, and experts offer a much lesser cost than a typical college course.
To help you make the right choice, we have compiled this list of the best AI courses, classes, certifications, Training Programs, and Tutorials. These are available online from which you can use to gain a good grounding in the field of AI. Following AI courses, certifications, or training programs will help you gain proficiency and prepare you for a promising career in AI and machine learning (ML).
1. Machine Learning by Stanford University (Coursera)
This Stanford Machine Learning Course was created in 2016 by Andrew Ng, the most renowned expert in AI and ML, Co-founder of Coursera, Formation lead of Google Deep learning, Study unit Google Mind, Former Skull of AI at Baido, and currently CEO at Landing AI. The popularity of the ML course can be judged from the point that around 3.5 million students and professionals have already taken this course and 93% of them have given it a five-star rating. Undoubtedly, AI experts often sight this course as the single most important resource for anyone looking to learn AI and ML.
Key Highlights of this course are:
- Highest rated among the Top Free ML and AI courses available online.
- Excellent fit for beginners in the field of AI and ML.
- Study about the most operative ML techniques, and gain repetition implementing them.
- Study about particular of Silicon Valley's best performs in the field of AI and ML innovations.
- Gaining the practical Knowledge desired to quickly and sturdily apply ML techniques to new real-life conditions and hitches.
Duration of the Course – 11 weeks, 5-6 hours per week
2. Deep Learning Specialization by Andrew Ng (Coursera)
The part of AI that is rising rapidly and driving a lot of development and transformation that AI is advertised for is Deep Learning. This Deep Learning Specialization created and taught by Andrew Ng is a more advanced course series for those looking to learn about AI and Deep Learning, How to relate it to solve the problem and figure a career in AI. Since it is not an entry-level program, beginners are expected to have Python Programming and Mathematics Skills and some knowledge and experience in ML. This specialty is cited as the next logical follow-up to Andrew NG's ML course on Coursera.
Key Highlights of this course are:
- Mater the theory of AI and Deep Learning and get how it is functional in the industry.
- Rehearsal in Python and Tensor Flow.
- Recognize Industry best performs for building and deep learning applications.
- Getting direction from deep learning experts and leaders in the arena.
Duration of the Course – 4 months, 5 hours per week
3. IBM Applied AI Professional Certificate
This certificate-based program has been created by IBM, the global leader in tech and one of the pioneers in AI innovations. It is targeted at those who want to learn the skills to work and AI developers. This program also supports an enterprise that is ambitious to employ AI applications and reap its benefits. It coaches the learners about AI tools such as ML, NLP (Natural Language Processing), data science, dispensation, twin Classifications, IBM Watson services of AI, image processing, and many more. It also guides the learners to get started with using pre-built AI smarts without having to create AI mockups and back ends from scrap.
Key Highlights of this course are:
- Gain the skills to generate AI-Powered applications.
- Exercise Basis of Python and understand its Programming ideas for AI as well as Data Science.
- Study to use AI services by IBM Watson, and APIs for designing, developing, and organizing AI-driven applications with minimal coding on the web.
- Especially worthy for those who need to become developers of AI solutions.
- It clarifies what computer visualization is and its applications.
Duration of the Course – 5-6 Months, 2-4 hours per week
4. IBM AI Engineering Professional Certificate
This certificate-based course is in AI offered by IBM. It has been designed in such a way that it inculcates the skills and tools necessary for starting a career as an AI or ML Engineer. It is quite suitable for existing professionals such as AI developers and data scientists who want to level up with ML and deep learning skills. It also serves well the students looking to enter the workforce with highly in-demand AI and ML skills.
The program comprises six self–paced courses that provide learners with a complete understanding of learning.
Duration of the Course – 3-4 Months, 12 hours per week
5. MicroMasters Program in AI from Columbia University (EDX)
This certificate-based program is offered by Columbia University, via the EDX platform. It is a very demanding graduate-level professional program that signifies 25% of the course work towards a Master's grade in processer at Columbia.
This bundle consists of a series of 4 courses that help as a foundation of knowledge in AI and ML and two of its key applications, robotics, and computer animation. These areas follow:
- Artificial intelligence (AI) – It teaches how to design intelligent machines that extract data online using certain criteria or keywords.
- Machine learning (ML) – Mainly includes overseen learning techniques for reversion and arrangement, unverified learning techniques for data showing analysis, probabilistic against non-probabilistic modeling, and optimization and implication algorithms.
- Robotics – It covers the rudiments of robotics directing on both the mind and the figure. It teaches the essential techniques for representing robots that achieve a real task in the real world.
- Simulation and CGI motion – This course studies the basic rules of gestures and how to turn them into supercomputer programs.
Key Highlights of this course are:
- Get a solid understanding of the foundational principles of AI
- Learn from experts in the field who teach at Columbia university
- Smear concepts of ML to real difficulties and applications
- Strategy and harness the power of neural networks
- Study to design intelligent mediators used as news rescue services, for online shopping and involuntary tasks
- Discover the applications of AI in fields of robotics, visualization, and limitations
- Exercises and assignments that help to comprehend real-world issues and come up with appropriate AI solutions
Duration of the Course – 10-12 Months, 8-10 hours per week
AI – a skill of the Future
AI is the skill of the future. It has been estimated that by 2030, the AI market will contribute more than USD 15 trillion to the world economy. AI has tremendous potential applications across industries. Be it healthcare, finance, mobile, automobiles, smart home devices, music and movie recommendation services, retail security surveillance, fraud detection, virtual player games, social media apps, the possibilities are endless. Almost every business is trying to implement AI in their processes and products. Learning AI can therefore open a world of opportunities for anyone. A combination of AI and ML and Deep Learning (DL) can chart out a way to great career prospects.
There is a huge skill shortage in the field of AI. Therefore, when planning for a career, getting skilled in AI can guarantee a promising fool-proof career. For these already in the workforce, re-skilling and up-skilling with future-oriented job skills like AI are more relevant than ever.
Career prospects after Masters in AI:
- Data Scientists
- Natural Language Processing (NLP Engineers)
- Machine Learning Engineers
- Computer Vision Engineers
- Network Analytics
- Cloud Engineers
AI Jobs is one of the most projected careers in the world. Top and leading networking firms in the world hire masters in AI graduates with attractive packages that are highly impressive. It is an experimental and fascinating field of the study approached by individuals with keen enthusiasm in the field. The world is also excitingly looking forward to AI-based devices that are being created and worked on every day under the expertise of individuals who have graduated with a degree in AI.