Artificial intelligence (AI) is the branch of computer science dealing with the Simulation of Intelligent behaviour in computer. Artificial intelligence makes the machine intelligent. Machine make intelligent and behave as human by using Artificial Intelligence.

Artificial Intelligence is the science and engineering of making computer machines able to perform tasks which normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. “Which normally require human intelligence?”

HISTORY OF ARTIFICIAL INTELLIGENCE

Alan Turing Question was:

Turing raised the question of the possible intelligence of a machine for the first time in 1950. Researcher where exploring machine intelligence much before the AI research come about in 1956.Turing said can machine Think?

Turing Test:

The Turing test in 1959 is the test of machine ability to exhibit intelligent behaviour like a human C has to find who human A is or B using written answer. His article "Computing Machinery and Intelligence" and described a "game of imitation", where a human should be able to distinguish in a teletype dialogue whether he is talking to a man or a machine. However controversial this article may be (this "Turing test" does not appear to qualify for many experts), it will often be cited as being at the source of the questioning of the boundary between the human and the machine.

Turing predicted that a chatbot would convince 30% of judges By 2000 Eugene Goostman achieved this milestone in June 2014

• AI (Artificial Intelligence) - The brood discipline to creating intelligent machines.
• ML (Machine Learning) - Is the study of computer algorithms that improve automatically through experience.
• DL (Duckworth-Lewis System) - Method sets targets based on the relative resources available to the teams.

SCOPE OF ARTIFICIAL INTELLIGENCE

The ultimate effort is to make computer programs that can solve problems and achieve goals in the world, as well as humans. There is a scope in developing the machines in game playing, speech recognition machine, language detection machine, computer vision, expert systems, robotics and many more.

WHAT YOU SHOULD STUDY BEFORE OR WHILE LEARNING AI?

Study mathematics, especially mathematical logic. The more you learn about sciences, e.g. physics or biology, the better, for the biological approaches to AI, study psychology and the physiology of the nervous system. Learn some programming languages--at least C, Lisp and Pro log. It is also a good idea to learn one basic machine language. Jobs are likely to depend on knowing the languages currently in fashion. In the late 1990s, these included C++ and Java.

ARTIFICIAL INTELLIGENCE APPLICATIONS & EXAMPLES

• Virtual Personal Assistants :

  Basically, in this, a huge amount of data is collected from a variety of sources to learn about users. Also, one needs to be more effective in helping them organize and track their information.

• Video Games:

  We use AI — Since the very first video games.

• SIRI :

  Basically, machine Learning technology is used by Siri users. Also, they use it to get understand natural language questions and requests.

• TESLA :

  Is something you are missing if you are a car geek. Also, this is one of the best automobiles available until now.

CAREER OPPORTUNITIES

One can expect jobs at Public and Private sectors which are American Association for Artificial Intelligence, European Coordinating Committee for Artificial Intelligence and many more.

JOB ROLES:

• Game Programmer
• Robotic Scientist
• Computer Scientist
• Software Engineer

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Microsoft Power BI is a business intelligence platform that provides nontechnical business users with tools for aggregating, analysing, visualizing and sharing data. Power BI is a Data Visualization and Business Intelligence tool that converts data from different data sources to interactive dashboards and BI reports. Power BI suite provides multiple software, connector, and services - Power BI desktop, Power BI service based on Saas, and mobile Power BI apps available for different platforms. These set of services are used by business users to consume data and build BI reports. This tutorial covers all the important concepts in Power BI and provides a foundational understanding on how to use Power BI.

Data Mining

In simple words, data mining is defined as a process used to extract usable data from a larger set of any raw data. It implies analysing data patterns in large batches of data using one or more software. Data mining has applications in multiple fields, like science and research. As an application of data mining, businesses can learn more about their customers and develop more effective strategies related to various business functions and in turn leverage resources in a more optimal and insightful manner. This helps businesses be closer to their objective and make better decisions. Data mining involves effective data collection and warehousing as well as computer processing. For segmenting the data and evaluating the probability of future events, data mining uses sophisticated mathematical algorithms. Data mining is also known as Knowledge Discovery in Data (KDD).

CONCLUSION

As a result, we have studied the future of Artificial Intelligence and also learned future of Artificial Intelligence from job perspective. As we have learned practical applications that will help to take a right decision in this direction.