Artificial Intelligence (AI) A-Z Course Training

Humans and animals display natural intelligence, involving consciousness and emotionality. While it's not possible for machines to portray such natural intelligence, machines can be programmed to simulate some aspects of human intelligence, using the science of Artificial Intelligence.

A lot of artificial intelligence systems are powered by machine learning. Some of them may be powered by deep learning.

According to Google's AI researcher Francois Chollet, intelligence isn't the skill itself, but it's the system's ability to learn new things, generalize its knowledge, and apply it to unfamiliar scenarios.

AI's traditional goals include reasoning, knowledge representation, planning, learning, prescription, NLP (natural language processing), and the ability to move and manipulate objects. To develop AI systems, a cross-disciplinary approach involving mathematics, computer science, linguistics, psychology, and more is required.

There are broadly two types of AI.

Weak AI (or Narrow AI):

These AI systems are designed to solve a single problem and focus on performing a single task extremely well. They're called narrow as these systems can only learn or be taught to do well-defined tasks.

A few examples of Narrow AI include:

• Google search
• Siri, Alexa, and other personal assistants
• Image recognition software
• Website chatbots
• Recommendation engines behind Amazon, Netflix and Spotify

Strong AI (or General AI):

Strong AI systems are complex and complicated systems capable of carrying out human-like tasks. While movies like Westworld, Star Trek, or Terminator have shown far beyond what's possible with present AI technologies, mentioned below are some fields where strong AI is being applied.

• Self-driving cars
• Disease mapping and prediction tools
• Manufacturing and drone robots
• Personalized healthcare treatment recommendations
• Robots capable of performing operations and surgeries

There is another AI type, called Artificial Super Intelligence (ASI), that would surpass all human capabilities. This AI would be able to make rational decisions ( and be able to act on them), and even things like making better art and building emotional relationships.

Artificial Intelligence growth has been primarily due to 3 reasons:

• Variety and Volume of digital data being produced every day, and the ability to capture it
• Cheaper and powerful computational processing availability
• Affordable data storage and Cloud Technology

Machine learning and deep learning are parts of the Artificial Intelligence domain. Machine learning is a subset of AI while deep learning itself is a subset of Machine learning itself.

Machine learning is all about giving machines the ability to learn on their own. It allows computer algorithms to automatically improve and get more accurate with experience.

Deep learning involves artificial neural networks and algorithms which learn from large amounts of data. Inspired by the human brain, these deep learning algorithms perform a task repeatedly and tweak it continually to improve the outcome.

To have a great career and earn a handsome salary! You want that, right?

AI jobs now account for an average of 15-20% of jobs in most companies, with more than 130 million roles available across all major sectors. Top companies like Amazon, Microsoft, Google, Nokia, and others continually recruit AI talent.

Listed below are a few reasons why you should learn Artificial Intelligence:

• AI is witnessing explosive growth. Some estimates suggest that the AI market will contribute as much as $15.7 trillion to the world economy by 2030. From Healthcare to finance, industries from all sorts of domains are looking to apply AI (and machine learning) to improve their efficiency or personalize their marketing campaigns, creating huge demands for data-skilled professionals. But there is a huge gap between demand and supply, with only a few skilled workers to meet the ever-growing demand.
• Learning AI will expand your problem-solving skills, a skill that's not useful for the professional world, but also in everyday life as well. Develop a better understanding of systems and tools that you interact with on a daily basis.
• Artificial Intelligence is a lucrative career option with an abundance of high-paying job opportunities (with the average package of an AI professional ranging between $100,000 to $150,000 in the USA and 14 - 15 lacs in India)
• You can generate some side income after learning AI (with things like Freelancing, an informative blog/YouTube channel, selling a data science course, or creating something innovative with your data knowledge)
• Get to make the world a better place with AI-powered solutions. Get to work on cutting-edge AI applications, like the Google self driving car, or IBM's Watson. Develop and improve farming solutions that provide information about the weather, fields, and soil to farmers and help them make a profit. Or Improve online recommendation systems. Whichever field you work in, your AI works can make a real difference to the world.

No matter what your background is, you can take this AI course. You just need to be passionate about numbers, and love challenging problems.

But your journey to becoming a successful AI (or data) scientist would be much easier if:

• - You have a background in analytical disciplines such as mathematics, physics, computer science, or engineering.
• - You love coding and have a basic understanding of programming languages.
• - You are patient enough to keep working on the project even when it seems to have hit a roadblock.

• - Most comprehensive and well-structured course covering basics to advanced topics, allowing you to master the complete niche.
• - Certified Trainers with extensive real-time experience in the Data Science domain and an immense passion for teaching.
• - Top-notch course with a perfect blend of theory, case studies, and capstone projects, along with an assignment for every taught concept.
• - 100% Job Placement assistance. Frequent mock interviews to evaluate and improve your knowledge and expertise. Facilitation of interviews with various top companies. Help in building a great resume, optimizing LinkedIn profile, and improving your marketability.

AI development is possible in two domains - engineering and programming. Listed below are some of the leading AI-based career options you can break into after completing the Artificial Intelligence course:

• AI Engineer
• AI Data Analyst
• Big Data Engineer
• Big Data Engineer/Architect
• Data Mining Analyst
• Data Scientist
• Business Intelligence Developer
• Machine Learning Engineer
• Product Manager
• Robotic Scientists
• UX Designers
• Video Game Programmer
• Software Engineer