Have you ever thought about how Google Assistant or Siri in your phone answers your questions, how driverless cars can move from one location to another, how robots carry goods in hospitals, factories and clean offices and large machinery? The technology that makes these things possible is Artificial Intelligence (AI).
- What is AI?
- Who Are AI Engineers?
- Difference between AI vs Machine learning vs Deep Learning
- Responsibilities
- Required Education And Eligibility
- Online Courses and Certifications in AI
- Required Technical And Soft Skills
- Top Institutes and training programs offering AI courses in India
- Career Opportunities in AI
- Companies Hiring AI Engineers
- Salary And Job Prospects
- Frequently Asked Questions
What is AI?
AI is the machines ability to mimic human intelligence for problem-solving. In AI the machines learn from past data and actions, and with this information, the machines make appropriate self-corrections so that the same problems don’t occur again. With increased scope for AI and Machine Learning (ML), the machines can be trained to self-decide.
AI is used in major sectors like Agriculture, Health Care, Transport, Cyber Security, Banking, Manufacturing, Hospitality and Entertainment. It has unlimited potential to find smart solutions to modern problems and simplify human tasks like visual perception, speech recognition, decision making and language transitions.
NIRF top engineering colleges 2023
Who Are AI Engineers?
AI Engineers develop, program and train the complex network of algorithms constituting the AI so they can perform the functionality of the human brain.
These engineers have to be experts in software development, data science and engineering and programming. These professionals process the data, develop and maintain the AI systems by using various tools and techniques.
They develop AI models using ML algorithms and deep learning neural networks for taking business decisions that impact the entire organization.
AI developers locate and extract data from different sources then create tests and develop ML models and use Application Program Interface (APIs) calls or embedded codes to build AI applications.
ENTRANCE EXAM QUESTIONS
Difference between AI vs Machine learning vs Deep Learning
- AI is the concept of creation of smart intelligent machines.
- ML is subset of AI that helps in building AI-driven applications.
- Deep Learning is subset of ML that uses vast data and complex algorithms for training a model.
NIRF top engineering colleges 2023
Responsibilities
- Learn and modify the prototypes of data sciences.
- Coordinate with robotics and electronics departments.
- Be up to date the latest developments in AI.
- Creation and management of AI process development and overall infrastructure of the product.
- Explain the applications of AI models to stakeholders, project managers and other individuals within the organization.
- Good team working skills as coordinating with other professionals is a must.
- Automate the l infrastructure of the data sciences team.
- Selection of appropriate data sets and data representation models.
ENTRANCE EXAM QUESTIONS
Required Education And Eligibility
- Completion of 10+2 in MPC stream with minimum of 50% aggregate from recognized board.
- Qualify entrance exams for admission in undergraduate courses like JEE Mains, EAMCET etc.
- Pursue engineering bachelors in fields like computer science, data sciences, information technology, statistics and finance.
- Pursue masters in fields like data sciences, mathematics, cognitive sciences and computer engineering to improve your employment opportunities and earning potential.
NIRF top engineering colleges 2023
Online Courses and Certifications in AI
- Deep Learning Nano degree from Udacity
- Machine Learning – Stanford University from Coursera
- AI Google Education from Google
- AI Intelligence Nano degree from Udacity
ENTRANCE EXAM QUESTIONS
Required Technical And Soft Skills
- Expertise in programming languages like Python, R, C++, and Java is required for building and implementation of AI models.
- To understand AI models, knowledge of Linear Algebra, Probability and Statistics are needed.
- Apache Spark and other big-data technologies like Hadoop, Cassandra and MongoDB etc.
- Knowledge of deep learning algorithms and frameworks like PyTorch, Theano, TensorFlow, and Caffe used in AI.
- Analytical skills.
- Business expertise with strong communication and coordination skills.
- Creative Thinking skills.
NIRF top engineering colleges 2023
Top Institutes and training programs offering AI courses in India
- Indian Institute Technology,
- Indraprastha Institute of Information Technology-Delhi,
- Great Lakes International University, and
- Jain University.
- Learnbay
- Simplilearn
- UpGrad
- Great learning
- Edureka
ENTRANCE EXAM QUESTIONS
Career Opportunities In AI
- AI Architect.
- AI Developer.
- Machine Learning Engineer.
- Data Scientists.
- Business Intelligence Developer.
NIRF top engineering colleges 2023
Companies Hiring AI
- Amazon
- Adobe
- IBM
- Uber
- Microsoft
- Wells Fargo
- Nvidia
ENTRANCE EXAM QUESTIONS
Salary And Job Prospects
For entry-level AI engineers, the annual salary is $71,600 while the salary for experienced AI professionals is $ 248,625.
According to Gartner’s report, AI was expected to create 2.3 million jobs in 2020. The demand for AI engineers have doubled up over the past few years, as a result, the job growth in AI has flooded the industry.
The business value of $3.9 trillion will be created by AI in 2022. The AI engineering industry is a rapidly evolving industry that can provide you with numerous opportunities and challenges for professional development.
Experience Level | Salary Range (Annual) |
|---|---|
| Entry Level | $70,000 – $100,000 |
| Mid-Level | $100,000 – $150,000 |
| Senior Level | $150,000 – $250,000 or more |
NIRF top engineering colleges 2023
Frequently Asked Questions
An expert who focuses on developing and implementing AI systems and technologies is known as an artificial intelligence (AI) engineer.
To create intelligent solutions, they use methods like computer vision, deep learning, natural language processing, and machine learning.
AI engineers are in charge of developing AI models and algorithms, preprocessing and analysing data, training and fine-tuning models, utilising computer vision and natural language processing technologies, deploying models in real-world settings, and staying up to date with recent developments in the field. They are essential to creating intelligent systems that can reason, learn, and make decisions, which significantly benefits a variety of fields and applications.
Certainly! As a result of its growing demand, lucrative salary potential, opportunities for creativity and problem-solving, diverse applications across industries, ongoing learning and advancement, collaborative work environments, and the growing significance of ethical considerations in AI development, AI engineering is, in summary, a very promising career choice. AI engineers are essential in fostering innovation, creating state-of-the-art solutions, and having a beneficial impact on society as AI continues to disrupt numerous industries and shape the future.
An artificial intelligence (AI) engineer makes, on average, $156,648 a year in the United States.
Depending on experience, region, and company, this pay may change. For instance, more experienced AI engineers may earn up to $201,500 year, whereas San Francisco AI engineers may earn up to $180,000 annually. AI engineers that work for major tech firms like Google or Facebook may also make more money.
The following are some of the variables that may have an impact on an AI engineer’s salary:
Experience: Experienced AI engineers can expect to make greater money. Location: AI engineers can make more money working in expensive cities like San Francisco or New York. AI engineers employed by major technology companies
Company: AI engineers who work at major tech firms should expect to make more money. Competencies: AI engineers can earn more money if they have specialised talents like deep learning or natural language processing.
You normally require a bachelor’s degree in a relevant subject, such as computer science or engineering, as well as skill in a programming language, such as Python, to be eligible for a career in AI. Understanding AI algorithms requires a solid background in math and statistics.
Understanding machine learning and artificial intelligence principles is crucial. This includes understanding supervised and unsupervised learning, neural networks, and natural language processing.
Success in the field of AI also requires abilities in problem-solving, critical thinking, data handling and analysis, and a dedication to lifelong learning.
While precise requirements could differ, having a combination of these abilities and knowledge will help you get ready for an AI job.
Most Popular links :-
