date_rangeMay 16, 2020
Artificial Intelligence is one of the most disruptive technologies for some time now. It has changed the way other industries function. Many other sectors like Tourism, Environmental Studies, Entertainment, Agriculture, etc. are continuously exploring ways by which they can implement AI in their work. According to Gartner, leading organizations are expected to double the number of AI projects within the coming year, and over 40% of them plan to deploy AI solutions by 2020 end.
The increased need for speed and accuracy and continuous innovation has resulted in AI becoming one of the fastest-growing technologies. Due to substantial progress in AI, there is a need for skilled professionals. At the moment, there is much more demand for trained Artificial Intelligence (AI) professionals than there is supply. The advent of AI has brought about a lot of new and exciting career options in the field, and this is an excellent time to start learning AI-related technologies.
A Machine Learning Engineer is a computer programmer whose primary responsibility is to program machines to perform tasks intelligently. They train systems to keep learning by using data. Machine Learning Engineers have to be comfortable working with large amounts of data and algorithms. Some of the programming languages that are commonly used by Machine Learning Engineers are Python, Java, and Scala. Algorithms are crucial in Machine Learning. Strong coding skills, analytical skills, problem-solving skills, and critical thinking are essential for Machine Learning Engineers. According to payscale.com, the average salary of a Machine Learning Engineer in the USA is $110,889.
A Robotics Engineer creates complex robotic systems and robots that efficiently perform tasks. Along with creating robots, Robotics Engineers have to ensure that the systems they are developing are safe to use. Robots have been widely introduced in the agriculture industry to perform tasks like pest control, irrigation, etc. They are used in restaurants to perform tasks like helping out in the kitchen, in the health care sector for purposes like floor cleaning, patient care, etc.
The scope of Robotics Engineering is large. Some of the skills required by a Robotics Engineer are curiosity, independence, excellent problem-solving abilities, good programming skills, Python skills, Artificial Intelligence (AI) knowledge, and critical thinking. According to Indeed, the average salary of a Robotics Engineer is $106937.
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, deep learning, and big data. - Wiki
Data Scientists are professionals who apply many processes, methods, and techniques on large amounts of complex data and come up with valuable insights from the data.
With so much data being generated every day, businesses have turned to this data to help them gain valuable information about their business and make future decisions. Data Scientists are highly needed now. They need to be comfortable working with complex structured and unstructured data and be ready to spend time cleaning, processing, and working with the data.
Some of the skills they need to have are strong Data Structure and Algorithms skills, Statistical skills, good Mathematical skills, comfort with programming languages like R and Python, and excellent analytical skills. The job of a Data Scientist requires a liking for research and intense study since they have to spend time studying random data. While this is a challenging job, it certainly is fascinating, is very high paying, and comes with a lot of scope for growth. The average salary of a Data Scientist is $123599, according to Indeed.
NLP Engineers design and develop Natural Language Processing (NLP) systems. Computers find it difficult to understand human language since it has its own grammar and rules. NLP Engineers bridge the gap between computers and human language and work towards making computers interpret human language. Some of the famous applications of NLP are Alexa and Google.
NLP Engineers need skills like Python, R, Java, comfort using algorithms and statistical methods, Spark, Hadoop, good problem-solving abilities, analytical thinking, text representation techniques, knowledge of Machine Learning frameworks and libraries and good communication skills. The average salary of an NLP Engineer is $107k, according to payscale.com
A Big Data Engineer handles complex big data systems. The main responsibilities include designing, creating, and managing large and complex processing systems while working on multiple big data platforms and NoSQL databases.
Since Big Data provides crucial insights for a business, therefore a Big Data Engineer's job is critical. Some of the skills needed by a Big Data Engineer are Hadoop, Spark, NoSQL technologies like MongoDB and Cassandra, DB architectures, SQL Technologies. Other skills involve persistence, problem-solving abilities, research skills, and good communication skills. The average salary of a Big Data Engineer is $89838, according to payscale.com.
Many people are worried that AI will replace a large percentage of jobs in the future. While this may be true, it is also to be noted that AI will create an equal or larger number of jobs. At the moment, very few people possess the skills necessary to work in the innovative field of AI. Employers say that most of their employees will have to upskill and learn AI technologies to be able to set themselves apart from the rest. This is an apt time to learn AI and Machine Learning since there are so many lucrative job opportunities available.
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