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Artificial Intelligence: – 21st century Skills – Microsoft Professional Program

Career in Data Science:

Artificial Intelligence is the fastest growing field in the last decade.  Projects like self-driving cars to Google Brain, have used artificial intelligence to make a huge-impact.

Artificial intelligence is used to make machines that behave like humans. It could be driving cars or some accounting work. Artificial Intelligence is currently solving many problems. One of the important aspects is natural language processing(NLP), learning the behavior of natural systems, knowledge gathering etc.

This is the right time to become an artificial intelligence engineer. Its not an easy task. But if you are already familiar with different programming languages, tools, and computer science basics, you can take up the study of artificial intelligence.

  • Career Growth for an Individual:

AI-driven organizations are creating the role of AI engineer, AI Specialist etc. These are people who can who can perform multiple tasks of data engineering, data science, and software development. They understand how to extract data efficiently from a various source, build their own machine learning models, and deploy those models using AI-infused applications.

Artificial Intelligence has turned from a niche technology into a mainstream computer science engineering subject. Big companies like Google, Facebook, LinkedIn and many others are heavily investing for Careers in Artificial Intelligence. Careers in Artificial Intelligence have become the heart of new IT developments in areas like automation, DevOps platforms, robotics, and Internet Chabot.  It is a fast-paced and challenging field that is making visible inroads into our everyday life. There has been a considerable rise in big-data-centric AI like data mining and machine learning of web data and very large curated databases.

  • Few Job profile and Job Titles are listed below:


  1. Research Scientists / Applied Research Scientists:

Research scientists work on the data leads uncovered by data scientists. They do experiments with novel approaches and are focused on driving scientific discovery. They may be less concerned with pursuing industrial applications of their findings. Applied research scientists tie these two fields together.  With backgrounds in both data science and computer science, they are most important members of any AI team.

  1. Machine Learning Engineers:

Machine learning engineers are people with backgrounds and skills in data science, applied research and heavy-duty coding. They are at the center of any machine learning project. They are responsible for running the operations of a machine learning project and also for managing the infrastructure and data pipelines needed to bring code to production. A machine learning engineer must be able to draw the line between knowing the mathematics and coding the mathematics.

  • Machine Learning and Artificial Intelligence Scientist:

The Artificial Intelligence Scientist are responsible for Designing, building and implementing AI business solutions. They work as an independent but integral member of a team to develop innovative and creative AI Chatbot and Machine Learning applications. They are expected to build and implement architecture roadmaps for next generation Artificial Intelligence projects. They need to actively participate in related Artificial Intelligence communities and technology forums.

  1. Robotics Technician:

A Robotics technician follows the prints and process sheets to assemble machines. They are responsible for aligning, fitting, or assembling component parts using hand tools, power tools, fixtures and microscopes. They also disassemble and reassemble robots or peripheral equipment to make repairs. They have to replace defective circuit boards, sensors, controllers, and other devices, as per the requirement. They also have to document robotics test procedures and result and test the performance of robotic assemblies, using precision on slugs, chips etc. They work with Engineering on new product introduction and train robots, using artificial intelligence software or interactive training techniques, to perform simple or complex tasks. Robotics technicians are also responsible for maximum quality by evaluating the efficiency and reliability of industrial robotic systems, reprogramming or calibrating

  1. Business Intelligence Developer

This is a high demand job. The primary job of a Business Intelligence Developer is to analyze complex data and keep a constant look on current business trends and derive insights that result in increase in profitability and efficiency of the organization. They are masters of strong technical and analytical skills. They should also have strong communication and problem-solving skills. They are responsible for designing, building and maintaining data for complex and highly accessible data platforms.

  • Who Can Learn Artificial Intelligence?
  • Any professional from Data Analytics background

  • Engineering or Non-Engineering aspirants wanting to specialize in Artificial Intelligence

  • Maths students who want to research in Artificial Intelligence and Robotics

  • Any Data Analyst or Software Developer aspiring to pursue a career in AI

  • Professionals wanting to build machine learning models, using distributed storage and distributed processing

  • Prerequisites to Study Data Science

To pursue Artificial Intelligence, you need knowledge of following streams:

  • Basic Programming Languages like C, C++ and Java
  • High level Programming Language i.e Python, R or any other
  • Mathematics like Calculus, Probability, Matrices and Statistics.
  • Computer Science.
  • Courses in Data science:
  • PG Program in Machine Learning and AI
  • Advanced Program in Data Sciences
  • Microsoft Professional Program in Data Science.
  • MSC in Artificial Intelligence.
  • Tech in Computer Science and Technology (AI)