Artificial Intelligence has turned from a niche technology/computational area into a mainstream computer science engineering toolkit. It has generated chaos in Silicon Valley and big IT giants like Google, Facebook, LinkedIn and many others are heavily investing for Careers in Artificial Intelligence.

Artificial Intelligence goes with a tagline “The Future is Automation” and the newbies are also starting up with these technologies as the market is very new for enterprise-level stuff.  It is expected that Careers in Artificial Intelligence will be at the heart of new IT developments in areas like automation, DevOps platforms, the Internet Chat bot, and robotics. Careers in Artificial Intelligence is a  fast-paced and challenging field that is making visible inroads into our everyday life.

How to become a AI expert

• Foundation Programs in Machine Learning and AI
• MTech in computer science and specialisation in artificial Intelligence
• MTech in Artificial Intelligence
• PG Diploma in Machine Learning and AI
• Short Term Certifications in AI

• Well versed with various  Programming languages
• Interpersonal Communication Skills
• Problem solving Skills
• Industry knowledge
• Management and Leadership Skills
• Team work
• Creative Thinking
• Solid Knowledge of Mathematical and Algorithms
• Distributed Computing Efficiency
• Good Command over UNIX Tools
• Knowledge of advanced signal processing techniques

• Matriculation with minimum 60% marks and Sr. Secondary (10+2) 70% marks (Aggregate) & minimum 60% marks in PCM Computer Science/PCB

• Machine Learning Engineer expert
• Natural Language processing-NLP and Speech Recognition
• Al Expert-Deep Learning
• Al Expert-Cognitive Computing
• Al Expert-Avionics Al
• AL Expert-Predictive APIs
• Visual Computing and Image Recognition/Computer vision
• Robotics, Gesture and motion control

• Recognition of speech and communicating, answering questions, giving insights, reacting to human emotions etc.
• Search for information and convey the search results, analyze information to recommend possible decision options and also recommend the best possible course of action in a given situation.
• Research on AI Topics and build prototype on identified areas
• Design experiments for testing hypotheses for AI Technology or solution development
• Develop machine learning model.
• Develop deep learning architecture and algorithm, neutral engineering architecture and algorithm, natural language processing algorithm and algorithm using other AI Technologies.
• Write codes (Computer programs) to build AI Systems.
• Research, develop and optimize AI applications.
• Perform research to advance the science and technology of intelligent machines.
• Apply knowledge of relevant research domains along with expert coding skills to platform and framework development projects.
• Design machine learning systems.
• Select appropriate data sets and data representation methods.
• Run machines learning tests and equipment’s.
• Perform statistical analysis and fine –tuning using test results.