Great Learning Introduces New Program in Artificial Intelligence and Machine Learning

Great Learning has witnessed massive demand from professionals for its program in Artificial Intelligence and Machine Learning. Great Learning has received nearly 2000 applications from mid-senior IT, BFSI and Analytics professionals for 40 seats.

The first batch has a collective experience of over 520 man-years with an average experience of about 13 years, ranging from 6 to 21 years. Even very senior executives, with over 20 years of experience have joined the course.

The program garnered the tremendous response from professionals in Bangalore with more than 2000 of them indicating their interest for enrolling for it. More than 60% of professionals in the batch are from IT and ITES industries, 25% from BFSI and the rest from other industries like healthcare, telecom and manufacturing.

Companies they represent include IT and BFSI leaders like the likes of IBM, Infosys, Fidelity Investments, SAP Labs India & JP Morgan Chase. Some of the areas in which students can expect to transition after completion of the course are Artificial Intelligence, Deep Learning, Automation and Machine Learning.

According to a research by Markets and Markets, the spending on machine learning technologies and applications is expected to grow from USD 1.03 billion in 2016 to USD 8.81 billion by 2022, a compound annual growth rate of 44.1 per cent. Demand for artificial intelligence and machine learning specialists in the country is expected to see a 60% rise this year due to increasing adoption of automation, as per a report by KellyOCG India.

The report further throws light on the average salary of AI professionals in India across the industries. Professionals with 2-4 years experience commands a salary of Rs 15-20 lacs per annum, while those with 4-8 years of experience command as much as Rs. 20-50 lacs per annum. Those with 8-15 years of experience can command as much as Rs. 50 lacs to Rs 1 crore per annum.

Great Learning’s course is exhaustive in nature and is designed to enable professionals to transition to a career in AI and ML. The course covers topics like Neural Networks, Face Recognition, Text and Speech Recognition, Natural language processing and Recommendation systems which enable a student to operate in these technologies professionally.