Genpact Launches The ML Incubator 2.0 Program

Genpact, a global professional services firm delivering digital transformation for Global Fortune 500 companies, has been strategically strengthening its resource pool of data scientists through its one-of-a-kind upskilling and re-skilling initiative – ML Incubator program. The program envisions to upskill its existing process and domain experts with the latest tools, techniques and technologies on data science, visual storytelling and augmented intelligence advisory. It is an in-house, meticulously structured instructor-led program which drives contextualised learning to employees alongside their regular flow of work through flexible learning paths and bite-sized learning material, housed on Genpact’s learning framework, Genome.

The first run of this program yielded highly promising results with 600+ employees graduating successfully in 2019. These employees are now actively driving meaningful business outcomes for Global Fortune 500 companies by redefining legacy business processes through artificial intelligence and machine learning (AI/ML), influential storytelling and augmented intelligence advisory skills.

The triumphs and the learnings from the first run of the program have enabled Genpact’s Learning and Development team to launch a reinvigorated – ML Incubator 2.0 program in partnership with Jigsaw Academy/Manipal Prolearn. The program now has three tracks – data science, visual storytelling and augmented intelligence advisory. 

The objectives of these tracks are mentioned below - 

• Data Science – to equip employees with the latest domain relevant AI/ML algorithms across various data science pillars
• Visual Storytelling – to train employees on the best-in-breed data visualization tools and storytelling techniques 
• Augmented Intelligence Advisory – to upskill employees on how to identify opportunities for augmented intelligence embedment across enterprise business processes 

The partnership with Jigsaw Academy and Manipal Prolearn has amplified the rigor of the program through pivotal elements –

• Experiential expertise of trainers – The trainers with optimal academic and industrial experience will deliver customised learning content to employees, with domain relevant examples. The exposure allows employees to retain their learnings for longer periods. 
• Access to safe sandbox-based learning environments –The ‘hands on’ learning experience with simulations or practice examples facilitated through sandboxes, allows employees to realise real world implementation challenges of latest tools and technologies.
• Real world business challenges focused case studies – Case Study based exercises enable employees to appreciate the pragmatic application of augmented intelligence and broadens their problem-solving capabilities.  

During the initial months of the training, employees will learn through self-paced tutorials on basic concepts and latest trends. In the next phase, the advanced concepts, relevant tools and technologies are introduced to employees through instructor led training sessions. In order to reinforce ‘Learning by Doing’ principles, employees are facilitated with safe sandbox environments, where they can practice and strengthen their grasp on concepts through simulations, practice examples and case studies. The end-to-end learning cycle is embedded with intermittent assessments which mimic real world business challenges. The graduates of ML Incubator 2.0 program will then be seasoned with pragmatic business challenges in the form of live customer projects through ML Upgrade 2.0 program.

The program has the potential to create an unparalleled Digital upskilling and re-skilling capability. Overall, the program has uniquely positioned Genpact with multi-year and multi-fold benefits like –

• Nurturing a truly adaptive workforce by developing more T-shaped professionals who can assess and drive augmented intelligence-led digital transformation projects at scale for clients
• Driving faster time-to-value for clients by engaging graduates of ML Incubator 2.0 programs in redefining legacy business processes
• Circumventing through the demand vs supply imbalance of data scientists by incubating in-house talent