IBM AI Engineering Professional Certificate (V2)

Authorized by IBM

This badge earner has demonstrated proficiency in Machine Learning (ML) and Deep Learning (DL). The earner understands various ML techniques such as regression, classification, clustering and recommender systems. The earner is able to build, test and deploy DL models using libraries such as Keras, PyTorch and Tensorflow. The earner has completed several ML and DL projects and is now armed with skills for starting a career in AI Engineering.This badge earner has demonstrated proficiency in Machine Learning (ML) and Deep Learning (DL). The earner understands various ML techniques such as regression, classification, clustering and recommender systems. The earner is able to build, test and deploy DL models using libraries such as Keras, PyTorch and Tensorflow. The earner has completed several ML and DL projects and is now armed with skills for starting a career in AI Engineering.WWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWThis badge earner has demonstrated proficiency in Machine Learning (ML) and Deep Learning (DL). The earner understands various ML techniques such as regression, classification, clustering and recommender systems. The earner is able to build, test and deploy DL models using libraries such as Keras, PyTorch and Tensorflow. The earner has completed several ML and DL projects and is now armed with skills for starting a career in AI Engineering.

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Skills

Earning Criteria

Occupations

AI Systems Engineers

Develop deep learning and computer vision applications for Autonomous Devices. Develop applications for AI devices using existing AI Platforms. Understand interplay of hardware and software architectures on future algorithms and applications to develop AI Platforms.

Machine Learning Engineers

Create artificial intelligence products. Create machine learning models and retraining systems using knowledge of statistics, programming, data science, and software engineering.

Machine Learning Researchers

Conceive, research, and prototype new machine learning and high-performance computing techniques. Develop relevant software and hardware technologies with the goal of converting these into products. May also participate in the development of intellectual property.

Software Application Developers

Develop, create, and modify general computer applications software or specialized utility programs. Analyze user needs and develop software solutions. Design software or customize software for client use with the aim of optimizing operational efficiency. May analyze and design databases within an application area, working individually or coordinating database development as part of a team. May coordinate computer programmers.

Robotics Engineers

Research, design, develop, or test robotic applications.